IMPACT OF MGNREGA ON WAGE RATE, FOOD SECURITY AND RURAL URBAN MIGRATION: A

CONSOLIDATED REPORT

PARMOD KUMAR

Agricultural Development and Rural Transformation Centre Institute for Social and Economic Change

Bangalore- 560 072

December 2013

Project Leader: Prof. Parmod Kumar

Project Team:

1. Ms. Prema Kumari

2. Ms. Neelambari Dasgupta

3. Dr. I Maruthi

1

Chapter 1

Introduction

1.1 Introduction

A majority of people in India live in villages and about 50 per cent of the villages have

very poor socio-economic conditions. Since the dawn of independence, concerted efforts

have been made to uplift the living standards of rural masses. Rural development as an

integrated concept of growth and poverty elimination has been of paramount concern in

all the consequent five year plans. The Ministry of Rural Development, Government of

India, runs a number of schemes and programmes with the principal objective of enabling

rural people to improve the quality of their lives. In the process of planned development,

it has been realized that a sustainable strategy of poverty alleviation has to be based on

increasing the productive employment opportunities in the process of growth itself. In the

Sixth Five Year Plan emphasis was laid on employment generation and poverty

alleviation. To generate additional gainful employment in rural areas, Ministry of Rural

Development, Government of India launched National Rural Employment Programme

(NREP) in October 1980. Under this programme, an outlay of 1620 crores was

provided which was to be shared equally between the Centre and the States. The creation

of durable assets was an important objective of this programme.

The total employment generated and expenditure incurred under the NREP is depicted in

Table 1.1. However, this programme was not targeted and therefore, it is not known as to

how much of out of total expenditure was directed towards those who were landless and

the poorest among the poor. To this extent, the programme apparently lacked a direct

focus on the target-group population for whom it was meant. The programme, however,

had a substantial impact in terms of stabilization of wages in the rural areas, containing

prices of foodgrains and creation of a wide variety of community assets which could be

expected to help raising the levels of living of the rural population.

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Table 1.1: Performance of NREP in the Sixth and Seventh Five Year Plans

Source: Planning commission, GOI (2001)

On 15th

August 1983, Rural Landless Employment Guarantee Programme (RLEGP), a

programme to supplement NREP was introduced by the Ministry of Rural Development,

Government of India, with the objective of improving and expanding employment

opportunities for the rural landless. The prime objective of this programme was providing

guaranteed employment to at least one member of every landless household up to 100

days in a year and creating durable assets for strengthening infrastructure so as to meet

the growing requirements of the rural economy. An outlay of 500 crores to be fully

financed by the Central Government was provided under this programme under the Sixth

Five Year Plan.

Table 1.2: Performance of RLEGP in the Seventh Five Year Plans

Year

Resource

availability

( crores)

Expenditure

( crores)

Employments

generation

(in million

man days)

Man-day

cost ( )

Wage:

Material

ratio

1985-86 580.35 453.17 247.58 18.30 57.43

1986-87 649.96 635.91 306.14 20.77 57.43

1987-88 648.41 653.53 304.11 21.49 58.42

1988-89 761.55 669.37 296.56 22.57 58.42

Source: Planning commission, GOI (2001)

Year

Resource

availability

( crores)

Expenditure

( crores)

Employments

generation (in

million man days)

Man-

day cost

( )

Wage:

Material

ratio

1980-81 346.32 219.03 413.58 5.25 -

1981-82 460.37 317.63 354.52 9.04 62:38

1982-83 540.15 394.76 351.20 11.24 69:31

1983-84 535.59 392.22 302.76 13.08 62:38

1984-85 590.68 519.14 352.31 14.74 60:40

1985-86 593.08 531.95 316.41 16.81 60:40

1986-87 765.13 717.77 395.39 18.15 60-40

1987-88 888.21 788.31 370.77 21.26 59:41

1988-89 845.68 901.84 394.96 22.83 57:43

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The implementation of the programme was entrusted to the States/Union Territories, but

they were required to prepare specific projects for approval by a Central Committee.

During (1985) the Central Committee approved 320 projects with an estimated cost of

906.59 crores. The target for employment generation in 1983-84 and 1984-85 was fixed

at 360 million mandays against which 260.18 million man-days of employment was

actually generated. Experience in the Sixth Plan in certain states indicated that if

integrated projects are developed, this stipulation would still allow substantial scope for

productive works to be planned within a decentralized framework at the district level.

Hence both the projects viz., NREP and RLEGP were merged as Jawahar Rozgar Yojana

(JRY) in the last year of 7th

Five Year Plan. JRY was launched with a total allocation of

2600 crores to generate 931 million mandays of employment. The primary objective of

the programme was generation of additional employment on productive works which

would either be of sustained benefit to the poor' or contribute to the creation of rural

infrastructure. Under this programme, Centre's contribution was 80 per cent while States’

share was 20 per cent. The JRY was implemented in all villages in the country.

It was reported that Panchayats were not above procedural violations, i.e., use of private

contractors. Under the program, projects were to be executed by the Government

Ministries and agencies without the employment of contractors so that full benefit of

wages should go to the workers. The payments to contractors constituted at least 10 per

cent of the cost of project. Clear-cut guidelines were absent regarding the criteria to be

used by the Panchayats in selecting the rural poor. It was not enough only to indicate that

the JRY was targeted at the poor. In practice, the executing agencies did not follow any

list of workers belonging to poor families needing employment (Islam, 2005).

Central assistance was provided to the states on the basis of proportion of the rural poor

in a state/UT to the total rural poor in the country. Of the total allocations at the state

level, six per cent of the total resources were earmarked for housing under the Indira

Awaas Yojana (IAY), which were allotted to the Scheduled Castes and Scheduled Tribes

and freed bonded labour. In addition, 20 per cent were earmarked for Million Wells

Scheme (MWS). In fact, this scheme was launched as a special feature both under NREP

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and RLEGP in 1988-89. The objective was to provide open wells free of cost to poor

SC/ST farmers in the category of small and marginal farmers and to free bonded

labourers. However, where such wells were not feasible, the amounts allotted was to be

utilized for other schemes of minor irrigation like irrigation tanks, water harvesting

structures and also for development of lands of SCs/STs and freed bonded labourers

including ceiling surplus and bhoodan lands. A maximum of 2 per cent of JRY funds

were to be spent as administrative costs inclusive of any additional staff.

The Employment Assurance Scheme (EAS) was launched on 2nd

October, 1993 in 1775

identified backward blocks situated in drought prone, desert and tribal and hill areas in

which the revamped public distribution system was in operation by District Rural

Development Agency (DRDA). Subsequently, the scheme was extended to additional

blocks which included the newly identified Drought Prone Area Programme (DPAP) /

Desert Development Programme (DDP), Modified Area Development Approach

(MADA) and blocks having a larger concentration of tribal and flood prone areas of Uttar

Pradesh, Bihar, Assam and Jammu & Kashmir. In addition, 722 non-EAS blocks

previously covered under second stream of Jawahar Rozgar Yojana (JRY) were also

brought under the EAS. The EAS has since been universalized to cover all the rural

blocks in the country with effect from 1.4.1997.

The main objective of the EAS was to provide about 100 days of assured casual manual

employment during the lean agricultural season at statutory minimum wages to all

persons above the age of 18 years and below 60 years who needed and sought

employment on economically productive and labour intensive social and community

works. Though, the creation of community assets had important spin offs for rural

poverty and development, the impact of these programmes on employment and income

was limited. The universalisation of the scheme severely eroded its basic objective of

providing assured employment in areas of extreme poverty and chronic unemployment.

Allocations were based on a fixed criterion that did not specifically provide for regionally

differentiated needs. This led to a very thin spread of resources across the country. As a

result, even in the poorer regions, employment was provided for only 31 days (Panning

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Commission, 2001). In many states, the works taken up were not labour-intensive. Cases

of bogus reporting and fudged muster rolls were reported. The efficacy of the programme

was also affected by faulty project selection and the absence of a coherent plan which

integrated EAS projects in a long-term development strategy.

It was however felt that a stage has come when the development of village infrastructure

needs to be taken up in a planned manner. This could best be done by the village

Panchayats who are closest to the ground realities and who can effectively determine

their local needs. Accordingly, the government had restructured the existing wage

employment programme namely Jawahar Rozgar Yojana (JRY) and Employment

Assurance Scheme (EAS). The new programme, namely Jawahar Gram Samridhi Yojana

(JGSY) was dedicated entirely to the development of rural infrastructure at the village

level and implemented by the village Panchayat. This programme came into effect from

1st April 1999. The primary objective of JGSY was creation of demand driven

community village infrastructure including durable assets at the village level and assets to

enable the rural poor to increase the opportunities for sustained employment. The

secondary objective was generation of wage employment for the unemployed poor in the

rural areas. JGSY was least understood by the target groups and was seldom in its goal-

oriented implementation. So, JGSY lasted only for a short time which was being merged

into a new scheme, the Sampoorna Grameen Rozgar Yojana (SGRY).

In practice, there was little difference between the JGSY and EAS in terms of both

objectives and implementation failures, with the only sustentative difference being

administrative. The JGSY was implemented by village level institutions (PRIs) while the

EAS relied on the State Administrative apparatus. In September 2001, EAS and JGSY

were merged into a new scheme, the Sampoorna Grameen Rozgar Yojana (SGRY). The

objectives of SGRY were to provide additional wage employment in rural areas and also

food security, alongside the creation of durable community, social and economic assets

and infrastructure development. The SGRY also encompasses all food for work programs

in the country since it includes a special component for augmenting food security through

additional wage employment in calamity affected rural areas. Several problems in

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implementation were highlighted. It was documented that wages were too high in

relatively prosperous villages, leading to the use of migrant labour and machinery, while

in poor villages the wages were much lower than prevailing rates leading to crowding-out

of the really poor. Other problems were also observed such as flagrant violation of

government guidelines, including use of contractors and intermediaries, excessive

reliance on labour displacing machinery etc., (Deshingkar and Johnson, 2003).

The Planning commission identified 150 most backward districts of the country on the

basis of prevalence of poverty indicated by SC/ST population, agricultural productivity

per worker and agricultural wage rate. Most of them happen to be tribal districts. There

was a need for substantial additional investment in these districts to convert their surplus

labour into required capital formation solving livelihood issues. The National Food for

Work Programme (NFFWP) started on January 2000-01 by Ministry of Rural

Development, Government of India, was such an attempt. Substantial resources in the

form of cash and foodgrains were being provided under the programme to generate

additional supplementary wage employment and to create productive assets in these 150

identified districts. Through the programme, an attempt was made to coordinate among

different on-going schemes which had wage employment potential, so that the focused

approach provides a solid base for the districts to take-off on their own. The major

objective was to provide additional resources apart from the resources available under the

Sampoorna Grameen Rozgar Yojana (SGRY) to 150 most backward districts of the

country so that generation of supplementary wage employment and provision of food-

security through creation of need based economic, social and community assets in these

districts was further intensified. Wages under SGRY and NFFWP Programmes were paid

partly in cash and partly in the form of foodgrains valued at BPL rates. It was assumed as

an excess flow of foodgrains for the poor through the wage employment schemes.

National Rural Employment Guarantee Act (MGNREGA), now Mahatma Gandhi

National Rural Employment Guarantee Act (MGNREGA from October 2, 2009) was

passed in the year 2005. The ongoing programmes of Sampoorn Grameen Rozgar Yojna

and National Food for Work Programme were subsumed within this programme in the

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200 of the most backward districts of the country. First, it ensured the legal right to work

for a hundred days to poor people whoever is willing to work at a minimum wage rate,

particularly in the rural areas, which in turn would reduce the flow of rural to urban

migration (Dreze et al. 2006). In addition to this, another important objective of the Act

has been to strengthen the PRIs. MGNREGA addresses mainly to rural poor and their

fundamental right to work with dignity. It is noted from the above mentioned

employment programmes that MGNREGA envisaged a paradigm shift from all precedent

Wage Employment Programmes (WEP) operating in the country since 1980. Earlier

WEP were allocation based whereas MGNREGA is demand-driven. MGNREGA has

extensive in-built transparency safeguards. The act is designed to offer employment

within 15 days of application of work, if the employment cannot be provided by the

authorities then daily unemployment allowance has to be paid.

Unique features of MGNREGA are: time bound employment guarantee and wage

payment within 15 days; Incentive-disincentive structure to the state governments for

providing employment as 90 per cent of the cost for employment provided is borne by the

Centre while payment of unemployment allowances are borne by state governments (at

their own cost); and emphasis on labour intensive works prohibiting the use of

contractors and machinery. The Act mandates 33 per cent participation for women. The

key processes in the implementation of MGNREGA are the following:

Adult members of rural households submit their name, age and address with photo to

the Gram Panchayat.

The Gram Panchayat registers households after making enquiry and issues a job card

which contains the details of adult member enrolled and his/her photo.

Registered person can submit an application for work in writing (for at least fourteen

days of continuous work) either to Panchayat or to Programme Officer.

The Panchayat/Programme Officer will accept the valid application and issue dated

receipt of application, letter providing work will be sent to the applicant and also

displayed at Panchayat Office.

The employment will be provided within a radius of 5 kilometers and if it is above 5

kilometers extra wage will be paid.

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If employment under the scheme is not provided within fifteen days of receipt of the

application daily unemployment allowance will be paid to the applicant.

The cost sharing is done as: Central Government 3/4th

and State Government 1/4th

.

MGNREGA was implemented in three phases:

I Phase - notified in 200 districts with effect from February 2nd

2006

II Phase - extended to 130 districts in the financial year 2007-08 (113 districts

from April 1st 2007 and 17 districts of Uttar Pradesh were notified with effect

from May 15th

2007)

III Phase - remaining districts in all the States/UTs were notified from April 1st

2008.

1.2 Review of Literature

The recent literature on various aspects of MGNREGA functioning is expanding vary fast

as the programme encompasses the whole of the rural India and spends a huge budget

compared to any other social welfare programme. When compared to preceding

programmes like the NFFWP, the MGNREGA has generated roughly three to four times

the number of work days. The Programme has therefore succeeded in providing the much

needed wage employment to the rural masses. Among many recent studies focusing on

the implementation and operational details of MGNREGA, the important ones are Aiyar

and Samji (2006), Bhatia and Dreze (2006), Chakraborty (2007), Comptroller and

Auditor General (2008), Ambasta et al. (2008), Jha et.al. (2009), Gopal (2009), Khera

and Nayak (2009), Adhikari and Bhatia (2010), Jha et al (2011), Shankar et al (2011),

Dutta et al (2012) and so on.

Aiyar and Samji (2006) argue for strengthening social audit in order to improve the

effectiveness of MGNREGA Programme. They argue that the earlier wage employment

programmes failed due to the common problems of ineffective targeting, leakages and

poor quality asset creation, etc. They emphasized for a clear separation of functions

across tiers of government. The Gram Panchayat (GP) along with Zila Panchayat should

be responsible for all operational activities whilst the state government should take

9

overall monitoring and regulation of the process. According to them such a system

allows the GP flexibility to respond effectively to citizen needs and priorities without

depending on any external authority. It also prevents tiers of government from passing

responsibility for performance on to one another, as is common in the present system.

Secondly, the citizen must play the central role in monitoring the provision of public

services. In such a system the regular flow of information would be crucial as well as the

enhanced ability of citizens to exercise enforceability through tools such as social audits

and community score cards will have to play a major role.

The Comptroller and Auditor General (CAG) carried a review of MGNREGA scheme in

which it found many loopholes in the implementation of MGNREGA in various parts of the

country (CAG, 2008). In 26 states, 558 village panchayats were identified for the survey

spread over 68 districts and 141 blocks. The study observed that in as many as 70 per cent of

villages checked, there were no proper records available on number of households who

demanded jobs and the actual number of people who benefited from the job guarantee

scheme. In many cases it was found that jobs were allocated on "verbal basis" and no

documentation was available with the village body. As per the survey findings, in 340

villages in 24 states, no meetings were conducted for identifying the households to be

registered under MGNREGA. No door-to-door survey was conducted in these villages to

identify persons. Some households were not registered despite submitting applications on the

ground that their names did not feature in the BPL survey list.

Chakraborty (2007) presents a budgetary appraisal of MGNREGA. The study observed

that the existing institutional arrangement in poorer states was not good enough to

implement the MGNREGA in an effective manner. Only half of the total available funds

were utilised and the utilisation ratio was particularly low in poorer states. There was an

urgent need for both vertical and horizontal coordination across levels of governments

within the states. The paper suggests that the devolution of responsibilities and strict

accountability norms would accelerate capacity building at the level of the panchayat and

the scheme could effectively function as a demand-driven one. Keeping the spatial

dimension of the implementation in mind, the importance of the smooth flow of funds for

implementation of projects in accordance with the demand, capacity building at the

10

village level, right to information to enable social audits effectively, accountability of

functionaries and an effective grievance redressal mechanism assume critical importance.

The paper further elaborates that better coordination by the levels of governments with

the gradual expansion of the programme covering more districts would lead to increased

outlays and one would hope that the programme effectiveness will increase with

experience, particularly in poorer states.

Dreze et al. (2008) in their evaluation study in Chhattisgarh found MGNREGA

functioning far better than the other employment programmes. They observed that there

was virtually no check on the embezzlement of NFFWP funds in Surguja district of

Chhattisgarh. The situation was so bad that it was constrained to describe NFFWP as

“Loot for Work Programme”. In the same district, it was interesting to hear from a wide

range of sources where the enactment of MGNREGA had led to a steep decline in the

incidence of corruption. This was borne out by the muster roll verification exercises. In a

random sample of nine works implemented by gram Panchayat, it was found that 95 per

cent of the wages that had been paid according to the muster rolls had actually reached

the labourers concerned. A similar exercise conducted in Koriya, the neighboring district,

led to similar estimates of “leakages” in the labour component of MGNREGA by only 5

per cent or so. In Jharkhand, detailed muster roll verification of MGNREGA works in

five randomly selected gram Panchayat of Ranchi District suggested leakages of around

33 per cent. In Jharkhand, there was evidence of a gradual retreat of corruption compared

with earlier years when it was not uncommon to find that entire muster rolls had been

manufactured from top to bottom. Another study by Bhatia and Dreze (2006) highlights

the weaknesses in the implementation of the project in Jharkhand.

In a similar study, Afridi (2008) discussed the nature and characteristics of monitoring

the MGNREGA‘s implementation with a focus on the community control mechanisms

existing in the two pioneering states of Rajasthan and Andhra Pradesh. Having a close

look on the way social audit was held he pointed out that conduct of audits in villages

without the support of NGOs and members of civil society is wishful thinking. He found

that CSOs had taken a lead role in Rajasthan in generating awareness and participation of

11

rural people with a bottom up approach, while in Andhra Pradesh the Government had

taken the lead role in initiating this process and co-opted individuals from

nongovernmental institutions into the process which was more of a top-down approach.

The study suggested synthesizing both the models for more effective monitoring of

MGNREGA activities.

Jacob (2008) observed that the MGNREGA programme has immense potential to

improve the gap between urban and rural India and lead to rural development in terms of

basic infrastructure like roads, in terms of agricultural productivity from irrigation works.

It also provides a stable income for workers; their income graph would be much smoother

with the MGNREGA bolstering their earnings in the 100 days between agricultural

seasons. The efforts made by the Villupuram district (of Tamil Nadu) authorities though

efficient functioning of MGNREGA, although there still might be some irregularities in

the implementation should be used as a model in other regions to help realize the

potential of this Act.

In another study (ISWSD, 2008) observed that both in Kerala and Karnataka there were

strong demand from the workers for increasing the work days to at least 200 per

household. However, in both the states, there were few complaints regarding non-

payment of minimum wages. In gross violation of the Act, workers at many MGNREGA

worksites (e.g., in Uttar Pradesh and Jharkhand) were earning less than the minimum

wages.

Ambasta et al (2008) evaluating the performance of MGNREGA in its first two years

highlights major issues confronting its implementation. The study found that the lack of

trained professionals for time bound implementation, under staffing and delay in

administration, lack of people‘s planning, poor quality of works and assets created,

inappropriate schedules of rates, unnecessary bureaucratic interventions and mockery of

social audits were hindering the implementation process. The authors suggested for hiring

a large number of full-time and fully trained professionals at Gram Panchayat level, while

strictly enforcing their accountability to PRIs. Better use of information technology,

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mandating a role for civil society organizations (CSOs) to work as support agencies for

PRIs in MGNREGA planning, implementation and social audit were some of their major

suggestions for improving the functioning of MGNREGA.

Khera (2008) observed that the role of farmer‘s organization was very effective in

making MGNREGA perform better. Her study on the Jagrut Adivasi Dalit Sangathan, a

farmer‘s organization with a membership of 3500 families in Madhya Pradesh observed

that the level of employment in the Sangathan areas was as high as 85 days per household

per year, and nearly half of all working households had got 100 days of work. Aiyar and

Samji (2009) document the Andhra Pradesh experience of institutionalizing social audits

into the implementation of the MGNREGA and use it to analyze the social audit process.

The paper draws on empirical work aimed at measuring the effectiveness of social audits

conducted in Andhra Pradesh between March and December 2007. The paper offers

some interesting insights in to the effectiveness of regular, sustained social audits.

Emerging empirical evidence on the social audits suggest social audits in fact have a

significant and lasting effect on citizen’s awareness levels. Moreover, it demonstrates that

it has some effects on implementation processes and in this process, ability to engage

with local officials. Crucially, it highlights some important lessons on how to ensure long

term effects of the audit. According to findings of the paper social audits are most

effective when they are conducted regularly, have inbuilt feedback mechanisms and are

undertaken in partnership with the state to ensure immediate, perceivable grievance

redressal. These lessons are important for any state government or civil society

organization that wants to undertake a social audit and develop a strategy for their

conduct.

Khera and Nayak (2009) undertook a study on perceptions of women workers regarding

the importance of the MGNREGA and to find out to what extent the full potential of the

programme has been realized by taking samples from Araria and Kaimur (Bihar); Surguja

(Chhattisgarh); Palamau and Koderma (Jharkhand); Badwani and Sidhi (Madhya

Pradesh); Dungarpur and Sirohi (Rajasthan); Sitapur (Uttar Pradesh). The study found

that the participation of the sample women workers varied largely across the selected

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study areas in various states. The overall women participation rate was 32 per cent

whereas the same in Rajasthan was as high as 71 per cent. The women participation rate

in Madhya Pradesh, Chhattisgarh, Jharkhand, Bihar and Uttar Pradesh was respectively ,

44 per cent, 25 per cent, 18 per cent, 13 per cent and 5 per cent as compare to stipulated

female participation rate of 33 per cent as per the MGNREGA guideline. Of the total

sample, more than 2/3rd of the sample workers stated the MGNREGA had helped them

avoid huger, while 57 per cent stated avoid migration. A majority (79 per cent) of women

workers were found to collect and keep their own wages. Major barriers to women's

participation were tenacious social norms, illegal presence of contractors, lack of

childcare facilities, and delayed payment of wages.

Jha et al. (2009) use primary data of 900 households to examine the extent of elite

capture in MGNREGA in Andhra Pradesh and Rajasthan. They observed that area of land

owned is a negative predictor of MGNREGA participation in Rajasthan, but the situation

is reversed in Andhra Pradesh indicating poor targeting due to possibly elite capture in

that state. In an another study Jha et al (2011) analyse the nutritional impact of

MGNREGA wage, non MGNREGA income and Public Distribution System (PDS)

participation. The study concludes that MGNREGA affects nutritional status of

households with respect to two macro nutrients, namely calories and protein as well as

various micronutrients. Assessing the link between information, access and delivery of

MGNREGA in Andhra Pradesh, Maharashtra and Rajasthan, Shankar et al (2011)

observed that information increases the propensity of access by those who are not

MGNREGA’s primary target, whereas, lack of information unambiguously disadvantages

the poor.

According to a NCAER-PIF study (Sharma et al, 2009) there were two possible outcomes

of MGNREGA, viz., (i) slightly improved share of ST households in employment and (ii)

the Act outshined the earlier Programme as for as participation of women was concerned.

The range of wages realized by workers under MGNREGA varied from state to state, but

in a large majority of states the average wages were little higher compared to the

minimum wages. However, the official estimates of wages realized by workers were

14

generally inflated as wages received by workers were much less than what was shown in

the official documents. The other anomalies they pointed out include no compensation

being paid to labourers in cases involving delayed payments beyond the stipulated period

of 15 days and non-payment of unemployment allowances. Cases of corruption, fudging

in muster rolls, discrepancies in work days and payments were also reported. More than

50 per cent slippage in the execution of works undertaken was reported. Works and their

implementation had also suffered due to anomalies in the selection of works, poor

execution, inflated estimates and inadequacies in measurement, cost overruns and delays

in release of funds by states.

Gaiha et al (2009) tried to construct an intuitive measure of the performance of the

MGNREGA. Their paper focused on whether excess demand responds to poverty and

whether recent hikes in MGNREGA wages were inflationary. Their analysis confirms

responsiveness of excess demand to poverty. They observed that apprehensions

expressed about the inflationary potential of hikes in MGNREGA wages were confirmed.

The higher MGNREGA wages were likely to undermine self-selection of the poor in the

programme. They suggested in order to realise the poverty reducing potential of this

scheme, a policy imperative was to ensure a speedier matching of demand and supply in

districts that were highly poverty prone, as also to avoid the trade-offs between poverty

reduction and inflation.

Kareemulla et al (2010) evaluated the scheme in four states, viz., Rajasthan, Andhra Pradesh,

Karnataka and Maharashtra with a specific focus on desirability, quality and durability of

assets created and the programme’s effects on the livelihood generation of beneficiaries. The

study found that a wide variety of works were taken up under the scheme in the study

districts including works on soil and water conservation structures and rural roads, which

matched the requirements of the people but the quality and maintenance of assets need more

attention in the coming years so that investment made would not go futile. They concluded

that scheme was achieving its primary objective of employment generation but the assets

created were generally seen as a by-product in the study areas.

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Adhikari and Bhatia (2010) argued that the direct transfer of wages into worker's bank

account was a substantial protection against embezzlement and control of corruption.

Respondents had a fairly positive attitude towards bank payments, and they showed interest

in learning how to use the banking system. However, poor record-keeping, inability to cope

with mass payment of MGNREGA wages, large distance to the nearest bank or post office

caused hardship to the MGNREGA workers. Their findings revealed positive picture of the

bank payments, but they also exposed the limited capacity of the banking and post office

system in fighting corruption.

Dey (2010) looked at the performance of the MGNREGA from three perspectives: it

examined the targeting aspect of the programme, the efficiency of the implementing PRI

bodies and the impact of the program on various outcomes at household level. The study

was based on primary data collected from 500 randomly selected households, 2249

individuals and 70 schemes located in 13 Gram Panchayats in Birbhum District of West

Bengal. The study observed that in Birbhum District, the programme was likely to be

accessed by poorer households, defined in terms of land holding, monthly per-capita

income and other household related characteristics. At the same time there was a clear

and substantial impact of left political inclination in terms of enabling access to a greater

number of days of work under the scheme. In terms of the efficiency impact, the analysis

revealed a clear violation of the formal clauses and the spirit of the MGNREG Act and

thereby undermining the potential of the programme in terms of providing a safety net.

The study found no statistically significant impact on economic outcomes at household

level but there existed a statistically significant relation between reduction of stress

related to joblessness and access to the MGNREGA. The author observed that while the

MGNREGA may not be creating any new employment and may indeed be substituting

for existing employment opportunities, the scheme was still considered valuable as it

offered better working conditions.

The study by Harish et al (2011) evaluates the impact of MGNREGA on income

generation and labour supply in agriculture in one of the districts in central dry zone of

Karnataka. The results of the study showed that for the participating families the numbers

of days worked in a year with the implementation of MGNREGA programme had

16

increased significantly to 201 days, reflecting 16 per cent increase. The authors observed

that MGNREGA contributed to increase in the consumption expenditure reducing the

debt burden of the beneficiaries. Regression analysis carried out to find out the

determinants of participation revealed that gender, education and family size of the

workers were the significant factors influencing the worker’s employment under the

Program. The increase in income was to the tune of 9.04 per cent due to additional

employment generated from MGNERGA. In the total income, the contribution of

agriculture was the highest (63%), followed by non-agricultural income (29%) and

MGNREGA income (8%). Implementation of MGNERGA works has led to labour

scarcity to the tune of 53 per cent and 30 per cent for agriculture operations like weeding

and sowing, respectively. There was a decline in area for labour intensive crops like

tomato and ragi to the extent of 30 per cent due to MGNERGA implementation.

Basu (2011) examines labor and output market responses to MGNREGA and determine

the optimal compensation to public work employees consistent with the objectives of

productive efficiency in agriculture and welfare maximization of the laborers. By

accounting for the seasonality in agricultural production and the institution of permanent

labor contracts, the paper shows that technological change and productivity increases in

MGNREGA programs tend to make laborers better-off as compared to a direct increase

in the wage paid at the relief program. Further, an optimal wage that maximizes expected

agricultural output may be in conflict with the one that maximizes the expected lifetime

utility of laborers indicating trade-offs between different policy objectives. Further, in the

event of high elasticity of MGNREGA with respect to permanent laborers, a specific

subsidy targeted towards the hiring of permanent laborers would best serve the twin

objectives of increased expected agricultural productivity and increased welfare for the

laborers. The paper concludes that MGNREGA by introducing contestability in the

agricultural labor market can yield a host of interesting implications for the wage and

employment patterns of the rural poor.

Mukherjee and Sinha (2011) using a theoretical model analyzed the impact of

MGNREGA scheme on rural labour market; income of the poor households; and overall

17

agricultural production. The paper finds that the income from MGNREGA alone can be a

substantial part of the target income of the poor. The poor may exhibit a backward

bending supply curve of labour which may lead to an aggregate reduction in agricultural

output. This adverse production effect could happen even when the MGNREGA

activities lead to a moderate improvement in agricultural productivity. A crucial

dimension of the rural labour market is the target income of the poor. This target income

is the root cause of the backward bending supply curve of labour. So the policy focus

should be to increase this target income by creating more market access and opportunities

for the poor households and improving their standard of living. To enhance the

opportunities for the poor the policy should be inclusive and multipronged. The target

income may be enhanced by creating opportunities and market access from multiple

dimensions and not just an income generating scheme like MGNREGA that can help to

improve the situation of the poor households.

Berg et al (2012) test the impact of the MGNREGA on agricultural wages using monthly

wage data from the period 2000-2011 for a panel of 249 districts across 19 Indian states.

They observed that on average MGNREGA boosts the real daily agricultural wage rates

by 5.3 per cent. It takes 6 to 11 months for an MGNREGA intensity shock to feed into

higher wages. The wage effect appears to be gender neutral and biased towards unskilled

labour. They found it was positive across different implementation stages and months and

remained significant even after controlling for rainfall; district and time fixed effects; and

phase-wise linear, quadratic, and cubic time trends. They argue that since most of the

world’s poor live in rural areas, and the poorest of the poor are agricultural wage

labourers, rural public works constitute a potentially important anti-poverty policy tool.

Dutta et al (2012) used National Sample Survey (NSS) data for 2009-10 to verify the

guarantee of employment at the stipulated wage rates to the households seeking employment

under the Act. They observed considerable un-met demand for work in all states under

MGNREGA. The authors confirm that poorer families tend to have more demand for

work expectations on the scheme and that despite the un-met demand the self-targeting

mechanism allows it to reach relatively poor families and backward castes. The extent of

18

the un-met demand is greater in the poorest states, ironically where the scheme is needed

most. Labor-market responses to the scheme are likely to be weak. The scheme is

attracting poor women into the workforce, although the local-level rationing processes

favor men. The authors although find a significant negative correlation between the extent

of rationing and the wage rate in the casual labor market relative to the wage rate on the

scheme. However, the correlation vanishes when the level of poverty was introduced as a

control factor. Poorer states tend to see both more rationing of work on the scheme and

lower casual wages, possibly due to a greater supply of labor given the extent of rural

landlessness.

Imbert and Papp (2012) estimated the impact of MGNREGA on wages and employment

using NSS employment and unemployment cross sectional data. They used quinquennial

surveys and as well as thin round surveys starting from 60 round up to 66th

round. The

authors found that MGNREGA increases public works employment by 0.3 person-days

per month. They further observed that casual wage income of the workers increased by

4.5 per cent. Liu and Barrett (2013) using 2009-10 NSS data, analysed patterns of job-

seeking, rationing, and participation in the MGNREGA. At the national level, they found

that the self-targeting design of MGNREGA leads to greater rates of self-selection into

the programme by poorer and Scheduled Tribe or Scheduled Caste households. However,

the administrative rationing of MGNREGA jobs was not pro-poor but exhibited a sort of

middle class bias. At the state level, roughly half of 27 states exhibited rationing and

participation profiles that signal effective pro-poor targeting; the other half struggled to

avoid high rates and regressive patterns of administrative rationing of jobs to which the

poor had a legal right. They argued that households near the poverty line were more

likely to receive the jobs they sought than were the poorer households, although those in

the upper reaches of the expenditure distribution were least likely to secure MGNREGA

jobs. They further observed that MGNREGA fares less well in reaching poor female-

headed households, due both to self- selection and rationing effects. Male headed

households were more likely to seek and receive MGNREGA jobs over most of the per

capita expenditure distribution. According to them there was room for improvement and

perhaps much to be learned from an in-depth comparative analysis of MGNREGA

19

programme implementation across states that had demonstrated greater or lesser success

in targeting the poor with job opportunities.

Anderson et al (2013) suggest the role of Unique Identification (UID) in the functioning

of MGNREGA and how this new system can bring better efficiency in its functioning and

they also suggest to use control group methodology for testing the efficiency of UID

system in improving MGNREGA. The new UID system will enable payments to go

through the banking system. Bank accounts for MGNREGA workers will be linked to the

unique biometric id. As a result, the actual transfer of payments will immediately reach

the hands of who it is intended for. This should drastically reduce the inherent corruption

in the current system and increase the amounts and reliability of payments to the workers.

Using an experimental approach, it would be possible to directly identify the effects of

introducing UID on the performance of MGNREGA programs. One needs to compare

outcomes in a designated “treatment” group compared to a “control” group. In the

treatment group, individuals will receive their MGNREGA payments through UID. In the

“control” group, individuals will continue to receive their MGNREGA payments as they

do now. Comparing outcomes across these two groups, will inform us directly on the

impacts of introducing UID on MGNREGA payments.

The MGNREGA Scheme has high expectations in terms of employment generation,

alleviation of poverty, food security, halting migration and overall rural development. As

the scheme has already completed seven years of its functioning, there is a need for a

study to evaluate the scheme for its impact on rural poor. Based on this background the

study is conceptualized with the following objectives:

1.3 Main Objectives of the Study

1. Measure the extent of manpower employment generated under MGNREGA, their

various socio-economic characteristics and gender variability in implementing

MGNREGA since its inception in the selected states.

2. To compare wage differentials between MGNREGA activities and other wage

employment activities.

20

3. Effect of MGNREGA on the pattern of migration from rural to urban areas.

4. To find out the nature of assets created under MGNREGA and their durability.

5. Identification of factors determining the participation of people in MGNREGA

scheme and whether MGNREGA has been successful in ensuring better food security

to the beneficiaries.

6. To assess the implementation of MGNREGA, its functioning and to suggest suitable

policy measures to further strengthen the programme.

1.4 Methodology and Data Sources

The study is based on both primary and secondary data. Primary data was collected from

the selected villages and households in 16 states as per the guidelines of the Ministry.

From the each selected state, five districts were selected, one each from the north, south,

east, west and central locations of the state. From each districts, two villages were

selected keeping into account their distance from the location of the district or the main

city/town. One village was selected from the nearby periphery of around 5 kilometers of

the district/city head- quarters and the second district was selected from a farthest

location of 20 kilometers or more than that. From each selected village, primary survey

was carried out on 20 participants in MGNREGA and 5 non-participants working as

wage employed. In this fashion, from each state, 10 villages were selected and a total

number of 250 households were surveyed in detail with the help of structured household

questionnaire. In this way around 200 participants and 50 non participants were selected

from each state and data was collected in 16 states. The total sample consists of 3166

participants and 839 non participants. The selected states were, Karnataka, Andhra

Pradesh and Kerala in the South, Himachal Pradesh, Uttar Pradesh, Haryana and Punjab

in the North, Madhya Pradesh and Chhattisgarh in the Central, Maharashtra, Gujarat and

Rajasthan in the West, Bihar, and West Bengal in the East and Sikkim and Assam in the

North-east. The details of the selected districts (falling in different phases) for the study

and the number of participants and non participants selected in each state and the name of

the AERCs carrying out the study is provided in Annexure II.

21

For the selection of participant households, a list of all beneficiaries (participants) in the

village was obtained from the Gram Panchayat in the village along with the information

about caste factor of the workers. After getting the list, Random Sampling Method was

adopted for selection of the participant households. Attention was given for the proper

representation of Scheduled Caste, Scheduled Tribe and Other Backward Castes. A due

representation was also given to the gender factor. For the selection of non participant

households no list existed and therefore the criterion followed for them was that these

households should not have participated in MGNREGA but constitute the similar

occupation characteristics (wage earners) and socio economic wise, caste and gender

characteristics as that of selected participant households to maintain the uniformity and to

avoid the selection bias.

While selecting the districts utmost care was given to the fact that how many districts

implemented MGNREGA in the first Phase and how many did in the second and third

Phase in order to give proper representation to all the three Phases of the MGNREGA

implementation. While selecting participants, care was also taken to select participants

belonging to different socio-economic groups (e.g., tribal area, hilly area, gender and

Backward and Scheduled Caste groups etc.). The data was collected through structured

questionnaires. The data pertain to the Reference Period of January to December

2009.

In addition to household questionnaire, a Village Schedule was also designed to capture

the general changes that have taken place in the village during the last one decade and to

take note of increase in labour charges for agricultural operations after the

implementation of MGNREGA. The village schedule also has qualitative questions

related to change in life style of the villagers taking place during the last one decade. One

village schedule in each village was filled up with the help of a ‘Group Discussion’ with

the Pachayat Members, Officials, educated and other well informed people available in

the village being surveyed.

22

1.5 Overview

The report has seven chapters including the present one which provides a glimpse of

employment programmes started in the past and provides an introduction to the

MGNREGA programme and review of literature on the studies carried out in the

literature on the functioning of the MGNREGA. It also outlines the main objectives, data

base and methodology followed in the study. The second chapter is based on secondary

data which outlines manpower employment generated in all the states during the entire

functioning of the MGNREGA programme. The chapter also discusses various socio-

economic characteristics of employment generated and projects completed in each state.

The next three chapters are based on primary household survey carried out in 16 states.

Chapter 3 presents household characteristics and income and consumption pattern of the

selected participant and non participant households. To ascertain the factors that

determine participation in MGNREGA Programme, quantitative analysis has been carried

out in this chapter using logit and OLS regressions.

Chapter 4 discusses work profile, wage structure and migration issues under

MGNREGA. This chapter specifically looks into operational issues of MGNREGA

programme, like how many participant households obtained 100 days employment, how

wage rate obtained by the participants compares with the minimum wage rate in the state,

assets created and their durability etc. Chapter 5 presents some qualitative aspects of the

functioning of the MGNREGA Programme based on the household survey data. As was

mentioned above in our field survey of the villages, we held group discussion in all the

ten villages and Chapter 6 is based on the information collected through the group

discussion in the surveyed villages. The chapter summarizes the visible impact of

MGNREGA on various aspects of village economy like changes in occupation structure,

agriculture cost and wage rate in agriculture and non agricultural sector. The last chapter

7 summarizes the main findings of the report and provides policy suggestions for further

improvement in the MGNREGA Programme.

23

Chapter 2

Manpower Employment Generated Under MGNREGA

and their Socio-economic Characteristics

2.1 The implementation of MGNREGA

National Rural Employment Guarantee Act (NREGA) now Mahatma Gandhi National

Rural Employment Guarantee Act (MGNREGA from October 2, 2009) is being

implemented in India since by legislation on August 25, 2005 by the UPA coalition

government supported by the left parties. The Act is now covering all the 28 states of the

country. The basic objective of the Act is to ensure livelihood and food security by

providing unskilled work to people through creation of sustainable assets. The mandate

of the government is to implement the Scheme in the most transparent and effective way.

Under the provisions of the Act, the State has to ensure enhancement of livelihood

security to the households in rural areas by providing at least one hundred days of

guaranteed wage employment to every household whose adult members volunteer to do

unskilled work. The Programme was started as a flagship program in 2005 by the Union

Government. In-built with various transparency and accountability measures and

provisions for social audits this Act for the first time brings the role of the state as

provider of livelihood. The Act came into effect in all the districts in all 28 States as well

as 7 Union Territories (UTs) of India from April 1st 2008.

2.2 Total employment generated and their socio economic characteristics

Table 2.1 provides the overall performance of MGNREGA in terms of numbers of days

of employment created and the number of projects completed in all states during the

current year 2013-14 (up to October end 2013). A total number of 2.3 crore households

were provided employment during the current financial year till the latest estimates were

available and a total numbers of 63 crore man-days of employment was generated

through MGNREGA during this period. Looking at the socio-economic structure of

beneficiaries, around 23 and 15 per cent was the share of Scheduled Caste and Scheduled

Tribes, respectively in the total man-days generated while women had above 55 per cent

24

share in the total employment generated. Around 44 lakh works were taken up out of

which around 10 per cent works were completed and rest 90 per cent were ongoing.

The MGNREGA programme has already completed seven financial years and now

running in to eighth year. The current financial year provides data only up to October

2013 as discussed above. In order to provide snapshot of MGNREGA work since its

inception, we used the information available on the MGNREGA website which covers

seven full financial years starting from 2006-07 up to 2012-13 and data for the current

financial year up to October 2013. Table 2.2 provides state wise statistics on numbers of

days of employment created, their socio economic characteristics and the numbers of

projects completed and ongoing. At the aggregate, 81 crore households were issued job

cards during the period from 2006-07 to 2013-14 up to October. Out of which around 35

per cent demanded employment and around 97.5 per cent of them were provided

employment. At the aggregate, around 34 crore households were provided employment

during the period 2006-07 to 2013-14 averaging around 4.5 crore households working in

MGNREGA per annum that constitutes roughly around 30 per cent of the rural

households in the country as a whole.

The states that employed more than 3 crore households during the implementation of this

programme (2006-07 to 2013-14 up to October) were Andhra Pradesh, Uttar Pradesh,

Rajasthan, Tamil Nadu, West Bengal and Madhya Pradesh. The states that provided

employment between 1 to 3 crore households included Bihar, Chhattisgarh, Jharkhand,

Assam, Odisha and Karnataka (Figure 2.1). All other states provided employment to less

than one crore households. However, the more pertinent question is how many person

days of employment were generated by different states under this programme. Figure 2.2

presents the aggregate statistics of total person days of employment generated under

MGNREGA during the period of 2006-07 to 2013-14 (up to October). A total number of

1.5 thousand crore man days of employment was generated under MGNREGA during the

above mentioned time period. Out of the total person days generated, the share of

Scheduled Castes and Scheduled Tribes was 26.9 and 22.0 per cent, respectively while

share of women in the total employment was 48 per cent (Figure 2.2 and Table 2.2).

25

Figure 2.1: Cumulative number of HH provided employment

during 2006-07 to 2013-14 (numbers in crore)

Figure 2.2: Total person days generated under MGNREGA during

2006-07 to 2013-14 (days in crore)

26

Andhra Pradesh state topped in the generation of total person days (207 crore), followed

by Rajasthan 204 crore, Uttar Pradesh 166 crore, Tamil Nadu 166 crore, Madhya Pradesh

158 crore and West Bengal 93 crore during the period of 2006-07 up to 2013-14

(October). On the other hand, richer states like Haryana and Punjab generated less than 6

crore person days during the same time period. However, the participation of

economically weaker community, viz., Scheduled Castes in per cent age of person days

worked in MGNREGA was highest in richer state like Punjab (77 per cent), Haryana (52

per cent), Uttar Pradesh (48 per cent) and Tamil Nadu (42 per cent) while Scheduled

Tribes topped in north-eastern states like Mizoram (100 per cent), Nagaland (98 per

cent), Meghalaya (93 per cent), Arunachal Pradesh (87 per cent) and Manipur (65 per

cent). The percentage of women share in MGNREGA work was highest in Kerala (91 per

cent), Tamil Nadu (79 per cent), Goa (70 per cent), Rajasthan (68 per cent) and Andhra

Pradesh (58 per cent). Women share in the work was lowest in Jammu & Kashmir (only

14 per cent), Uttar Pradesh (19 per cent) and Bihar, Arunachal Pradesh and Assam (28

per cent, each).

Figure 2.3: Numbers of days per household employment generated

under MGNREGA during 2006-07 to 2013-14

27

State wise employment performance of MGNREGA is summarized in Figure 2.3 for the

period 2006-07 to 2013-14 (up to September). The figure depicts the numbers of days of

employment provided per household every year by the MGNREGA since the inception of

the programme. At the aggregate, a total number of 45 person days of employment has

been provided under MGNREGA during the implementation of this programme whereas

the target set under the programme is 100 days of employment per household. In other

words, not even half of the set target has been achieved by MGNREGA in terms of

providing employment. Only in the year 2009-10, 54 days of employment that is slightly

above 50 per cent of the target was achieved (Figure 2.4). In the beginning years of 2006-

07 and 2007-08, a total number of 43 and 42 days of employment was generated. In the

following year slightly more around 48 days of employment was generated which went

up to 54 days in 2009-10 but again came down to 47 days in 2010-11 and further slided

down to 43 days in 2011-12 and rose to 46 days in 2012-13. In the current financial year,

only 33 days of employment has been generated so far up to the month of October 2013

which is not expected to surpass the last two years range of above 43 to 46 days.

Figure 2.4: Employment generation under MGNREGA - All India

(Number of days per household)

28

Looking at the distribution of different states (Table 2.2 and Figure 2.3) the highest

numbers of days of employment (60 to 70 days) was provided by the north-eastern states

of Mizoram, Nagaland, Tripura, Sikkim and Manipur. Among the mainland states,

Rajasthan, Madhya Pradesh and Andhra Pradesh provided between 50 to 60 days of

employment. The states that lied in the middle providing 40 to 50 days of employment

included, Chhattisgarh, Himachal Pradesh, Tamil Nadu, Karnataka, Maharashtra, Uttar

Pradesh, Jharkhand and Odisha. Among the low performing states namely, Haryana,

Jammu & Kashmir, Uttrakhand, Gujarat, Kerala and Assam only 30 to 40 days of

employment was provided. The states that lied at the bottom included Bihar (31 days),

Arunachal Pradesh, West Bengal and Punjab (28 days, each) and Goa only 25 days of

employment.

How successful the MGNREGA programme in India has been in providing 100 days of

employment to those who demanded work. While at the aggregate per household

employment provided in all the states was far less than 100 days, however, there were

some households who completed 100 days of work in MGNREGA. Table 2.2 and Figure

2.5 provide statistics on the numbers of households who availed 100 days of employment

in each state during the whole period for which MGNREGA has been in operation. Out

of the total 34 crore households working in MGNREGA during its full tenure, only 2.9

crore households completed 100 days of employment. Among states, Rajasthan provided

100 days employment to 55 lakh households, followed by Andhra Pradesh, 49 lakh

households, Tamil Nadu 45 lakh households and Madhya Pradesh and Uttar Pradesh

both 25 lakh households, each. On the opposite, the richer states like Haryana provided

only 64 thousand households and Punjab only 25 thousand households hundred days of

employment under MGNREGA since the inception of the MGNREGA programme.

It is interesting to note whereas bigger states topped in the completion of hundred days of

employment like Rajasthan, Andhra Pradesh and Tamil Nadu, the percentage of

households who completed hundred days out of the households working in MGNREGA,

it was the north-eastern states which topped in the percentage term. Around 25 per cent

households completed 100 days in Mizoram, 20 per cent in Tripura, 18 per cent in

29

Sikkim and Nagaland each, 16 percent in Rajasthan and 14 per cent in Manipur. Tamil

Nadu and Andhra Pradesh were the other states where around 10 to 13 per cent

households completed hundred days of employment. Goa, Punjab and West Bengal were

at the bottom where only less than 2 per cent households completed hundred days of

employment (Figure 2.6). At the all India aggregate, only 8.4 per cent households

completed hundred days of employment during the entire period of MGNREGA in

operation up till October 2013. This indicates inefficiency of the programme in providing

hundred days work to all household who opted for working in the MGNREGA

programme.

Figure 2.5: Number of HH provided hundred days employment during

2006-07 to 2013-14 (numbers in lakh)

30

Figure 2.6: Percentage of HH completed hundred day of employment

during 2006-07 to 2013-104

2.3 Number of projects completed and total amount spent

There are around nine specific categories of works in which MGNREGA wage earners

are employed namely, rural connectivity, flood control and protection, water conservation

and water harvesting, drought proofing, micro irrigation works, provision of irrigation

facility to land owned by SCs, STs and others, renovation of traditional water bodies,

land development and other activities approved by MORD. The percentage allocation of

works completed or on-going during the entire period of MGNREGA implementation up

to October 2013 is shown in Figure 2.7 below. Looking at different activities under which

work was done, the Water conservation was the leading activity which occupied around

24 per cent projects (completed or under progress) followed by Rural connectivity

projects 17 per cent, Provision of irrigation 14 per cent, Drought proofing (13 per cent),

Land development 10 per cent, Renovation of traditional water bodies and Micro

irrigation 6 per cent, each and Flood control 3 per cent. Other works including Rajiv

Gandhi Seva Kendra occupied around 7 per cent share among the total works completed

or undergoing during the period from 2006-07 to 2013-14 up to October (Figure 2.7).

31

State wise details of works completed/under progress are given in Table 2.3 and the total

amount spent in Table 2.4 on each programme during the implementation of MGNREGA

up to December 2012. During the entire period of MGNREGA, a total number of 1 crore

projects were completed and around 2.9 crore were ongoing. Thus, out of total 4 crore

projects taken up under MGNREGA around 30 per cent were completed and rest of 70

per cent were in progress. Total amount spent on the above projects aggregated to

1,03,204 crores on the completed projects and 1,31,880 crores on the ongoing projects

during the entire period of MGNREGA. Thus a total amount of 2,35,084 crore was

spent on the MGNREGA during around 7 and a half years of functioning of the

MGNREGA with an average of slightly less than 30 thousand crore every year.

Presenting the budget for the financial year 2013-14, the Finance Minister has allocated a

sum of 33 thousand crore for MGNREGA work during the financial year 2013-14.

Working out the total expenditure incurred per project for the completed projects it

turned out around 87 thousand per project while it was 47 thousand per project for the

ongoing works giving the combined average of 59 thousand cost per project for all

MGNREGA works undertaken so far at the aggregate.

Figure 2.7: Share of different activities in MGNREGA work

during 2006-07 to 2013-14

32

Figure 2.8 presents the numbers of works completed or on-going for each of the above

nine activities during the implementation of MGNREGA. Out of the total 4 crore projects

undertaken, around 96 lakh projects were taken for water conservation, 67 lakh for rural

connectivity, 58 lakh for provision of irrigation, 52 lakh for drought proofing, 40 lakh for

land development and 23 lakh for renovation of traditional water bodies and micro

irrigation, each and around 13 lakh for the flood control and protection. Total amount

spent on completed and on-going projects during the implementation of MGNREGA is

given in Figure 2.9 and Table 2.4. During the whole period of implementation of

MGNREGA a total amount of 75 thousand crore was spent on rural connectivity, 45

thousand crore on water conservation, 27 and 25 thousand crore on renovation of

traditional water bodies and drought proofing, respectively, 17 thousand crore on

provision of irrigation, 16 thousand crore on land development, 12 thousand crore on

micro irrigation, 11 thousand crore on flood control and around 6 thousand crore on

other activities including Bharat Nirman works. Thus, at the aggregate, a sum total of

2.35 lakh crore were spent on MGNREGA works during the entire period starting from

2006-07 up to October 2013 (Table 2.4).

Figure 2.8: Numbers of works undertaken under MGNREGA

during 2006-07 to 2013-14 (lakh)

33

Looking at the state wise numbers of works completed or on-going under MGNREGA

(Figure 2.10), Andhra Pradesh topped the list with a sum of 135 lakhs works undertaken

during the entire period of MGNREGA. Uttar Pradesh was second with 48 lakh works

followed by Madhya Pradesh with 44 lakh works. Karnataka, Rajasthan, West Bengal,

Bihar, Jharkhand and Odisha lied in the middle with numbers of projects ranging between

20 to 10 lakh. The state that lied in the lower stratum included Meghalaya, Nagaland,

Punjab, Haryana and Manipur having numbers of projects between 50 and 100 thousand

while Mizoram, Sikkim, Arunachal Pradesh and Goa had less than 50 thousand projects.

Figure 2.9: Amount spent for different activities under MGNREGA

during 2006-07 to 2013-14 (Rs thousand crore)

34

Figure 2.10: State wise number of works completed/under progress

under MGNREGA during 2006-07 to 2013-14 (lakh)

Glancing through the total budget spent on the completed and on-going projects by

different states it is indicated by the statistics presented in Table 2.4 that Uttar Pradesh

topped in the total amount spent on MGNREGA works with a total budget of 26

thousand crore. Uttar Pradesh was closely followed by Madhya Pradesh, Rajasthan and

Andhra Pradesh with almost similar amount spent at the aggregate on all projects in the

duration of MGNREGA period up to October 2013. Maharashtra, Chhattisgarh, West

Bengal, Tamil Nadu and Bihar spent slightly less amount each varying between 13 to

18 thousand crore. Nagaland, Manipur, Uttrakhand, Jammu & Kashmir, Meghalaya,

Haryana and Mizoram spent only around or less than 2 thousand crore each, while

Punjab, Sikkim, Arunachal Pradesh and Goa lied at the bottom with less than 1 thousand

crore spent by each state on MGNREGA during the period 2006-07 up to October 2013

(Figure 2.11).

35

Figure 2.11: State wise expenditure incurred on MGNREGA

during 2006-07 to 2013-14 (Rs thousand crore)

The expenditure incurred on the completed and on-going projects was not exactly similar

to that of allocation of projects in different states indicating cost differences across the

projects as well as per project cost across states. It was mentioned above that at the

aggregate per project cost of MGNREGA works for its full duration up to October 2013

was around 59 thousand per project. At the aggregate, the highest amount per project

was spent on renovation of traditional water bodies 121 thousand per project that was

closely followed by 112 thousand per project on rural connectivity. Expenditure on

flood control lied on the third place with an expenditure of 79 thousand per project.

Micro irrigation had a spending of 53 thousand per project followed by drought

proofing 49 thousand per project, water conservation 47 thousand per project, land

development 40 thousand per project and provision of irrigation 29 thousand per

project (Figure 2.12). Thus, whereas water conservation topped in the total numbers of

projects undertaken but spending on per project was much less on water conservation

compared to rural connectivity that topped among all projects not only in the total amount

spent but also amount spent per project. State wise total expenditure per project

(aggregate of all categories) is depicted in Figure 2.13 below. Highest amount per project

was spent in Manipur, 297 thousand followed by Nagaland ( 245 thousand), Mizoram

36

( 269 thousand), Tamil Nadu ( 255 thousand), Assam ( 191 thousand) and

Maharashtra ( 160 thousand). The states that lied at the bottom in spending per project

were Andhra Pradesh ( 18 thousand), Gujarat ( 41 thousand), Karnataka and Goa (

48 thousand), Kerala ( 49 thousand), and Uttar Pradesh ( 54 thousand) only.

Figure 2.12: Amount spent under MGNREGA (Rs thousand per project)

during 2006-07 to 2013-14

Figure 2.13: State wise amount spent under MGNREGA during

2006-07 to 2013-14 (Rs thousand per project)

37

2.4 Performance of MGNREGA – Some qualitative indicators

Table 2.5 provides details of social auditing and inspection carried out for MGNREGA

work in different states in India. The Gram Panchayats open muster rolls to carry out

registration of workers demanding employment under MGNREGA. These muster rolls

are verified under social auditing. During 2008-09 to 2013-14 (up to October), a total

number of 10.52 crore muster rolls were opened at the aggregate (all states) out of which

around 85 per cent were verified by the authorities who carried out the auditing work.

The verification process was more than 70 per cent in all the states except West Bengal

where verification of muster roles was only 59 per cent. Social auditing of MGNREGA

work of the Gram Panchayats (GP) was held in around 87 per cent of the GPs during

2008-09 to 2013-14. The social audit was held in above 90 per cent GPs in Tamil Nadu,

Madhya Pradesh, Kerala and Nagaland whereas, it was held in less than 60 per cent GPs

in Arunachal Pradesh, around 60 to 65 per cent GPs in Jammu & Kashmir and Karnataka.

As far as inspection of the works taken up by GPs under MGNREGA, there was district

level inspection as well as at the block level inspection. The percentage of works

inspected at the district level were very low only 12 per cent whereas the works inspected

at the block level were as high as 81 per cent during the above mentioned period. Almost

half of the works were inspected at the district level in Arunachal Pradesh while

proportion of inspected works was half to 1/3rd

in Assam, Sikkim, Nagaland and Kerala.

In rest of the states, less than 1/3rd works were being inspected at the district level. On

the other hand, West Bengal, Uttar Pradesh and Maharashtra had less than half of the

works inspected at the block level. In Rajasthan, Chhattisgarh and Tamil Nadu almost all

the works taken were being inspected at the block level while rest of the states more than

half to 3/4th

works taken up was being inspected at the block level.

Complaint redressal system was adopted under MGNREGA and a total number of

215542 complaints were registered in all the states during the period of 2008-09 to 2013-

14 (up to October) out of which around 84 per cent were redressed. Complaint redressal

was 100 per cent in Goa, Arunachal Pradesh and Mizoram. It was less than 80 per cent in

38

Madhya Pradesh, Maharashtra, Odisha, West Bengal and Gujarat while in rest of the

states above 80 per cent complaints were redressed during the above mentioned period.

MGNREGA programme not only provides employment to the households but it also

brings awareness among the households. The efforts are made to bring more transparency

in the payment system. The Gram Panchayats are encouraged to make payments to the

workers through banks or post office. The numbers of active bank accounts in the year

2008-09 to 2012-13 exceeded 20 crore on individual accounts and 3 crore on joint

accounts. Similarly the active post office accounts during the same years exceeded 15

crore on individual accounts and around 1.8 crore on joint accounts. Thus a total number

of 41 crore individual and joint accounts in post offices and banks were operative through

which payments were made for MGNREGA works during the period 2008-09 to 2012-

13 (Table 2.6).

Looking at state wise performance, the highest number of bank and post office accounts

were operative in Andhra Pradesh (6.4 crore), Rajasthan (4.4 crore), Uttar Pradesh (3.7

crore), Tamil Nadu (3.6 crore) and Madhya Pradesh (3.5 crore) during the period from

2008-09 up to October 2013. The north-eastern states namely Manipur, Meghalaya,

Mizoram, Nagaland, Sikkim and Arunachal Pradesh were at the bottom having less than

10 lakh accounts in operation for MGNREGA. The more important issue is how much

amount was being paid through these operative accounts under MGNREGA. Table 2.6

also presents the amount disbursed through bank/post office for making MGNREGA

payments to the households employed. A total sum of 51 thousand crore were disbursed

through banks and 30 thousand crore through the post offices, and thus a sum of 81

thousand crore were disbursed through banks and post offices during the period of 2008-

09 to 2012-13. State wise highest amount was disbursed by Uttar Pradesh ( 12.5

thousand crore) followed by Andhra Pradesh (around 12 thousand crore), Rajasthan (

11 thousand crore), Madhya Pradesh (9 thousand crore) and Karnataka (around 5

thousand crore). The north-eastern state namely, Arunachal Pradesh was at the bottom in

disbursal of total amount through banks and post offices (Figure 2.14) during the period

2008-09 to 2012-13.

39

Figure 2.14: Amount disbursed by banks and post office

under MGNREGA during 2008-09 to 2012-13

Figure 2.15: Amount spent under MGNREGA through banks and

post offices during 2008-09 to 2012-13 (Rs lakh per project)

It is interesting to note that out of total amount paid through banks and post offices in

MGNREGA during the period 2010-11 to 2012-13, the average amount paid through

40

bank/post office per account was 1.97 lakh. State wise, the highest amount paid per

account was in Nagaland ( 24 lakh), Meghalaya ( 9.5 lakh), Mizoram ( 6 lakh),

Sikkim ( 5.8 lakh) and Tripura ( 3.8 lakh). The lowest amount was paid in Tamil Nadu

(only 3 thousand), Bihar ( 1 lakh) and Gujarat ( 1.2 lakh) as shown in Figure 2.15.

Table 2.7 shows the unemployment allowance paid to the households in lieu of not being

able to provide employment to them after having registered a household’s name for

MGNREGA work. According to the legislation on MGNREGA, if a member of a

household has not been provided employment after issuing him/her a job card after a

lapse of 15 days, the GPs are supposed to provide unemployment allowance and such

amount would be borne by the concerned state government. Following this rule, during

the period 2007-08 to 2013-14 (up to October) unemployment allowance was due for

4.83 crore person days for which employment was not provided to the job card holders.

However, there was hardly any unemployment allowance paid to the job card holders as

only in West Bengal, Nagaland, Karnataka, Tamil Nadu, Uttar Pradesh and few others

unemployment allowance was paid for few days. Even in the states where some

unemployment allowance was paid, the amount paid per day was much less than the

stipulated minimum wages set by the states, except the case of Tamil Nadu. However, it

is interesting to note that the allowance paid even in those state was only a small fraction

of the total number of days for which unemployment allowance was due. At the

aggregate, out of 4.83 crore days for which unemployment allowance was due only 2478

days of allowance was paid that makes only 0.01 per cent days of unemployment

allowance paid and it was not more than 0.04 per cent in any state.

2.5 Summary of the Chapter

In the three phases of MGNREGA implementation in India from 2006-07 to 2013-14 (up

to October) 81 crore households were issued job cards at the country as a whole out of

which around 34 crore households were provided employment averaging around 4.5

crore households working in MGNREGA per annum that constitutes roughly around 30

per cent of the rural households in the country as a whole. A total number of 1.5 thousand

crore mandays of employment was generated during the above mentioned time period.

41

Out of the total person days generated, the share of Scheduled Castes and Scheduled

Tribes was 26.9 and 22.0 per cent, respectively while share of women in the total

employment was 48.0 per cent. The Andhra Pradesh state topped in the generation of

total person days, followed by Rajasthan, Uttar Pradesh Madhya Pradesh, Tamil Nadu

and West Bengal. At the aggregate, a total number of 45 person days of employment was

provided under MGNREGA during the implementation of this programme whereas the

target set under the programme is 100 days of employment per household. The highest

numbers of days of employment was provided by the north-eastern states followed by

Rajasthan, Madhya Pradesh and Andhra Pradesh. How successful the MGNREGA

programme in India has been in providing hundred days of employment to those who

demanded work. Out of 34 crore households working in MGNREGA only 2.9 crore

households (only 8.4 per cent) completed hundred days during its full tenure. It is

interesting to note whereas bigger states topped in the completion of hundred days of

employment like Rajasthan, Andhra Pradesh and Tamil Nadu, the percentage of

households who completed hundred days, it was the north-eastern states which topped in

the percentage term.

Water conservation was the leading activity which occupied the highest numbers of

projects followed by rural connectivity, provision of irrigation, drought proofing, land

development, renovation of traditional water bodies, micro irrigation and flood control.

During the entire period of MGNREGA, out of total 2.9 crore projects taken up under

MGNREGA around 30 per cent were completed and rest of 70 per cent were in progress.

A total amount of 2,35,084 crore was spent on the MGNREGA during 7 and a half

years of functioning of the MGNREGA with an average of slightly less than 30

thousand crore every year while average expenditure per project was 59 thousand. At

the aggregate, the highest amount per project was spent on renovation of traditional water

bodies closely followed by rural connectivity, flood control, micro irrigation, drought

proofing, water conservation, and land development in the descending order.

During 2008-09 to 2013-14 (up to October), a total number of 10.52 crore muster rolls

were opened at the aggregate out of which around 85 per cent were verified. Social

42

auditing of MGNREGA work of the Gram Panchayats (GP) was held in around 87 per

cent of the GPs while the percentage of works inspected at the district level were only 12

per cent. Complaint redressal system was adopted under MGNREGA and a total number

of 215542 complaints were registered in all the states out of which around 84 per cent

were redressed. It is interesting to note that out of total amount paid through banks and

post offices under the MGNREGA during the period 2008-09 to 2012-13, the average

amount paid through bank/post office per account was 1.97 lakh. According to the

legislation on MGNREGA, if a member of a household has not been provided

employment after issuing him/her a job card after a lapse of 15 days, the GPs are

supposed to provide unemployment allowance. Following this rule, during the period

2007-08 to 2013-14 (up to October) unemployment allowance was due for 4.83 crore

person days whereas only 2478 days of allowance was paid that makes only 0.01 per cent

days of unemployment allowance paid and it was not more than 0.04 per cent in any

state.

Table 2.1: MGNREGA Statistics for the Financial Year 2013-14

(As on 6 December 2013)

Description Latest Estimates

Employment provided to Households (crore) 2.31

Total person days generated (crore) 62.57

Person days generated for SCs (crore) 14.45

(23.1)

Person days generated for STs (crore) 9.59

(15.33)

Person days generated for Women (crore) 34.91

(55.78)

Person days generated for Others (crore) 38.53

(61.57)

Total works taken up (lakh) 44.18

Work Completed (lakh) 4.22

(9.56)

Works in progress (lakhs) 39.96

(90.44)

Note: Figures in parentheses are respective percentages of total

Source: http://nrega.nic.in

43

Table 2.2: Employment Generated through MGNREGA and its Socio-Economic characteristics (2006-07 to 2013-14)

Name of

the States

Cumulati

ve No. of

HH issued

job cards

(in

crores)

No.of HH

who have

demanded

employ-

ment

(in crores)

No.of HH

provided

employ-

ment

(in crores)

Per

centage of

HH

provided

employ-

ment

No. of

days of

Employ-

ment

provided

(per HH)

Person days in crores Works

Ongoing

(in crores)

Works

Complete

d

(in crores)

Total

Works

(in crores)

Works

Completed

(%)

No. of HH

Availed

100 days

of Employ-

ment

Per centage

of HH

completed

100 days of

Employment

Total SCs

(%)

STs

(%)

Women

(%)

Others

(%)

Andhra Pradesh 8.57 4.08 4.08 100.00 50.82 207.37 25.31 14.91 57.82 59.78 0.24 1.38 1.62 85.23 4905592 12.02

Arunachal Pradesh 0.09 0.07 0.05 74.40 28.32 1.38 0.45 87.40 27.94 12.15 0.00 0.00 0.00 77.08 17985 3.70

Assam 2.54 1.19 1.14 96.34 33.47 38.26 9.22 32.44 27.93 58.34 0.01 0.02 0.03 69.88 380266 3.33

Bihar 8.51 2.39 2.32 97.40 30.92 71.85 40.95 2.29 28.42 56.77 0.04 0.12 0.16 74.91 1003496 4.32

Chhattisgarh 2.85 1.80 1.76 97.53 47.89 84.09 12.96 39.29 45.98 47.75 0.05 0.06 0.11 53.47 1093631 6.23

Goa 0.01 0.00 0.00 99.53 24.79 0.10 3.93 23.97 70.40 72.20 0.00 0.00 0.00 70.11 678 1.74

Gujarat 2.34 0.61 0.59 97.36 37.00 21.86 11.77 42.67 45.40 45.55 0.05 0.03 0.08 40.95 321998 5.45

Haryana 0.39 0.15 0.15 95.70 39.22 5.73 51.47 0.00 36.49 48.52 0.00 0.00 0.01 47.84 63756 4.36

Himachal Pradesh 0.68 0.33 0.31 95.10 47.95 14.90 31.35 8.11 49.98 60.54 0.02 0.03 0.05 54.75 202038 6.50

Jammu And

Kashmir

0.53 0.27 0.25 92.28 43.17 10.78 6.84 20.02 13.63 73.14 0.01 0.03 0.04 67.47 147968 5.92

Jharkhand 2.82 1.23 1.22 99.20 42.19 51.33 16.46 40.81 32.10 42.74 0.04 0.10 0.14 69.15 523126 4.30

Karnataka 3.26 1.20 1.13 93.85 47.22 53.22 18.26 9.93 43.17 71.81 0.05 0.19 0.24 79.54 772301 6.85

Kerala 1.52 0.78 0.73 93.19 39.79 28.97 15.93 3.72 90.98 80.36 0.06 0.03 0.09 33.95 592212 8.13

Madhya Pradesh 8.03 3.04 3.01 98.97 52.46 157.85 18.35 42.73 43.11 38.93 0.15 0.31 0.46 68.03 2515984 8.36

Maharashtra 4.30 0.67 0.66 98.06 46.65 30.80 12.53 25.27 43.99 62.21 0.02 0.10 0.12 86.42 511089 7.74

Manipur 0.28 0.25 0.25 98.47 59.45 14.73 6.96 65.14 39.59 27.90 0.00 0.00 0.01 51.84 358487 14.47

Meghalaya 0.27 0.21 0.20 95.90 46.02 9.13 0.53 93.29 46.58 6.18 0.00 0.01 0.01 68.22 125782 6.34

Mizoram 0.13 0.12 0.12 99.11 71.71 8.43 0.03 99.79 31.03 0.18 0.00 0.00 0.00 64.42 299150 25.44

Nagaland 0.23 0.22 0.22 99.87 63.68 14.04 0.34 97.51 33.27 2.14 0.00 0.00 0.01 61.26 369167 16.75

Odisha 4.26 1.18 1.13 95.67 39.96 45.13 19.77 39.20 36.91 41.03 0.03 0.10 0.14 76.52 483165 4.28

Punjab 0.49 0.15 0.15 95.95 27.37 4.06 77.65 0.02 36.46 22.33 0.00 0.01 0.01 63.27 25521 1.72

Rajasthan 6.05 3.48 3.37 96.69 60.57 204.10 23.70 27.49 67.81 48.81 0.05 0.14 0.18 73.64 5464900 16.22

Sikkim 0.05 0.04 0.03 95.75 62.76 2.11 7.46 40.73 45.04 51.81 0.00 0.00 0.00 65.33 59476 17.69

Tamil Nadu 4.94 3.38 3.37 99.65 49.37 166.27 42.26 1.71 78.98 56.03 0.02 0.04 0.06 62.17 4532597 13.46

Tripura 0.42 0.39 0.39 99.51 67.60 26.47 18.65 43.44 42.96 37.91 0.04 0.02 0.06 38.77 792636 20.24

Uttar Pradesh 9.11 4.07 3.92 96.47 42.21 165.62 47.84 1.68 19.43 50.48 0.22 0.30 0.53 57.29 2443749 6.23

Uttrakhand 0.64 0.28 0.28 99.24 38.79 10.72 23.21 3.62 41.69 73.17 0.01 0.02 0.03 60.48 93252 3.37

West Bengal 7.83 3.38 3.27 96.58 28.36 92.64 35.34 12.56 30.33 52.09 0.09 0.10 0.19 51.63 543778 1.66

Grand Total 81.15 34.96 34.09 97.51 45.24 1541.94 26.87 21.95 48.04 51.18 1.23 3.15 4.37 71.98 28643780 8.40

44

Table 2.3: State wise Works Completed/Progress under MGNREGA: 2006-07 to 2013-14 (Number of projects)

Name of

the States

Rural Connectivity Flood Control and

Protection

Water

Conservation and

Water Harvesting

Drought Proofing Micro Irrigation

Works

Provision of

Irrigation facility to

Land Owned by

Renovation of

Traditional Water

bodies

Land Development Other activity

Approved by

MRD

Total

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Comp-

leted

On-

going

Andhra

Pradesh

96072 332649 21065 123352 740931 4166080 143666 2133419 376592 798429 178432 1445415 169653 240612 480878 441458 5292 15967

04

2212581 11278118

Arunachal

Pradesh

1358 4135 478 1313 181 532 300 1007 410 1589 3 47 44 100 139 1290 214 386 3127 10399

Assam 40333 101689 7232 12810 4606 12129 12819 34698 3245 7242 8934 11325 2205 4363 8256 23621 6631 9764 94261 217641

Bihar 171453 368650 22021 30746 52580 88956 49496 483797 33588 68356 6196 17549 31225 49156 20130 60066 15082 28623 401771 1195899

Chhattisgarh 91054 163096 3134 5461 42829 67189 25962 36512 9358 18293 149507 99959 42582 50645 146154 130673 3780 10009 514360 581837

Goa 384 602 308 816 26 77 0 0 13 47 0 22 112 286 362 975 2 6 1207 2831

Gujarat 34055 50061 21610 33457 274251 55316 33699 44872 2152 4120 34166 73672 15508 15201 17328 14409 24774 19514 457543 310622

Haryana 17607 16049 1480 1368 6929 6657 2052 706 8300 4634 221 557 2925 3114 7080 5645 1072 3447 47666 42177

Himachal

Pradesh

62887 76446 24101 28775 36386 45728 4433 5527 17514 21865 18436 25661 10616 9188 30266 34032 4210 4694 208849 251916

Jammu and

Kashmir

48709 113499 36935 67761 12582 21969 1397 2426 15401 32092 1824 1475 5082 8660 16765 34168 2403 9454 141098 291504

Jharkhand 87228 170077 1380 2503 182157 400014 6350 22832 4289 10354 82383 245775 22708 38241 44653 67748 10031 29178 441179 986722

Karnataka 53274 195123 43371 143692 81071 282463 60952 233728 24480 107565 71740 217398 23588 109093 84405 278475 20258 90995 463139 1658532

Kerala 15139 8803 144198 65111 85059 51230 16704 8042 51489 26332 29605 17765 76302 36574 168587 86313 2923 2187 590006 302357

Madhya

Pradesh

159245 485482 6886 13849 286594 610645 141083 444608 16291 27902 498100 892407 32280 66484 287962 396537 12998 43320 1441439 2981234

Maharashtra 8071 97378 794 3035 73094 281498 26814 290489 1053 7399 17747 205425 10130 43678 8834 27899 3223 23162 149760 979963

Manipur 11157 15694 8632 4532 3770 4139 5524 5008 2418 3961 121 139 1099 618 3847 4723 1191 1920 37759 40734

Meghalaya 15284 34309 1236 2333 5653 11489 3115 6545 1132 2098 60 115 2119 3164 2261 5019 547 2181 31407 67253

Mizoram 9680 19943 451 1431 669 978 1247 1146 45 132 17 30 46 58 2288 3349 1334 1497 15777 28564

Nagaland 10230 31182 2116 1492 5195 4250 2422 1933 2326 3235 121 64 658 216 6014 2584 777 2229 29859 47185

Odisha 100955 300250 1703 5474 59131 203444 18819 73121 2362 13072 47063 135351 44764 166316 23558 50193 18362 81140 316717 1028361

Punjab 12141 15197 1022 1451 737 972 3592 7425 2483 2725 5 16 6378 17049 3761 7936 2274 2947 32393 55718

Rajasthan 96038 329594 4403 15908 77562 209918 15922 65295 18707 51608 172731 376559 44095 122296 25862 77916 17756 63047 473076 1312141

Sikkim 1265 3263 683 1481 714 906 1875 1307 404 844 5 16 69 105 1630 4579 265 513 6910 13014

Tamil Nadu 49546 76873 1270 1429 34490 54179 20 698 28543 45246 2347 6579 94071 164219 858 6403 166 398 211311 356024

Tripura 77346 51055 6145 2901 55988 41135 21244 22493 34691 19940 6814 1340 18781 19106 93243 53383 60708 26940 374960 238293

Uttar

Pradesh

768128 1078544 95639 130862 187423 300482 106272 148556 93070 132081 346603 293826 115361 123932 236892 254645 139757 22851

2

2089145 2691440

Uttrakhand 10449 17765 30578 49775 33419 38916 10406 15631 11216 16009 1808 2025 5206 9346 9270 20014 1053 3314 113405 172795

West

Bengal

249932 264990 50444 44475 168582 169640 161177 213229 43854 41273 44048 57322 104647 94581 85787 80329 5850 9190 914321 975029

Grand Total 2299020 4422398 539315 797593 2512609 7130931 877362 4305050 805426 1468443 1719037 4127834 882254 1396401 1817070 2174382 362933 22952

71

11815026 28118303

45

Table 2.4: State wise Works Completed/Progress under MGNREGA: 2006-07 to 2013-14 (Amount spent in Rs lakh)

Name of

the States

Rural Connectivity Flood Control

and Protection

Water

Conservation and

Water Harvesting

Drought Proofing Micro Irrigation

Works

Provision of

Irrigation facility

to Land Owned

by

Renovation of

Traditional Water

bodies

Land

Development

Any Other

activity

Approved by

MRD

Total

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Comp-

leted

On

going

Andhra

Pradesh

132725 266257 17308 18954 282201 328702 58889 79896 122307 80349 120024 214876 240826 167178 149580 97842 3896 38956 1127756 1293011

Arunachal

Pradesh

1383 3237 741 1048 153 275 219 424 282 892 3 0 62 54 79 716 46 78 2969 6724

Assam 108688 188426 38185 55059 10766 63607 7783 16989 8278 13955 1603 2048 6026 9393 16037 33950 6407 9531 203773 392958

Bihar 414436 265008 29648 28787 70108 67018 24017 146007 35634 40763 7007 8901 32091 35311 21683 29415 11923 20743 646546 641953

Chhattisgarh 189845 266619 7144 11864 80890 95590 31874 443472 25463 49101 38601 27644 88391 92205 48461 41113 1379 8085 512048 1035693

Goa 384 178 290 230 24 17 0 0 18 7 0 5 73 69 413 259 2 0 1203 765

Gujarat 44619 38911 17889 20588 45145 27900 10049 14140 1869 1712 11617 21810 15241 7399 4383 4396 4480 19471 155292 156326

Haryana 28805 23321 2057 2014 13752 11771 2169 769 9819 4868 247 279 4756 5118 10580 8523 2897 7980 75082 64644

Himachal

Pradesh

43124 53692 19489 19885 22703 19937 2933 2551 14389 14935 9951 6714 5651 4797 16804 12986 2194 2098 137238 137596

Jammu &

Kashmir

39209 40364 28128 21422 7055 5477 914 875 10383 10858 1166 453 2657 2331 14603 11981 2322 6100 106438 99862

Jharkhand 92222 135953 2036 2832 122054 180601 4063 18906 5187 7947 58311 91997 15621 20100 15845 21476 3566 18536 318906 498349

Karnataka 72874 111914 70909 96820 79803 110186 31858 63520 27821 52467 21115 28382 26350 45423 50561 73015 15859 41760 397151 623488

Kerala 7193 2764 55282 17589 53313 19692 8909 2461 23383 7705 21615 8298 35249 12172 123831 36485 1643 757 330418 107924

Madhya

Pradesh

329666 526028 14158 11208 232843 363973 44279 115125 15435 26266 251448 281179 34364 44473 65988 99762 2918 5302 991099 1473316

Maharashtra 23480 135098 1471 5013 105266 372686 561301 403847 356 1979 15463 65294 48930 47750 6711 8404 1315 8234 764294 1048306

Manipur 52343 51823 14394 7630 10172 8995 9178 8011 12551 16832 146 450 3909 1000 15029 11385 5298 4079 123020 110205

Meghalaya 35180 39596 3372 3721 6649 7094 4198 4048 1996 1701 62 88 1750 1748 4595 5419 2149 5292 59952 68707

Mizoram 43902 50391 832 504 2040 1428 3223 785 152 129 328 433 71 71 5603 3087 4370 1817 60519 58646

Nagaland 83294 78581 7887 2669 6703 3401 5347 3542 9094 3642 447 12 755 204 8457 3884 5237 5263 127221 101200

Odisha 90800 229009 1571 4121 27037 117620 4340 29316 2797 9215 7342 13821 22210 72317 3636 7425 21411 66590 181143 549434

Punjab 11910 14523 1709 2434 713 882 1489 2176 1563 2155 4 2 8070 18119 4193 6224 2067 4876 31718 51392

Rajasthan 220979 693470 9844 33745 154238 391973 18943 90645 30671 83176 73072 127180 89451 256152 25410 64214 30560 61335 653169 1801890

Sikkim 1938 4903 1219 2592 213 1096 598 938 658 1073 7 10 23 105 1338 2443 69 178 6062 13339

Tamil Nadu 126183 152188 3794 4171 105413 130905 49 219 82856 98477 1503 2729 301011 432977 933 3639 585 366 622328 825671

Tripura 105375 40610 8903 1777 44592 10334 21975 10685 23755 8739 4496 518 10315 2200 62512 13467 29255 20769 311177 109099

Uttar Pradesh 636707 587497 71143 67109 187913 180279 52125 53527 43800 52641 61344 45349 164895 98327 100240 82516 44239 55867 1362405 1223110

Uttrakhand 6524 7532 27466 29465 20189 15053 7482 6635 10329 9955 733 581 3347 2563 9547 10685 588 1813 86204 84282

West Bengal 333576 242484 69105 58808 183097 102444 42802 37740 54901 32219 30332 14402 138552 73727 69451 42493 3438 5833 925255 610149

Grand Total 3277363 4250378 525972 532059 1875045 2638938 961004 1557250 575747 633759 737989 963455 1300648 1453281 856503 737205 210115 421713 10320386 13188037

46

Table 2.5: Social Auditing and Inspection of MGNREGA work (2008-09 to 2013-14) Name of the State Must Roll Verified Social Audit Inspections Conducted Gram Sabha Held Complaints

No. of

Muster Rolls

Used

% age of

muster

rolls

Verified

Total Gram

Panchayats

%age of GP

where

social Audit

held

Total Works

Taken up

%age of

Works

Inspected at

District

Level

%age of

Works

Inspected at

Block Level

Total Gram

Panchayats

No. of

Gram

Sabhas

held

No. of

VMC

meetings

held

No. of

Complaints

Received

%age of

Complaints

Disposed

Andhra Pradesh 15256472 91.33 22025 84.92 2961546 9.14 91.27 22025 21232 7112 9486 96.38

Arunachal Pradesh 19312 99.41 313 58.93 2437 45.38 90.07 313 189 124 5 100.00

Assam 2215732 82.28 1886 88.13 111733 35.71 101.51 1904 5742 3121 1687 90.16

Bihar 6848974 84.91 5307 91.83 548555 9.00 60.85 5137 16948 16902 13720 61.81

Chhattisgarh 7364510 82.78 8089 92.44 684369 19.20 87.53 9544 12046 5110 11625 85.28

Goa 7370 94.67 142 73.54 1806 8.75 89.04 172 411 22 4 100.00

Gujarat 2264472 97.37 13777 93.28 612509 9.86 95.13 14744 20008 17301 4708 79.25

Haryana 446733 98.66 5979 60.27 80898 9.21 73.07 5535 6683 3299 661 88.05

Himachal Pradesh 950859 86.54 4430 80.45 301485 13.38 85.44 2903 7576 13166 2633 85.83

Jammu and Kashmir 607317 85.80 2548 65.55 170958 17.08 76.87 2563 3087 2834 1893 96.20

Jharkhand 6210689 92.21 4445 122.64 899744 16.14 71.40 5073 23270 19340 6447 90.65

Karnataka 1429346 88.71 4041 60.02 822657 11.89 76.04 4094 4398 1897 3264 87.38

Kerala 2470199 88.82 2242 77.26 331141 31.07 90.47 2583 16105 19947 1536 91.02

Madhya Pradesh 8694851 87.32 21544 91.39 2834452 13.11 93.46 20784 52174 34859 28621 73.58

Maharashtra 925445 88.05 18179 79.97 194925 11.17 52.03 18752 23614 9713 468 73.93

Manipur 808504 88.05 2029 94.68 27634 27.46 74.17 2402 3590 3006 1184 89.95

Meghalaya 763359 86.82 1602 71.28 43016 14.33 83.83 1681 3392 3160 1050 86.00

Mizoram 230216 103.95 585 71.26 12817 30.77 99.42 570 600 990 138 98.55

Nagaland 100110 93.63 1109 99.44 37598 33.88 82.44 1160 1776 1661 48 68.75

Odisha 5445318 86.54 7373 95.68 1050512 15.03 74.17 6178 8104 13201 8646 79.26

Punjab 295491 91.33 9439 95.71 54264 20.11 83.85 9591 11209 5024 630 81.43

Rajasthan 14962913 97.64 7337 90.11 841546 19.90 148.12 7083 7435 9531 45460 85.44

Sikkim 38747 97.90 161 69.16 9046 33.00 96.29 164 431 34 5 80.00

Tamil Nadu 2287101 100.01 13293 107.47 267117 14.36 99.70 14272 29826 2513 2332 97.73

Tripura 2008475 88.54 1039 89.15 254039 11.56 49.87 1039 1019 3538 190 86.32

Uttar Pradesh 13824894 71.40 45966 82.56 2325857 10.46 53.90 38098 36637 33994 61460 90.21

Uttrakhand 1250775 73.07 5869 88.17 157424 11.42 64.96 5869 5767 6418 1540 87.34

West Bengal 7454365 59.25 6322 71.73 803781 3.59 37.17 3276 4908 2852 6101 78.45

Total 105182549 85.46 204191 87.06 16443866 12.75 81.06 194419 312577 231023 215542 84.13

47

Table 2.6: The MGNREGA payment processed through Banks / Post office (2008-09 to 2012-13)

State No. of Active Bank Account

During the Financial Year

2008-2012

Amount of wages

Disbursed

through bank

Accounts

(in lakhs.)

No. of Active Post Office

Account for Financial

Year

2008-2012

Amount of

Wages disbursed

through post office

Accounts (in

lakhs.)

Total Accounts Use During the

Financial Year 2008-2012

Total

Amount

Disbursed

(in lakhs.)

Individual Joint Individual Joint Individual Joint Total

Andhra Pradesh 22125456 0 394046.94 42043964 0 808835.74 64169420 0 64169420 1202882.7

Arunachal Pradesh

21494 24469 677.54 11695 8630 299.45 33189 33099 66288 977

Assam 5703034 197343 95646.95 5010532 119764 62480.54 10713566 317107 11030673 158127

Bihar 6479061 333180 45795.39 23157465 660261 280992.25 29636526 993441 30629967 326788

Chhattisgarh 11407540 73186 187901.99 16491178 211570 201899.95 27898718 284756 28183474 389802

Goa 34475 77 1165.9 0 0 0 34475 77 34552 1166

Gujarat 1932740 2610942 59221.44 4940075 4575279 114429.75 6872815 7186221 14059036 173651

Haryana 857602 732424 61864.24 62872 58554 3581.33 920474 790978 1711452 65446

Himachal Pradesh 3439016 194048 122274.09 285601 15419 9980.15 3724617 209467 3934084 132254

Jammu & Kashmir

1584941 59762 61997.69 11646 3466 533.01 1596587 63228 1659815 62531

Jharkhand 4098462 626363 81722.79 9735868 1321331 243991.71 13834330 1947694 15782024 325715

Karnataka 11897536 3528235 442482.38 2031841 3030668 73287.31 13929377 6558903 20488280 515770

Kerala 5218247 1894 176256.46 290630 382 7471.65 5508877 2276 5511153 183728

Madhya Pradesh 22075781 8598461 747073.59 3368858 1416761 125028.63 25444639 10015222 35459861 872102

Maharashtra 3083926 217317 64163.93 4246868 139114 106456.36 7330794 356431 7687225 170620

Manipur 359537 5909 37000.36 574904 0 19801.65 934441 5909 940350 56802

Meghalaya 151475 37389 32651.95 188854 18465 5044.47 340329 55854 396183 37696

Mizoram 82809 62108 14139.42 138069 159825 18904.43 220878 221933 442811 33044

Nagaland 0 4591 110752.64 0 0 0 0 4591 4591 110753

Odisha 7748786 706114 124108.73 4112687 1291956 93912.53 11861473 1998070 13859543 218021

Punjab 1408591 283549 25740.76 418789 47440 7120.67 1827380 330989 2158369 32861

Rajasthan 16310043 3749423 622331.03 22460108 1292003 493892.13 38770151 5041426 43811577 1116223

Sikkim 156091 18419 11459.04 100201 11881 5284.05 256292 30300 286592 16743

Tamil Nadu 35021217 523462 11566.79 8875 2408 0 35030092 525870 35555962 11567

Tripura 271203 1212990 59151.96 202405 372610 20073.81 473608 1585600 2059208 79226

Uttar Pradesh 33039242 2780426 1221270.1 761804 48979 28893.86 33801046 2829405 36630451 1250164

Uttrakhand 3060330 325669 63417.57 654146 57462 18522.96 3714476 383131 4097607 81941

West Bengal 11527289 3879158 247013.49 14573671 3148637 258281.34 26100960 7027795 33128755 505295

Total 209095924 30786908 5122895.1 155883606 18012865 3008999.7 364979530 48799773 413779303 8131895

48

Table 2.7: Unemployment Allowances paid in lieu of not providing Employment (2007-08 to 2013-14) Sl.

No.

State Un Employment

Allowance Due

Unemployment Allowance Paid Amount

paid Rs

per day

% days for which

unemployment

allowance paid No. of Days No. of Days Amount (in Rs.)

1 Andhra Pradesh 0 0 0 0 0.00

2 Arunachal Pradesh 1547352 0 0 0 0.00

3 Assam 37064 0 0 0 0.00

4 Bihar 1270148 0 0 0 0.00

5 Chhattisgarh 1111264 0 0 0 0.00

6 Goa 83088 19 1438.5 76 0.02

7 Gujarat 692117 19 1820 96 0.00

8 Haryana 18930 0 0 0 0.00

9 Himachal Pradesh 621270 12 1320 110 0.00

10 Jammu & Kashmir 4889440 33 1146 35 0.00

11 Jharkhand 129936 0 0 0 0.00

12 Karnataka 745276 322 10836 34 0.04

13 Kerala 775611 31 1038 33 0.00

14 Madhya Pradesh 627763 21 1214 58 0.00

15 Maharashtra 413621 0 0 0 0.00

16 Manipur 1238993 0 0 0 0.00

17 Meghalaya 276807 0 0 0 0.00

18 Mizoram 1342045 0 0 0 0.00

19 Nagaland 2080547 663 11620 18 0.03

20 Odisha 226004 0 0 0 0.00

21 Punjab 3358232 71 6238 88 0.00

22 Rajasthan 680960 15 1200 80 0.00

23 Sikkim 145014 0 0 0 0.00

24 Tamil Nadu 862564 282 99924 354 0.03

25 Tripura 74405 6 600 100 0.01

26 Uttar Pradesh 690635 218 24620 113 0.03

27 Uttrakhand 6012677 7 430 61 0.00

28 West Bengal 18409904 759 16574.5 22 0.00

Total 48361667 2478 180019 73 0.01

49

Table 2.8: Work Projection under MGNREGA for India during 2011-12 to 2012-13

Shelf of works Through Which

Employment to be Provided

Total No. of

Spill over

Works

From

Previous

year

Total No. of

New Works

Taken up in

Current

Year

No. of Works

Likely to

Spill Over

From

Current

Financial

Year to Next

financial year

No. Of

New

Works

Proposed

for next

financial

year

Benefit

Achieved

Unit

Person days

to be

Generated

Estimated Cost (In Lakhs)

On

Unskilled

Wage

On

Material

including

skilled and

semiskilled

wages

Total

Rural Connectivity 307670 856875 344466 2011738 189076226 2606487112 3831378 2592510 6423888

Flood Control and Protection 77129 299051 93551 703784 67227013 404559406 953502 663797 1617299

Water Conservation and Water Harvesting 228862 680252 293371 1484860 2709621374 8067494457 3682505 2234915 5917420

Drought Proofing 876795 536077 306661 891557 431600544 558756194 2400973 1496810 3897783

Micro Irrigation Works 86470 307757 85974 514621 106960627 10510900425 1715916 1080052 2795969

Provision of Irrigation facility to Land

Owned by

322483 884696 425794 2192011 637362744 959687614 1201329 742674 1944003

Renovation of Traditional Water bodies 141301 378155 158252 1111076 2735120114 1127740285 2098633 943888 3042521

Land Development 138096 527193 151479 1224103 11130205509 570944653 1237010 702146 1939157

Any Other activity Approved by MRD 40270 53790 21135 198988 8730369 70205053 597877 417019 1014895

Bharat Nirman Rajiv Gandhi Sewa Kendra 8235 13800 12465 39897 7235033 129024339 132737 212430 345167

Total 2227311 4537646 1893148 10372635 18023139552 25005799538 17851861 11086241 28938102

50

Chapter 3

Household Characteristics their Income and Consumption Pattern

3.1 Profile of respondents

The previous chapter presented a comprehensive analysis of functioning of the MGNREGA in

India among all states based on secondary data. In order to see the performance of MGNREGA

at the ground level and to capture qualitative information, a household survey was carried out

among a selected number of households. A sample of 250 households was selected from five

districts in each of the states covered in the study. While selecting five districts from each state, a

due representation was given to all the three phases of the implementation of MGNREGA. From

each district, two villages were selected with one village from the periphery of around 5

kilometers of the district/city head-quarters and the second district from a farthest location of 20

kilometers or more. From each selected village, primary survey was carried out on 20

participants in MGNREGA and 5 non-participants working as wage-employed. In summary,

from each state 10 villages were selected and a total number of 250 households were surveyed

with the help of a structured household questionnaire. Total sample consisted of 200 participants

and 50 non participants in each state. The detailed selection procedure for the participant and non

participant households is discussed in Chapter 1. This chapter presents a brief overview of the

selected households followed by a detailed discussion on the socio-economic characteristics,

occupation, income and consumption structures of the selected respondents in different states.

Our analysis in this chapter would be classified into participants of MGNREGA and non

participants in each state while the selected households from five districts in each state would be

clubbed together.

Tables 3.1 and 3.1.1 present demographic profile of the selected households (participants in

MGNREGA and non participants). The average household size was 4.75 with participants

having average family size of 4.7 and non participants 4.9. The number of earners in the family

was also higher for non participating households in comparison to participating households. The

average numbers of earners in the family were 2.2 members among participating families and 2.6

members among the non participating families. Similarly, the number of members in working

51

age (i.e., 16-60 years) was 74.4 per cent among participants and 73.7 per cent among non

participants. The percentage of below sixteen was less than 20 per cent among both participant

and non participant households and 6 and 7 per cent above the age of sixty years, respectively for

participants and non participants. Looking at the education status among the selected households,

the percentage of illiterate was around 1/3rd

among the participants and less than 1/3rd

among the

non participants. Those who were educated up to primary level their ratio was almost 1/3rd

among both participants and non participants and the proportion of member educated up to

secondary level was slightly above 1/4th

among both participants non participants. The

proportion of graduates and above was less than 3 per cent among the participants and less than 7

per cent among the non participants. Thus, non participants were better educated compared to

participant household members.

The demographic profile of households indicates their socio-economic characteristics. Looking

at the caste distribution among the participating households, the percentage of households

belonging to Scheduled Caste (SC), Scheduled Tribes (ST) and Other Backward Castes (OBC)

was 34, 17 and 34 per cent, respectively while General category had only 16 per cent proportion

among the selected households. In the case of non participating households, the proportion of

SC, ST, OBC and General among the selected sample was 33, 12, 35 and 20 per cent,

respectively. Looking at the proportion of number of job cards issued and number of person-days

generated as discussed in the last chapter, our socio economic structure of the selected sample

truly represents the distribution of job cards and numbers of people employed in NREGA.

Looking at the economic classification of the selected households, the people who had

Antyodaya (AAY) and Below Poverty Line (BPL) card among the participants constituted 16

and 53 per cent, respectively while Above Poverty Line (APL) card was held by 25 per cent

participating households. Among non participants, AAY card was held by 18 per cent, BPL by

39 per cent and APL by 34 per cent selected households. Six per cent households among

participants and nine per cent non participants were found not possessing any card. More than

2/3rd

proportion of the households who participated in MGNREGA had the main occupation as

wage earning. Only 23 per cent of them had main occupation as farming and another 3 per cent

as self business and 4 per cent as salaried work. Among the selected non participants, exactly

52

half were wage earners and one forth had farming as their main occupation. Other 10 per cent

each were in self business and in salaried job. The incidence of migration was not much different

among the participants and non participants.

3.2 Occupation structure

Distribution of sample family members in different occupations for participating and non

participating household is given in Tables 3.2 and 3.2.1. The age distribution in the previous

section indicated that around 2/3rd

members of the selected households were in the working age.

However, out of the working population, some members were full time students either in

college/university or doing other professional courses. A significant number of family members

belonged to housewives engaged in household activities without yielding any economic

remuneration. A few other members were unemployed or disabled persons not having any active

participation in any economic activities. Thus, the data presented in the table gives us

occupational distribution of the members who were truly active and were engaged in some

earning activities either in agriculture and related activities or in the secondary and tertiary

sectors.

The trends in occupation depict that among the participating households, the proportion of work

provided by MGNREGA was only a small proportion of their aggregate employment. Out of the

total man days employed per household including all the working members, the share of

MGNREGA varied between 12 to 32 per cent among different states. It was less than 15 per cent

in Karnataka, Kerala, Assam, Gujarat and West Bengal. Its proportion was between 15 to 25 per

cent in Uttar Pradesh, Sikkim, Madhya Pradesh, Chhattisgarh, Maharashtra, Himachal Pradesh,

Rajasthan, Haryana and Punjab. The share of MGNREGA in total employment was above 25 per

cent only in two states namely Bihar and Andhra Pradesh. At the aggregate, MGNREGA

provided 18 per cent share in the total employment among our selected households.

Glancing through the employment pattern it is evident from the statistics in the table that

participating households had their highest share in employment in casual labour in agriculture

and non agriculture sector among all the states. At the aggregate, casual labour in agriculture and

non agriculture sector constituted more than 40 per cent share in employment. Self employment

53

in agriculture and livestock constituted around 20 per cent share and self employment in business

and regular salary had around 5 and 10 per cent share, respectively in the total employment

among the selected participants. Among non participating households also majority (around 47

per cent) was engaged in casual wages in agriculture and non agriculture sector. Self

employment in agriculture and allied activities including animal husbandry contributed around

35 per cent share in the total man day’s employment. Almost 15 per cent share of man days was

contributed by regular salaried jobs. Self employment in non farming contributed around 12 per

cent. Thus, casual labour and self employment in agriculture and animal husbandry was the

prime activity that provided major employment to both participant and non participant

households. The MGNREGA programme provided only around 1/4th

to 1/5th

share of the total

employment to the participating households.

3.3 Household income

The main sources of earnings of the selected participant and non participant households were,

agriculture income also known as farm business income; Income from livestock activities

namely dairy and poultry farming; self-employment in non agricultural activities, such as small

business, shop or factory etc.; earnings through casual labour including that of NREGA; regular

salary or pension. Besides these major sources, there were also minor inflows of income in terms

of sale or renting out assets or land and remittances obtained from outside. These earnings were

mostly intermittent in nature and were sighted among very few households.

Tables 3.3 and 3.3.1 present distribution of household income by activity classifications for

participant and non participant households. All earnings from different activities are in terms of

net income obtained by subtracting material cost from the gross earnings for each activity. The

above tables also present the respective percentage share of each activity in the total household

income. The coefficient of variation is calculated for each activity across the working members.

The data on household income pertains to the calendar year 2009. A glance on the household

income statistics reveals that by and large estimated income of participant and non participant

households was on expected lines. The estimated per household income of non participant

households was higher compared to participant households. On an average, the selected non

participant households earned 70 thousand per annum compared to 59 thousand earned by the

54

participating households. Comparing the sources of income across different activities, it is

clearly evident from the tables that wage income constituted a lion’s share in the income of both

participating as well as non participating households. It was observed in the last section that

casual labour was the prominent occupation among the selected households. Looking at the share

of income obtained from different wage earning activities among the participants, it evident that

wage earnings in agriculture contributed around 17 per cent followed by wage earnings in non

agricultural activities 22 per cent, while wage earnings in MGNREGA activities contributed only

12 per cent share in the total household income of participants. In addition to wage earnings,

income from self employment in agriculture and livestock constituted around 17 per cent share

of their household income while regular salaried job contributed around 14 per cent share in the

household income of the participating households. Trends in share of various sources were

somewhat similar in the case of non participating households. Self business in agriculture and

livestock constituted 20 per cent share of their total household income while wages in agriculture

and non agriculture sectors constituted around 37 per cent share in their total income. The third

most important source of their income was regular employment in salaried job in various

activities. Income from self employment in non farming including that of business sector

constituted around 13 per cent share in their total household income.

Comparing household income per annum across the selected states for participants, the estimated

income was above 1 lakh in Kerala and Assam. It ranged between 50 thousand to 1 lakh in

Karnataka, Haryana, Madhya Pradesh, Himachal Pradesh, Gujarat and Rajasthan. The household

income per annum was found less than 50 thousand in Uttar Pradesh, Bihar, Sikkim, Andhra

Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal. Thus, majority of the states

observed household income less than the aggregate average of 59 thousand. Ironically, the

states that observed highest household income namely Kerala and Assam, however, had much

lower percentage coming from the MGNREGA activity less than 7 per cent in Kerala and only 3

per cent in Assam in the aggregate income. Highest share contributed by MGNREGA in total

household income was observed in Maharashtra (29 per cent), followed by Haryana and Sikkim

(25 per cent, each), Andhra Pradesh and Punjab (18 per cent, each), West Bengal, Rajasthan,

Madhya Pradesh and Uttar Pradesh (each having above 13 per cent share). The lower

contribution by MGNREGA was found in Assam (3 per cent), Kerala (7 per cent), (slightly

55

above 10 per cent). In most of the states, around 50 per cent of the income share was contributed

by casual wages either in agriculture or in non agricultural sector. As MGNREGA mandates only

100 days of employment provision per household (that target is also rarely achieved) and in

many cases there are two to three members working per household, thereby MGNREGA ensures

only partial employment provision and households ought to depend on alternate employment

avenues either in agriculture sector or in other casual activities. In the case of non participants,

household income pattern was also similar to that of participant households. The highest income

in their case was observed in Himachal Pradesh, Kerala and Assam. The lowest income was

found in Sikkim, followed by Bihar.

The coefficient of variation (CV) indicates the dispersion of income across household members

for the respective economic activities (Tables 3.4 and 3.4.1). The dispersion of income across

households was highest for agriculture and livestock income for both participant and non

participant households. High variability of agricultural income across households indicates

seasonal nature of agricultural occupation, diversified cropping pattern across households and

different amount of land cultivated by different households. Dispersion was also high in casual

wage earnings in the agriculture and non agricultural activities indicating their casual nature. The

dispersion was comparatively less in MGNREGA activities indicating lesser amount of wage

rate differentials in MGNREGA as compared to casual wage rate in agriculture and non

agricultural activities. Dispersion was also high in the salaried income.

3.4 Household consumption

Food consumption expressed in Kilocalories (Kcal) per capita is used for measuring the level of

nutrition. In defining poverty, the Planning Commission uses the calorie requirement norm of

2400 Kcal per capita for the rural areas and 2100 Kcal per capita for the urban areas. It further

emphasizes that 50 per cent of calories to be derived from carbohydrate and the remaining from

the protein and fat with 25 per cent each. Fifty per cent of the required calorie means drawing

1200 calorie from cereals in rural India and 1050 in the urban India. To get the requisite 1200

calories, 10.44 kg cereals per capita per 30 days or 348 gms per capita per day are required by

56

the rural people and 9.12 kg cereals per capita per 30 days or 304 gms per capita per day are

required by the urban people to obtain 1050 calories1.

Tables 3.5 and 3.5.1 present per capita monthly consumption of food items, viz., cereals, pulses,

edible oils, sugar and milk by our selected participant and non participant households. It is

evident from the results that on average per capita cereal consumption satisfied the 1200-calorie

norm, i.e., total cereal consumption surpassed 10.5 kgs per capita per month by both the

participant and non participant households. The average cereal consumption was measured at

11.1 kg per capita per month in the case of participants and 11.6 kg per capita per month in the

case of non participants. Rice and wheat were the major cereals consumed with average amount

of 4.8 kg and 4.4 kg, respectively among the participants and 5.2 kg and 4.6 kg, respectively by

the non participants. Coarse cereals consumption was 1.8 kg among participants and 1.5 kg

among non participants.

The states that reported less than 10.5 kg cereal consumption were Bihar, Punjab, Maharashtra

and Rajasthan among both participants and non participants. Karnataka, Sikkim, Andhra

Pradesh, Chhattisgarh, Assam and West Bengal had rice as the staple cereal whereas Haryana,

Madhya Pradesh, Punjab and Rajasthan had wheat as the major cereal of consumption. The states

that had combination of wheat and rice consumption were Uttar Pradesh, Maharashtra, Himachal

Pradesh and Gujarat. Pulses consumption varied between 0.5 to 3 kg per capita per month among

different selected states and it averaged around 1 kg among both the participants and non

participants. On an average consumption basket including sugar, milk and milk products, edible

oils and fruits and vegetables were found similar among participant and non participant

households at the aggregate.

Table 3.5.2 presents household consumption of food items as revealed by the 66th

Round of

National Sample Survey (NSS) for the year 2009-10 for rural areas. The NSS data which

coincides with our survey period shows that at all India, rice consumption per capita per month

was 6 kg and wheat consumption was 4 kg per capita that compares well with our participant and

1 The above calculations are based on Planning Commission (1977) calculations that 100 gms cereal on an average

produce 345 calories.

57

non participant consumption. At the aggregate, total cereal consumption in India according to

NSS data was 11.4 kg that compared with 11.1 kg for our participant households and 11.6 kg for

the non participants. The states that had less than 10.5 kg of cereal consumption according to

NSS data were Haryana, Punjab, Gujarat, Maharashtra and Karnataka that also stand close to our

survey data. The reason, why the richer states like Punjab, Haryana, Gujarat and Maharashtra

observed less consumption of cereals, seems to be the diversification of consumption basket

taking place from the traditional cereal and pulse crops to high value commodities like milk and

meat products and fruits and vegetables. It is evident from the NSS consumption data that milk

consumption was highest in Haryana and Punjab and meat consumption topped in better off

states like Karnataka, Andhra Pradesh and West Bengal.

It is now well established that per capita consumption of cereals and total calorie intake in most

of the Indian states has started declining in the recent past. Total cereals consumption declined

from 14.9 kg to 11.8 kg in Rajasthan, 14.3 kgs to 12.2 kg in Bihar, 13.9 kgs to 12 kg in Uttar

Pradesh, 13 kg to 12.89 kg in Assam, 14.2 kg to 11.3 kg in Madhya Pradesh and 11.4 kgs to 10.2

kg in Maharashtra during almost two decades time period from 1993-94 to 2009-10. This

declining trend in cereal consumption has been caused by the diversification of food basket and

the changing income and lifestyle of the rural and urban masses. On the one hand, due to change

in work nature, the requirement of calorie intake has declined overtime and on the other, the

changes in the composition of diet have increased the cost of calories (Radhakrishna and Ravi,

1991; Murty, 1999). Convergence between rural and urban patterns of calorie consumption also

provides an explanation to this phenomenon.

The food basket of an average Indian is diversifying with her rising income and improved living

standards. Whereas, cereals and pulses were the main source of protein in both rural and urban

areas in the seventies and early eighties, the contribution of milk and milk products as source of

protein is consistently increasing in the more recent rounds of NSS and the increase is observed

much more in the urban areas. The contribution from meat, fish and eggs to protein has slightly

increased (Delgado, et. al. 1999). The diversification of consumption from cereals and pulses

towards edible oils, milk and high value products was also visible from the trends presented in

our data. Comparing the participant and non participant households, non participants were better

58

off compared to participant households as was depicted by their household income. The quantity

of high value commodities like milk and milk products, fruits and vegetables was higher for non

participant households compared to participant households. Therefore, these trends substantiate

our argument that with the rising level of income, people have a tendency to diversify their

palate towards more nutritious and high value commodities. Comparing the consumption of

other commodities like milk, sugar, edible oil etc., with NSS, generally the quantity consumed

by our participant and non participant households closely matched with the NSS 2009-10 data.

Various rounds of NSS consumption expenditure data reveals that the share of non-cereal items

in the monthly per capita expenditure (All India) has been consistently increasing in both rural

and urban areas. The share of non-food consumption expenditure increased from 27 per cent in

1972-73 to 41 per cent in 1999-00 which went up to 43 per cent in 2009-10 in rural areas, while

it increased from 36 per cent to 52 and further to 55.6 per cent in the urban areas during the same

time period. In 2009-10, about 57 per cent of the total consumption expenditure (All India) was

on food items in rural areas, while it was 44 per cent in the urban areas. As our selected sample

constitutes only rural households, expenditure on food is expected to lead that of non-food

expenditure to commensurate with the NSS trends as discussed above. Monthly consumption

expenditure per capita for participants and non participants for our selected states for food and

non-food items are given in Table 3.6 and 3.6.1. Tables present percentage distribution of each

food item in total food expenditure, each non-food item in total non-food expenditure and

percentage of total food items and total non-food items in the total expenditure.

Monthly per capita food consumption expenditure was measured as 420 for participant and

455 for non participant households (Tables 3.6 and 3.6.1). Total expenditure on cereals was

observed as 139 for participants and 143 for non participants. The corresponding amount for

the NSS 2009-10 (66th

Round) for all India was 145. In pulses, expenditure by our sample

households averaged at 44 per capita per month (that was almost same for both the categories)

which stands close to NSS average expenditure for pulses at 35. Consumption of edible oil by

our participants averaged around 34 for both the categories was also close to the national

average shown by the NSS 69th

Round of 39. Consumption of other high value commodities

like fruits, vegetables, milk and meat products were slightly higher for non participants

59

compared to participants and overall their value was comparable with that of NSS consumption

expenditure. Total monthly food expenditure among our selected sample averaged at 421 for

the participants and 455 for the non participants, whereas NSS food expenditure for all India

averaged around 600.

The difference between participants and non participants was much higher in the non food

expenditure, especially in education, clothing and other items including medical and health. The

overall non food expenditure was 237 per capita per month among the participants compared

to 271 among the non participants. Our non food expenditure was under estimated as is clear

from the much above NSS amount of 453. Almost all items of non food expenditure in the case

of our sample households were less than that of NSS. The difference could be due to under

reporting and may be few items missing in our questionnaire like conveyance, consumer

services, various entertainment goods, rent, taxes and other durable goods. Comparing food and

non-food expenditure, the proportion of food in total expenditure was 64 per cent among the

participants and 63 per cent among the non participants. In comparison, share of food

expenditure in the NSS data was 57 per cent of total expenditure that also indicate that our non

food expenditure was slightly under estimated.

3.5 Variability (CV) and Gini ratios of income and consumption

Distribution of observed income and consumption per household of the selected participants and

non participants is presented in Tables 3.7 and 3.7.1. In most of the states household income

exceeded household consumption per annum indicating household net savings. Karnataka, Bihar,

Andhra Pradesh and Rajasthan among the participants and Bihar and Rajasthan among non

participants made exception where consumption exceeded income and the selected households

had to depend either on the past savings or on borrowing from various sources. Glancing through

the coefficients of variation in the tables it is observed that variation in consumption across the

households was less than that of income. It indicates that consumption was more symmetric

compared to income. The coefficient of variation of income was higher compared to

consumption in most of the states. The only exception was Karnataka and Sikkim among the

participants while among non participants it was across the board. Looking at the concentration

ratio, the Gini coefficient of income was also mostly higher than that of consumption for both

60

participants and non participants. However, compared to coefficient of variation, Gini

coefficients of income and consumption were closer compared to coefficient of variation that

showed comparatively higher variation among the two. Thus, higher variation in income

compared to consumption shows the more vulnerability of the household in the case of an

external shock to the household income and the necessity of households to search for some

formal or informal sources of consumption smoothening (Kumar and Singh in press).

3.6 Factors determining participation in MGNREGA

Unlike other poverty removal programmes that are mostly supply based, NREGA programme is

demand driven programme, whereby every household in rural areas is given opportunity to

register any time to work under NREGA in any unskilled work at the stipulated wage rate which

is supposed to be not less than the minimum wage rate prevailing in that state. In this section, we

try to ascertain the factors that determine the participation of a particular household to register

for working under NREGA. We run two sets of equations, first at the household level and second

at the member level. In each state, at the household level, we have 250 observations pertaining to

200 observations for the participants and 50 observations for the non participants. At the member

level, numbers of observations vary from state to state depending upon the size of the household

in each state. Generally we have around more than 1000 members in each state in the category of

participating households and above 250 members in the non participating households. In the first

set, we used a logistic2 regression model regressing participation in NREGA (with households or

members who registered and worked in NREGA with value 1 and those who did not with value 0

on the explanatory variables. The explanatory variables included continuous variables as

household size, household employment and income, value of assets; and dummy variables, such

as, land ownership with value 1 for those who owned land and zero for others, dummy for AAY

and BPL card holders and dummy for various social characteristics such as households being SC,

2 In statistics, logistic regression (sometimes called the logistic model or logit model) is used for prediction of the

probability of occurrence of an event by fitting data to a logit function logistic curve. It is a generalized linear model

used for binomial regression. Like many forms of regression analysis, it makes use of several predictor variables that

may be either numerical or categorical. Logistic regression is a variation of ordinary regression which is used when

the dependent (response) variable is a dichotomous variable (i. e. it takes only two values, which usually represent

the occurrence or non-occurrence of some outcome event, usually coded as 0 or 1) and the independent (input)

variables are continuous, categorical, or both. Unlike ordinary linear regression, logistic regression does not assume

that the relationship between the independent variables and the dependent variable is a linear one. Nor does it

assume that the dependent variable or the error terms are distributed normally.

61

ST or OBC. In the second set of equations, instead of regressing dichotomous variable with

value zero or one, we tried continuous variable as response or dependent variable. We regressed,

the number of days of employment in NREGA by a household on the above mentioned

independent variables. The member level regression was done only among the participant

households. The results of the above two sets of equations are presented in Tables 3.8 to 3.10.

The logit function provides us the probabilities of the participation of a household in

MGNREGA activities. State level regression results presented in Table 3.8 show that the

households who had alternate employment opportunities and those who had higher income

contribution from other activities had less incentives to work in MGNREGA. The coefficient for

employment other than MGNREGA was negative and significant in Sikkim, Haryana, Madhya

Pradesh and Chhattisgarh. Coefficient of income other than MGNREGA was significant and

negative in Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and Himachal Pradesh. The

household size had significant and positive sign in Karnataka, Andhra Pradesh, Kerala, Haryana,

Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal indicating with increase in

family size there was more probability of household members working in MGNREGA among

the selected households. Household size had significant but negative relationship in Uttar

Pradesh and Himachal Pradesh indicating low participation at higher family size in these two

states.

The value of assets and land ownership had negative sign in the regression indicating household

members with land ownership or better assets accumulation had less probability of participating

in MGNREGA activities although legally there was no bar on the households having land

ownership in registering for NREGA work. The coefficient was significant with a negative sign

in Karnataka, Uttar Pradesh, Sikkim, Madhya Pradesh, Assam, Punjab and West Bengal. On the

opposite, if a household owned an AAY or BPL card or if they belonged to Scheduled Caste or

Scheduled Tribe community they had higher possibility of entering into MGNREGA work. The

coefficient of dummy BPL was found positive and significant in Karnataka, Sikkim and in

Haryana. Similarly, coefficient of social characteristics (household belonging to SC, ST and

OBC) was found significant and positive in Sikkim, Andhra Pradesh, Chhattisgarh and

Maharashtra.

62

In the logit regression on member participation in MGNREGA (Table 3.9), we clubbed some

member level variables with the household variables. Some interesting relations emerged out of

this exercise. For example, among the members in a household, those who worked in

MGNREGA had a direct and significant relationship with age and negative relationship with

education. The implication is that older age and less educated people preferred to work in

MGNREGA as the latter is known providing soft wages. Similarly, the dummy on sex indicates

that the male members had higher probability of working in MGNREGA compared to female

members although female proportion in total work force constituted around 45 per cent varying

in its degree from state to state. The members with BPL and AAY cards and members belonging

to SC and ST community had better probability of working in MGNREGA. The above findings

were generally true across the states.

In the alternate regressions, continuous variable of number of days per household worked in

MGNREGA was used instead of dummy variable of participation in MGNREGA (Table 3.10).

In this household level regression, employment other than MGNREGA was significant with a

negative sign in Karnataka, Sikkim, Chhattisgarh and West Bengal indicating that those

households who had employment opportunities in other activities did not prefer to work in

MGNREGA. The other most important and significant variable was wage rate in MGNREGA

with a positive sign in almost all the states indicating that with higher wage rate households

preferred to work in MGNREGA. Once again the economic backwardness indicated by AAY

and BPL card holding and social backwardness indicating by lower castes like SC, ST and OBC

were found having positive and significant association with participation in MGNREGA in most

of the states. Household income other than MGNREGA, household size and value of land were

the other variables that were significant in some of the states.

3.7 Summary of the chapter

This chapter presents households characteristics and income and consumption details of the

selected households. The average household size was 4.75 with participants having average

family size of 4.7 and non participants 4.9. The average numbers of earners in the family were

2.2 members among participating families and 2.6 members among the non participating

families. On the overall, non participants were better educated compared to participant household

63

members. The trends in occupation depict that among the participating households, the

proportion of work provided by MGNREGA was only a small proportion of their aggregate

employment. Out of the total man days employed per household including all the working

members, the share of MGNREGA varied between 12 to 32 per cent among different states. At

the aggregate, MGNREGA provided 18 per cent share in the total employment among our

selected households. Casual labour in agriculture and non agriculture sector constituted more

than 40 per cent share in employment. Self employment in agriculture and livestock constituted

around 20 per cent share and self employment in business and regular salary had around 5 and 10

per cent share, respectively in the total employment among the selected participants.

A glance on the household income statistics reveals that the estimated per household income of

non participant households was higher compared to participant households. On an average, the

selected non participant households earned 70 thousand per annum compared to 59 thousand

earned by the participating households. Comparing the sources of income across different

activities, wage income constituted a lion’s share in the income of both participating as well as

non participating households. The dispersion of income across households was highest for

agriculture and livestock income for both participant and non participant households while it was

comparatively less in MGNREGA activities indicating lesser amount of wage rate differentials in

MGNREGA as compared to casual wage rate in agriculture and non agricultural activities. On

average, per capita cereal consumption satisfied the 1200-calorie norm, i.e., total cereal

consumption surpassed 10.5 kgs per capita per month by both the participant and non participant

households. The average cereal consumption was measured at 11.1 kg per capita per month in

the case of participants and 11.6 kg per capita per month in the case of non participants. Pulses

consumption varied between 0.5 to 3 kg per capita per month among different selected states and

it averaged around 1 kg among both the participants and non participants. The diversification of

consumption from cereals and pulses towards edible oils, milk and high value products was

visible from our data.

Total monthly food expenditure among our selected sample averaged at 421 for the participants

and 455 for the non participants whereas NSS food expenditure for all India averaged around

600. The overall non food expenditure was 237 per capita per month among the participants

64

compared to 271 among the non participants. Our non food expenditure was under estimated as

is clear from the much above NSS amount of 453. The difference could be due to under

reporting and may be few items missing in our questionnaire. The, higher variation in income

compared to consumption shows the more vulnerability of the household in the case of an

external shock to the household income and the necessity of households to search for some

formal or informal sources of consumption smoothening.

The logit function provided us the probabilities of the participation of a household in

MGNREGA activities. State level regression results showed that the households who had

alternate employment opportunities and those who had higher income contribution from other

activities had less incentive to work in MGNREGA. The value of assets and land ownership had

negative sign in the regression indicating household members with land ownership or better

assets accumulation had less probability of participating in MGNREGA activities. On the

opposite, if a household owned an AAY or BPL card or if they belonged to Scheduled Caste or

Scheduled Tribe community they had higher possibility of entering into MGNREGA work. From

the household OLS regression, the most important and significant variable emerged was wage

rate in MGNREGA with a positive sign in almost all the states indicating that with higher wage

rate households preferred to work in MGNREGA. Some interesting relations were observed in

the member level logit regression. Among the members in a household, those who worked in

MGNREGA had a direct and significant relationship with age and negative relationship with

education. The implication is that older age and less educated people preferred to work in

MGNREGA as the latter is known providing soft wages. Similarly, the dummy on sex indicates

that the male members had higher probability of working in MGNREGA compared to female

members. The members with BPL and AAY cards and members belonging to SC and ST

community had better probability of working in MGNREGA. The above findings were generally

true across the states.

65

Table 3.1 Demographic profile of the respondents (Percentage of households) – Participants S

tate

s

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Characteristics

No of HH 201 200 200 160 200 200 200 200 200 200 200 205 200 200 200 200 3166

Household size (numbers) 5.29 4.15 6.38 4.33 4.20 3.47 5.59 5.14 3.00 4.92 3.78 5.13 4.28 5.52 5.43 4.53 4.70

Average number of earners 2.68 2.31 2.25 3.12 2.61 1.42 2.68 2.00 1.00 1.57 1.92 2.81 0.00 3.55 2.50 2.42 2.17

Age group <16 24.9 34.1 0.0 0.0 27.2 10.8 33.1 0.0 0.0 29.7 15.6 32.3 24.2 33.7 38.1 0.0 19.9

16-60 68.3 63.9 91.0 91.9 69.6 79.9 62.7 96.0 96.0 63.1 76.6 61.1 69.0 64.0 58.1 94.0 74.4

>60 6.8 2.1 9.0 8.1 3.2 9.3 4.2 4.0 4.0 7.2 7.4 5.6 6.8 2.3 3.8 6.0 5.6

Identity of

respondent

Head 54.2 99.5 72.0 79.4 95.0 66.5 65.5 85.0 84.0 90.5 35.0 82.4 90.5 43.5 73.5 96.0 75.1

Others 45.8 0.5 28.0 22.6 5.0 33.5 34.5 15.0 16.0 9.5 65.0 17.7 9.5 56.5 26.5 4.0 25.0

Education

status (Above

only)

Illiterate 35.5 43.0 31.5 21.9 47.2 2.7 38.8 46.0 43.0 18.2 52.2 39.6 18.0 37.4 44.4 46.0 35.8

Up to primary 23.2 36.7 44.5 73.1 34.5 14.8 48.1 25.0 33.0 56.2 32.3 16.4 27.8 25.4 23.9 30.5 33.8

Up to secondary 39.4 15.2 23.0 4.4 19.1 68.5 12.1 26.5 22.0 21.4 10.6 34.0 39.5 35.2 28.5 23.5 26.5

Up to graduate 1.9 3.5 1.0 0.6 3.4 11.0 0.9 2.5 2.0 3.9 0.1 9.5 2.9 1.8 2.7 0.0 2.9

Above graduate 0.0 1.7 0.0 0.0 0.4 3.0 0.1 0.0 0.0 0.4 0.1 0.1 0.4 0.1 0.5 0.0 0.4

Caste SC 34.3 49.0 38.0 5.0 27.5 12.0 61.0 35.0 17.5 34.0 86.0 20.6 33.0 24.0 25.5 37.5 34.1

ST 8.5 1.0 0.0 53.8 13.0 3.5 6.0 34.5 39.0 10.5 0.0 38.2 13.5 20.0 24.5 6.5 16.6

OBC 26.9 46.0 52.0 40.6 40.5 59.0 31.0 28.0 41.5 26.0 9.5 35.3 22.5 54.5 25.0 4.5 33.8

General 30.4 4.0 10.0 0.6 19.0 25.5 2.0 2.5 2.0 29.5 4.5 5.9 31.0 1.5 25.0 51.5 15.5

Card

holding

AAY 47.8 18.5 19.5 0.0 4.5 17.5 0.0 9.0 21.5 0.0 78.0 15.2 10.0 3.0 2.5 5.5 16.0

BPL 39.3 34.0 52.5 93.8 91.5 42.5 83.0 50.5 55.5 74.0 22.0 49.2 33.0 55.0 44.0 42.5 53.4

APL 11.9 47.0 8.5 6.3 2.5 40.0 8.5 30.5 11.5 19.0 0.0 22.6 55.0 40.0 45.0 50.0 25.1

None 1.0 8.5 19.5 0.0 1.5 0.0 8.5 10.0 11.5 7.0 0.0 13.2 2.0 2.0 8.5 2.0 6.0

Decision

maker

Male 83.6 90.0 70.0 86.3 87.5 71.0 84.5 94.5 90.5 97.0 95.0 87.8 83.5 80.0 87.5 76.5 85.3

Female 16.4 10.0 30.0 13.8 12.5 29.0 15.5 5.5 9.5 3.0 5.0 12.3 16.5 20.0 12.5 23.5 14.7

Main occupation

Farming 16.0 38.1 56.5 31.5 5.2 0.7 0.0 18.5 29.0 8.0 2.0 43.7 49.1 21.8 11.6 19.5 22.5

Self business 6.1 1.4 0.0 6.3 1.1 8.2 0.6 3.5 1.5 3.0 9.5 1.6 3.3 0.5 4.3 2.5 3.1

Salaried / pensioners 6.3 1.9 0.0 6.9 1.9 6.7 0.8 2.5 0.0 9.5 12.5 1.2 12.3 0.9 6.7 0.5 4.2

Wage earners 71.6 58.7 43.5 54.4 91.4 84.4 98.7 68.5 53.5 79.5 76.0 53.5 32.3 76.8 77.4 69.5 68.4

Others 0.0 0.0 0.0 1.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4 0.0 0.0 8.0 0.6

Involved in migration during year

2009

2.73 0.00 15.00 0.00 6.91 0.00 1.00 0.00 13.50 60.50 0.00 11.65 6.66 47.00 6.00 21.50 12.18

66

Table 3.1.1 Demographic profile of the respondents (Percentage of households) - Non- Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Characteristics

No of HH 54 50 50 40 50 50 50 50 50 50 100 45 50 50 50 50 839

Household size (numbers) 4.89 4.80 6.00 4.47 3.44 3.15 4.86 4.46 10.00 5.22 3.92 4.98 4.60 5.32 5.44 4.21 4.93

Average number of earners 1.94 2.26 2.32 2.03 2.74 1.60 2.36 1.00 1.00 1.62 1.70 2.56 0.00 3.30 2.10 2.12 2.60

Age group <16 42.1 0.0 0.0 23.0 6.5 28.3 0.0 0.0 31.8 15.9 33.5 30.4 39.1 33.6 0.0 0.0 18.7

16-60 54.6 76.0 90.0 69.8 76.8 65.2 98.0 94.0 60.2 80.0 62.5 62.2 59.0 62.3 88.0 88.0 73.7

>60 3.3 24.0 10.0 7.2 16.8 6.6 2.0 6.0 8.1 4.1 3.6 7.4 1.9 4.1 12.0 12.0 7.5

Identity of

respondent

Head 94.0 74.0 80.0 100.0 64.0 60.0 92.0 74.0 94.0 52.0 84.4 82.0 64.0 94.0 96.0 96.0 77.2

Others 6.0 26.0 20.0 0.0 36.0 40.0 12.0 26.0 6.0 48.0 15.6 18.0 36.0 6.0 4.0 4.0 23.0

Education

status

(Above only)

Illiterate 33.8 14.0 15.0 47.9 0.0 34.2 30.0 48.0 19.5 51.4 29.9 10.9 24.9 41.6 36.0 36.0 31.1

Up to primary 37.5 34.0 62.5 23.9 8.4 48.7 24.0 38.0 45.2 37.4 15.6 24.4 34.5 29.2 32.0 32.0 33.1

Up to secondary 18.3 34.0 22.5 21.2 53.6 15.8 36.0 14.0 30.3 11.2 37.5 45.2 39.4 27.3 22.0 22.0 28.2

Up to graduate 10.0 18.0 0.0 7.1 30.3 0.9 8.0 0.0 4.2 0.0 15.6 3.0 0.8 1.9 10.0 10.0 6.1

Above graduate 0.4 0.0 0.0 0.0 7.7 0.5 2.0 0.0 0.8 0.0 0.9 1.3 0.4 0.0 0.0 0.0 0.7

Caste SC 44.0 28.0 2.5 16.0 4.0 62.0 36.0 14.0 34.0 88.0 15.6 34.0 16.0 22.0 30.0 30.0 33.1

ST 0.0 0.0 27.5 2.0 0.0 4.0 14.0 36.0 10.0 0.0 28.9 18.0 18.0 26.0 16.0 16.0 12.0

OBC 46.0 38.0 55.0 52.0 54.0 32.0 38.0 48.0 36.0 8.0 35.6 14.0 64.0 32.0 4.0 4.0 34.8

General 10.0 34.0 15.0 30.0 42.0 2.0 12.0 2.0 20.0 4.0 20.0 34.0 2.0 20.0 50.0 50.0 20.0

Card holding AAY 24.0 2.0 27.5 4.0 6.0 2.0 6.0 16.0 0.0 73.0 15.6 6.0 8.0 0.0 4.0 4.0 17.9

BPL 22.0 20.0 52.5 92.0 16.0 72.0 38.0 64.0 44.0 25.0 35.6 34.0 36.0 24.0 40.0 40.0 39.3

APL 54.0 30.0 20.0 2.0 78.0 8.0 40.0 10.0 40.0 2.0 35.6 60.0 56.0 64.0 50.0 50.0 34.1

None 0.0 48.0 0.0 2.0 0.0 18.0 16.0 10.0 16.0 0.0 13.3 0.0 0.0 12.0 6.0 6.0 8.7

Decision

maker

Male 94.0 62.0 92.5 92.0 96.0 92.0 90.0 92.0 100.0 98.0 88.9 98.0 88.0 98.0 82.0 82.0 91.3

Female 6.0 38.0 7.5 8.0 4.0 8.0 10.0 8.0 0.0 2.0 11.1 2.0 12.0 2.0 18.0 18.0 8.7

Main occupation

Farming 46.0 52.0 45.0 23.7 0.0 0.0 26.0 22.0 22.0 2.0 48.6 46.7 21.1 17.8 20.0 20.0 26.5

Self business 5.3 20.0 25.0 20.3 11.5 0.0 16.0 10.0 4.0 10.0 8.3 6.7 0.9 12.1 8.0 8.0 9.9

Salaried/pensioners 1.8 2.0 5.0 6.1 59.0 2.5 10.0 2.0 14.0 16.0 6.4 35.0 0.9 8.4 8.0 8.0 10.3

Wage earners 46.9 26.0 10.0 49.9 29.5 97.5 42.0 52.0 60.0 72.0 36.7 10.8 77.2 61.7 52.0 52.0 50.0

Others 0.0 0.0 15.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.0 12.0 12.0 1.3

Involved in migration during

year 2009

2.65 0.00 9.00 0.00 8.00 0.00 0.00 0.00 10.00 82.00 0.00 11.16 1.74 42.00 9.40 14.00 11.27

67

Table: 3.2: Main Occupation (% of total man-days per hh) – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation

Agricultural casual labour 43.7 16.6 26.1 6.9 35.4 7.3 35.8 22.0 11.0 2.7 34.1 25.6 4.4 20.3 9.7 24.2 20.5

Non-agricultural casual labour 12.5 35.9 12.0 12.8 6.9 16.2 27.8 18.7 21.7 41.1 38.5 9.1 12.5 28.1 20.8 36.6 22.0

Work for PWP other than NREGA 0.1 2.3 6.0 0.0 0.0 0.0 0.2 0.2 0.9 0.0 0.0 0.1 1.3 0.6 0.3 0.0 0.8

Self employed in non-farming 4.3 6.7 0.0 6.2 1.6 11.2 0.0 13.7 6.0 12.3 5.3 1.1 3.1 0.6 4.2 4.3 5.0

Self employed in agriculture 10.0 15.3 12.0 25.0 9.3 9.2 0.0 10.3 14.8 6.5 0.0 12.7 17.1 7.7 13.7 9.8 10.7

Self employed in livestock 5.0 1.4 8.0 10.7 8.9 0.0 11.1 2.7 12.1 9.7 0.9 19.9 17.8 7.2 16.5 4.7 8.5

Regular/salary job 9.1 2.0 0.0 22.0 5.5 44.6 0.5 5.6 10.3 10.0 0.0 2.8 22.3 1.6 10.6 3.7 9.2

Worked as migrant worker 3.0 4.3 3.5 0.0 0.8 0.0 0.1 10.4 7.5 3.8 0.0 8.6 2.0 22.0 6.5 4.3 4.9

Worked under NREGA 12.2 15.5 29.0 16.4 31.5 11.5 24.6 16.3 15.8 13.9 21.2 20.3 19.7 12.0 17.7 12.3 18.1

Any other 0.0 0.0 3.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2

Total 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

68

Table: 3.2.1 Main Occupation (% of total man-days per hh) - Non- Participants

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Occupation

Agricultural casual labour 16.9 26.1 20.0 4.0 18.7 7.2 34.7 11.9 14.3 7.7 26.7 22.1 0.8 16.6 10.7 16.2 16.7

Non-agricultural casual labour 18.5 38.8 13.0 10.3 23.1 22.3 53.1 16.8 32.9 36.3 61.2 8.9 9.6 44.3 28.5 34.2 30.5

Work for PWP other than NREGA 0.6 4.6 7.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 1.6 0.0 0.0 0.9

Self employed in non-farming 4.2 8.0 11.0 25.3 13.6 14.0 0.0 28.1 12.5 29.4 6.8 5.2 9.5 0.0 9.9 16.9 11.7

Self employed in agriculture 29.5 15.9 30.0 24.3 27.2 0.0 0.0 18.5 10.3 2.2 0.9 19.8 13.3 8.3 6.9 12.4 12.9

Self employed in livestock 7.8 1.0 12.0 11.1 2.3 0.0 11.6 3.4 15.0 3.7 1.8 25.8 15.9 4.7 17.6 3.1 8.0

Regular/salary job 19.9 0.0 2.0 25.1 13.3 56.5 0.0 21.4 14.9 14.8 2.6 9.0 50.9 1.1 12.1 7.2 14.8

Worked as migrant worker 2.7 5.6 3.0 0.0 1.8 0.0 0.0 0.0 0.0 5.9 0.0 9.2 0.0 23.5 14.3 10.0 4.5

Any other 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

Total 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

69

Table: 3.3: Household net income (Annual) (Rs. Per household)* - Participants

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Characteristics

Income from work under NREGA 6524 6128 4121 8118 6939 7409 14086 7584 5330 4154 6660 11913 9302 7084 6572 5252 7320

(11.4) (13.1) (10.1) (25.0) (18.1) (6.7) (25.0) (13.7) (11.0) (3.3) (17.8) (28.5) (10.6) (9.3) (13.1) (14.3) (12.4)

Income from wages in agriculture 22524 3593 10347 2782 12501 22318 20954 8016 7689 3118 12386 8812 2150 11183 3729 7989 10099

(39.4) (7.7) (25.3) (8.6) (32.6) (20.2) (37.3) (14.4) (15.9) (2.5) (33.1) (21.1) (2.4) (14.7) (7.4) (21.7) (17.0)

Income from wages non agriculture 9928 15693 10016 5682 5973 25551 18439 14092 12477 16826 14375 3606 7097 25029 11737 13652 13214

(17.3) (33.5) (24.5) (17.5) (15.6) (23.1) (32.8) (25.4) (25.9) (13.4) (38.4) (8.6) (8.1) (33.0) (23.4) (37.1) (22.3)

Income from wages in PWP 64 1004 3630 0 0 0 150 302 218 0 0 59 433 409 198 0 409

(0.1) (2.1) (8.9) (0.0) (0.0) (0.0) (0.3) (0.5) (0.5) (0.0) (0.0) (0.1) (0.5) (0.5) (0.4) (0.0) (0.7)

Income from wages as migrant

workers

1997 12640 3193 0 652 0 0 4798 6118 2168 0 7367 9525 19888 6893 2725 4937

(3.5) (27.0) (7.8) (0.0) (1.7) (0.0) (0.0) (8.6) (12.7) (1.7) (0.0) (17.6) (10.8) (26.2) (13.8) (7.4) (8.3)

Income from self employed in non

farming

2470 1691 0 1848 1831 21423 0 3581 2924 25888 3377 586 2415 980 2680 1096 4577

(4.3) (3.6) (0.0) (5.7) (4.8) (19.4) (0.0) (6.4) (6.1) (20.6) (9.0) (1.4) (2.7) (1.3) (5.3) (3.0) (7.7)

Income from agriculture/livestock 8723 4938 8381 6208 9591 11250 2430 13205 10588 10735 621 8664 32284 6167 12948 4961 9521

(15.2) (10.5) (20.5) (19.1) (25.0) (10.2) (4.3) (23.8) (21.9) (8.5) (1.7) (20.7) (36.7) (8.1) (25.8) (13.5) (16.1)

Income from livestock 1373 0 0 1439 0 0 0 0 0 0 0 0 0 2755 0 424 361

(2.4) (0.0) (0.0) (4.4) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (3.6) (0.0) (1.2) (0.6)

Income from regular job/

salary/pension

3621 1165 0 6350 865 22544 180 3897 2894 62859 0 755 16444 1039 3854 742 7958

(6.3) (2.5) (0.0) (19.6) (2.3) (20.4) (0.3) (7.0) (6.0) (50.0) (0.0) (1.8) (18.7) (1.4) (7.7) (2.0) (13.5)

Income from sale of assets/

rent/transfer etc.

10 0 1194 0 0 0 0 73 0 0 0 0 8218 1288 1507 0 776

(0.0) (0.0) (2.9) (0.0) (0.0) (0.0) (0.0) (0.1) (0.0) (0.0) (0.0) (0.0) (9.4) (1.7) (3.0) (0.0) (1.3)

Total 57234 46852 40882 32426 38352 110494 56239 55548 48236 125748 37418 41762 87868 75822 50117 36842 59171

(100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)

70

Table: 3.3.1: Household net income (Annual) (Rs. Per household)* - Non- Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Characteristics

Income from wages in agriculture 6188 7659 10403 1717 6698 32563 14629 7709 6766 2581 10346 8338 147 9189 3963 4766 8541

(6.6) (14.0) (25.0) (4.8) (15.4) (25.9) (34.3) (12.3) (12.2) (2.4) (24.1) (12.3) (0.1) (11.1) (6.8) (9.5) (12.3)

Income from wages non agriculture 11291 17277 6242 5567 10150 33364 25464 17791 14925 11107 24803 9193 8755 39664 17974 9890 17111

(12.1) (31.6) (15.0) (15.7) (23.4) (26.5) (59.7) (28.3) (26.9) (10.5) (57.7) (13.5) (5.1) (47.9) (30.8) (19.7) (24.5)

Income from wages in PWP 370 1650 2913 0 0 0 288 0 0 0 0 0 964 442 0 0 397

(0.4) (3.0) (7.0) (0.0) (0.0) (0.0) (0.7) (0.0) (0.0) (0.0) (0.0) (0.0) (0.6) (0.5) (0.0) (0.0) (0.6)

Income from wages as migrant

workers

1059 18250 4223 0 380 0 0 2026 15078 2402 0 9009 0 20281 16878 3324 5488

(1.1) (33.4) (10.2) (0.0) (0.9) (0.0) (0.0) (3.2) (27.2) (2.3) (0.0) (13.3) (0.0) (24.5) (29.0) (6.6) (7.9)

Income from self employed in non

farming

1763 3190 4577 8725 5831 35222 0 8818 7058 20271 5980 6971 15956 0 6150 12227 8726

(1.9) (5.8) (11.0) (24.6) (13.4) (28.0) (0.0) (14.0) (12.7) (19.2) (13.9) (10.3) (9.4) (0.0) (10.6) (24.4) (12.5)

Income from agriculture/ livestock 57944 6569 10236 7399 17370 0 2280 12090 10187 8043 588 30167 44053 9660 9540 9486 14085

(62.2) (12.0) (24.6) (20.8) (40.0) (0.0) (5.3) (19.2) (18.4) (7.6) (1.4) (44.4) (25.8) (11.7) (16.4) (18.9) (20.2)

Income from livestock 2639 0 0 2350 0 0 0 0 0 0 1260 0 0 2370 0 280 590

(2.8) (0.0) (0.0) (6.6) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (2.9) (0.0) (0.0) (2.9) (0.0) (0.6) (0.8)

Income from regular job/

salary/pension

11889 0 832 9750 3012 24632 0 14398 1440 61357 0 4196 59471 280 3348 10160 12118

(12.8) (0.0) (2.0) (27.5) (6.9) (19.6) (0.0) (22.9) (2.6) (58.0) (0.0) (6.2) (34.9) (0.3) (5.7) (20.3) (17.4)

Income from sale of assets/

rent/transfer etc.

0 0 2185 0 0 0 0 0 0 0 0 0 41093 1000 430 0 2664

(0.0) (0.0) (5.2) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (24.1) (1.2) (0.7) (0.0) (3.8)

Total 93143 54595 41610 35508 43441 125780 42661 62833 55453 105761 42976 67874 17044

0

82886 58283 50133 69721

(100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)

71

Table: 3.4: Variability (CV) in income across households – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Occupation

Income from work under NREGA 118.0 42.9 26.1 63.2 55.7 70.0 31.8 33.2 47.6 81.4 132.7 107.1 90.0 45.6 72.0

Income from wages in agriculture 94.6 92.7 82.0 37.3 94.8 80.0 29.1 24.1 60.9 75.4 101.4 248.2 110.0 131.4 77.9

Income from wages non agriculture 204.4 58.2 78.2 91.7 43.8 153.0 52.6 62.3 52.3 105.4 305.7 197.7 168.0 67.1 94.1

Income from wages in PWP 642.6 186.4 - - 0.0 - 191.2 287.2 0.0 - 1431.8 715.9 320.0 554.1 -

Income from wages as migrant workers 437.2 330.0 - 242.6 0.0 0.0 186.7 113.4 66.2 - 287.6 305.2 196.0 255.7 370.6

Income from self employed in non farming 439.4 290.1 291.4 297.4 44.8 0.0 100.3 122.4 54.7 351.4 712.5 870.8 969.0 186.3 468.8

Income from agriculture/ livestock 283.2 85.2 80.6 97.2 15.7 41.0 90.8 67.3 87.3 705.7 156.0 93.8 229.0 - 187.2

Income from livestock 439.5 495.7 217.2 133.0 - - - - - - - - 189.0 46.5 264.1

Income from regular job/ salary/pension 433.4 0.0 198.7 42.4 0.0 204.8 221.5 80.1 160.9 663.3 275.2 691.0 158.4 561.9

Total 69.5 91.6 - 37.5 87.5 - 61.6 66.3 - 47.7 81.9 - 113.0 34.7 49.7

Table: 3.4.1: Variability (CV) in income across households - Non- Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Occupation

Income from wages in agriculture 194.1 64.8 150.3 121.7 45.5 71.0 45.5 41.8 35.3 74.7 134.5 479.8 121.0 92.9 112.0

Income from wages non agriculture 342.7 53.9 112.9 78.2 55.1 67.0 59.5 51.2 43.5 82.8 326.3 193.4 144.0 55.9 124.0

Income from wages in PWP 525.3 111.1 - - 0.0 - 0.0 0.0 0.0 - 0.0 568.0 410.0 0.0 -

Income from wages as migrant workers 500.5 354.7 - 183.7 0.0 - 349.4 85.7 79.7 - 257.3 - 149.0 175.5 229.3

Income from self employed in non farming 295.2 184.6 148.4 222.0 42.4 0.0 71.4 112.9 69.2 440.0 348.4 221.7 - 159.1 327.0

Income from agriculture 472.5 109.4 60.3 78.9 0.0 41.0 106.1 70.7 67.5 703.5 194.3 71.9 223.0 74.0 186.3

Income from livestock 263.0 0.0 147.9 46.7 - - - - - - - - 187.0 - 276.3

Income from regular job/ salary/pension 275.6 0.0 147.9 - 66.7 - 129.9 266.3 20.7 185.9 327.9 120.2 707.0 192.5 455.4

Total 314.9 118.6 - 60.5 58.7 - 74.8 48.2 - 71.8 120.9 - 102.0 44.6 105.4

72

Table 3.5: Household consumption of food items (kg per capita per month) – Participants

S

tate

s

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

greg

ate

Rice 7.47 5.78 1.71 9.20 7.46 2.24 2.17 10.97 10.41 0.67 4.51 4.45 2.61 1.00 10.81 4.83

Wheat 1.27 7.53 5.73 1.80 0.50 8.41 7.45 1.70 1.38 8.35 2.79 5.84 5.14 7.00 1.49 4.36

Other cereals 4.12 0.29 2.00 1.70 1.34 0.65 2.33 0.87 0.00 0.43 3.00 1.00 6.73 2.20 0.17 1.84

Total cereals 12.85 13.60 9.44 12.70 11.70 11.29 11.93 13.54 11.80 9.45 9.39 11.29 14.48 10.20 12.47 11.10

Total pulses 1.14 1.32 1.45 0.40 1.00 1.42 0.70 0.81 0.53 0.63 1.15 3.47 1.64 1.10 0.44 1.12

Sugar 1.29 0.64 0.42 0.40 0.60 1.90 0.54 0.55 0.49 2.04 1.27 0.80 0.90 1.00 0.49 0.86

Edible oils 1.31 0.66 0.50 0.30 0.84 0.61 0.58 0.39 0.54 0.38 0.67 0.83 1.01 0.80 0.52 0.65

Liquid milk 2.79 1.56 3.50 1.20 2.48 3.89 0.91 0.34 1.12 - 2.56 7.80 3.11 3.90 0.93 2.43

Milk products 0.15 0.29 0.04 0.00 0.16 0.12 0.10 0.01 0.02 4.18 1.94 0.10 0.45 0.60 0.07 0.49

Meat and products 0.36 0.07 0.34 0.40 0.68 0.22 0.13 0.20 0.24 - 0.42 0.26 0.32 0.10 0.39 0.26

Fruits 0.47 0.35 - 0.10 1.00 0.26 0.23 0.10 0.33 0.23 0.20 0.84 0.42 0.40 0.12 0.32

Vegetables 2.23 6.82 4.11 2.60 5.50 0.11 5.86 6.12 6.54 2.84 1.15 2.77 3.02 3.80 6.16 3.68

73

Table 3.5.1: Household consumption of food items (kg per capita per month) - Non-Participants

S

tate

s

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

greg

ate

Rice 7.53 4.98 1.37 9.10

5.92 1.97 2.09 11.59 10.54 0.59 4.27 4.91 2.84 0.90 10.74 5.15

Wheat 1.29 6.87 6.70 1.70

0.20 9.00 8.58 2.19 0.91 8.97 2.70 8.87 4.50 5.80 1.52 4.60

Other cereals 3.48 0.07 1.50 1.60

1.00 0.42 1.85 0.68 0.00 0.51 3.48 1.22 4.83 4.00 0.20 1.54

Total cereals 12.31 11.92 9.57 12.50

15.88 11.39 12.52 14.46 11.45 10.07 9.59 15.00 12.13 10.70 12.46 11.62

Total pulses 1.19 1.14 1.50 0.30

0.76 0.67 1.12 0.92 0.46 0.67 1.26 3.22 1.33 1.00 0.45 1.02

Sugar 1.17 0.62 0.80 0.30

0.52 1.75 0.73 0.54 0.46 2.09 1.75 0.79 0.84 1.10 0.49 0.93

Edible oils1 0.75 0.52 0.53 0.30

0.64 0.57 0.62 0.38 0.50 0.42 0.73 0.81 0.91 0.70 0.52 0.56

Liquid milk1 3.71 1.63 5.00 1.10

2.20 4.02 1.00 0.17 0.80 3.92 8.40 3.11 4.10 1.59 2.43

Milk products 0.51 0.04 0.15 0.00

0.12 0.08 0.16 0.01 0.02 4.66 0.80 0.50 0.40 0.40 0.04 0.63

Meat and products 0.33 0.08 0.40 0.40

0.60 0.00 0.20 0.22 0.22 0.55 0.26 0.41 0.10 0.61 0.26

Fruits 0.61 1.80 0.00

1.00 0.51 0.37 0.31 0.39 0.28 0.28 1.77 0.47 0.60 0.17 0.52

Vegetables 2.30 3.90 4.00 2.60

4.00 0.64 6.09 7.93 8.67 3.07 1.12 2.26 3.11 3.60 7.92 4.13

Note: 1-Edible oil and Liquid milk is in Liters

74

Table 3.5.2: Household consumption of food items (kg per capita per month) - NSS (2009-10)

S

tate

s

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

All

In

dia

Rice 5.66 4.27 6.38 9.52 10.67 0.70 2.17 11.18 12.38 0.79 3.25 4.09 1.74 0.24 10.26 6.14

Wheat 1.10 7.66 5.55 0.87 0.32 8.91 8.13 0.88 0.51 8.43 4.25 6.35 4.19 8.65 1.16 4.36

Other

cereals

3.27 0.11 0.30 0.36 0.49 0.20 1.01 0.07 0.00 0.12 2.73 0.80 3.28 2.92 0.01 0.85

Total

cereals

10.03 12.04 12.23 10.76 11.48 9.81 11.30 12.13 12.89 9.35 10.24 11.24 9.21 11.82 11.43 11.35

Total pulses 0.70 0.76 0.56 0.46 0.66 0.62 0.71 0.62 0.51 0.83 0.86 1.25 0.68 0.43 0.39 0.65

Sugar 0.72 0.71 0.32 0.42 0.48 1.45 0.80 0.54 0.48 1.71 1.00 1.17 0.99 1.15 0.43 0.71

Edible oils1 0.64 0.59 0.50 0.55 0.71 0.57 0.59 0.56 0.47 0.82 0.93 0.89 0.99 0.72 0.59 0.64

Liquid

milk1

3.79 4.59 2.67 5.87 3.37 13.40 4.00 0.77 1.55 11.56 3.05 9.51 6.18 9.86 1.39 4.12

Milk

products

0.04 0.01 0.02 0.03 0.06 0.07 0.02 0.02 0.03 0.05 0.02 0.07 0.03 0.08 0.02 0.03

Eggs (no) 2.20 0.63 1.05 2.68 3.91 0.26 0.67 1.18 3.38 0.77 1.37 0.77 0.45 0.21 4.59 1.73

Meat and

products

0.50 0.19 0.14 0.47 0.67 0.08 0.20 0.34 0.99 0.07 0.33 0.20 0.12 0.07 1.10 0.49

Source: Household Consumption of Various Goods and Services in India – NSS 66th Round, Report No 541/(66/1.0/3), Ministry of Statistics and Programme Implementation, Government of India, February 2012.

Note: 1- Edible oil and Liquid milk is in Liters

75

Table 3.6: Monthly consumption expenditure of households (Rs per capita) - Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Rice 101.00

(19.7)

69.62

(17.21)

42.95

(8.37)

146.9

(46.17)

99.47

(24.88)

39.32

(10.62)

28.57

(8.67)

145.55

(41.53)

167.86

(37.75)

13.18

(2.86)

39.33

(11.86)

43.76

(9.3)

47.94

(6.96)

18.60

(3.45)

149.91

(41.79)

69.12

(16.4)

Wheat 14.00

(2.7)

62.85

(15.54)

81.60

(15.9)

24.8

(7.80)

0.86

(0.22)

72.19

(19.5)

71.94

(21.84)

17.37

(4.96)

25.05

(5.63)

62.37

(13.52)

21.52

(6.49)

59.95

(12.74)

85.31

(12.38)

87.50

(16.25)

15.72

(4.38)

47.25

(11.2)

Other

cereals

52 .00

(10.2)

2.46

(0.61)

20.00

(3.9)

14.8

(4.65)

32.2

(8.05)

8.25

(2.23)

22.81

(6.92)

7.71

(2.19)

0.00 9.80

(2.12)

23.85

(7.19)

10.24

(2.18)

85.68

(12.44)

40.10

(7.45)

2.24

(0.62)

22.77

(5.4)

Total

cereals

167.00

(32.6)

134.93

(33.36)

144.55

(28.16)

186.4

(58.61)

132.53

(33.14)

119.77

(32.34)

123.32

(37.44)

170.63

(48.69)

192.21

(43.39)

85.35

(18.51)

84.71

(25.53)

113.96

(24.22)

218.93

(31.78)

146.20

(27.14)

167.87

(46.8)

139.08

(33.1)

Pulses 79 .00

(15.4)

68.67

(16.98)

69.21

(13.48)

21.3

(6.69)

41.25

(10.32)

38.44

(10.38)

32.52

(9.87)

35.2

(10.04)

24.03

(5.4)

18. 90

(4.1)

50.26

(15.15)

23.13

(4.92)

78.75

(11.43)

51.40

(9.54)

24.56

(6.85)

43.79

(10.4)

Sugar 42.00

(8.2)

11.37

(2.81)

5.06

(0.99)

10.6

(3.33)

16.83

(4.21)

59.11

(15.96)

15.64

(4.75)

14.28

(4.07)

12.99

(2.92)

78.97

(17.12)

34.87

(10.51)

15.03

(3.19)

28.85

(4.19)

36.60

(6.8)

12.49

(3.48)

25.37

(6.0)

Cooking oil 47.00

(9.2)

41.48

(10.26)

33.89

(6.6)

17.3

(5.44)

36.77

(9.2)

41.00

(11.07)

28.18

(8.55)

22.84

(6.52)

25.82

(5.81 )

32.35

(7.01)

27.91

(8.41)

27.55

(5.85)

59.60

(8.65)

43.80

(8.13)

32.46

(9.05)

33.90

(8.1)

Spices 20.00

(3.9)

12.97

(3.21)

50.13

(9.77)

6.1

(1.92)

9.56

(2.39)

14.70

(3.97)

9.21

(2.8)

14.1

(4.02)

26.40

(5.94)

50.07

(10.86)

8.44

(2.54)

14.89

(3.16)

36.08

(5.24)

26.80

(4.98)

10.69

(2.98)

20.60

(4.9)

Milk and

products

53.00

(10.38)

37.50

(9.27)

96.00

(18.70)

15.8

(4.97)

34.15

(8.54)

20.57

(5.56)

32.55

(9.88)

9.15

(2.61)

19.66

(4.42)

84.17

(18.25)

24.27

(7.32)

143.36

(30.47)

82.68

(12.0)

119.60

(22.21)

15.45

(4.31)

52.26

(12.50)

Poultry-

meat

44.00

(8.59)

7.42

(1.83)

42.50

(8.28)

35.1

(11.03)

54.47

(13.62)

15.13

(4.09)

16.54

(5.02)

16.48

(4.70)

64.35

(14.47) -

32.19

(9.7)

45.26

(9.62)

26.67

(3.87)

13.00

(2.41)

35.76

(9.97)

29.08

(6.9)

Fruits 15.00

(2.9)

5.90

(1.46) -

3.4

(1.07)

14.63

(3.66)

7.85

(2.12)

8.52

(2.59)

3.26

(0.93)

10.45

(2.35)

11.57

(2.51)

14.42

(4.35)

23.62

(5.02)

10.15

(1.47)

9.10

(1.69)

2.05

(0.57)

8.89

(2.1)

Vegetables 38 .00

(7.4)

74.65

(18.46)

71.92

(14.01)

13.6

(4.27)

50.67

(12.67)

53.70

(14.5)

59.31

(18)

61.88

(17.66)

68.02

(15.3)

89.70

(19.45)

43.61

(13.15)

52.34

(11.12)

72.40

(10.51)

70,10

(13.02)

45.70

(12.74)

55.57

(13.2)

Confectione

ry

2.00

(0.4)

9.54

(2.36)

8.5

(2.67)

8.99

(2.25)

0.00 3.62

(1.10)

2.65

(0.76)

0.00 10.12

(2.19)

11.04

(3.33)

11.40

(2.42)

6.00

(1.11)

11.65

(3.25)

5.03

(1.2)

Any other 5 .00

(0.98) - - - - - - - - - - -

74.80

(10.86)

16.0

(2.97) -

7.07

(1.7)

Total food 512.00

(47.5)

404.43

(78.33)

513.26

(73.27)

318.2

(54.4)

399.85

(68.9)

370.26

(79.6)

329.41

(51.06)

350.47

(50.76)

444.63

(75.51)

461.20

(65.17)

331.71

(54.67)

470.54

(78.05)

688.91

(62.83)

538.6

(66.45)

358.68

(69.73)

420.65

(64.0)

Education 49.00

(8.7)

13.95

(12.47)

32.06

(17.12)

22.2

(8.33)

38.08

(21.1)

0.00 22.76

(7.21)

37.9

(11.15)

17.37

(12.04)

49.01

(19.88)

39.37

(14.31)

10.29

(7.77)

55.40

(13.59)

49.80

(18.32)

25.45

(15.6)

29.61

(12.5)

Clothing 56 .00

(9.89)

18.64

(16.66)

23.50

(12.55)

34.9

(13.1)

39.39

(21.82)

26.77

(28.21)

23.81

(7.54)

61.57

(18.11)

43.96

(30.48)

72.32

(29.34)

24.28

(8.83)

54.79

(41.39)

38.59

(9.47)

23.40

(8.61)

27.01

(16.55)

34.70

(14.6)

Footwear 12.00

(2.12)

10.26

(9.17)

7.03

(3.75)

10.3

(3.87)

11.7

(6.48)

11.42

(12.03)

8.62

(2.73)

9.55

(2.81)

4.81

(3.34)

7.85

(2.85)

26.58

(20.08)

10.03

(2.46)

7.10

(2.61)

8.19

(5.02)

9.17

(3.9)

Fuel 24.00

(4.2)

16.08

(14.38)

56.06

(29.94)

34.0

(12.76)

32.29

(17.89)

0.00 61.4

(19.45)

62.49

(18.38)

58.33

(40.45)

93.17

(37.79)

26.84

(9.76)

8.13

(6.14)

43.67

(10.72)

19.60

(7.21)

27.18

(16.66)

34.85

(14.7)

Other items 425.00

(75.2)

52.93

(47.32)

68.61

(36.64)

165.0

(61.94)

59.03

(32.71)

56.71

(59.76)

199.16

(63.08)

168.53

(49.56)

19.75

(13.69)

32.03

(12.99)

176.71

(64.25)

32.56

(24.60)

259.82

(63.76)

172.00

(63.26)

75.35

(46.18)

128.70

(54.3)

Total Non

food

566 .00

(52.5)

111.86

(21.67)

187.26

(26.73)

266.4

(45.6)

180.49

(31.1)

94.90

(20.40)

315.75

(48.94)

340.04

(49.24)

144.22

(24.49)

246. 53

(34.83)

275.05

(45.33)

132.35

(21.95)

407.51

(37.17)

271.90

(33.53)

163.18

(31.27)

237.03

(36.0)

Total hh

expenditure

1078

(100.0)

516.29

(100)

700.52

(100)

584.6

(100.0)

580.34

(100)

465.16

(100.0)

645.16

(100.0)

690.51

(100.0)

588.85

(100)

707.73

(100)

606.76

(100)

602.89

(100)

1096.42

(100.0)

810.50

(100)

521.86

(100)

657.68

(100.0)

76

Table 3.6.1: Monthly consumption expenditure of households (Rs per capita) - Non-Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Rice 117.00

(20.4)

57.86

(15.5)

34.41

(6.34)

142.7

(47.2)

93.74

(22.79)

34.99

(9.8)

30.45

(7.61)

160.57

(41.76)

169.97

(36.36)

11.80

(2.37)

37.53

(8.71)

43.89

(6.97)

55.16

(7.97)

20.60

(3.36)

152.47

(36.52)

75.52

(16.6)

Wheat 17.00

(3.0)

77.71

(20.85)

95.41

(17.59)

23..5

(7.78)

0.49

(0.12)

75.74

(21.22)

86.42

(21.61)

21.78

(5.66)

16.42

(3.51)

72.84

(14.64)

23.13

(5.37)

74.15

(11.78)

67.56

(9.76)

90.30

(14.71)

16.57

(3.97)

49.76

(10.9)

Other cereals 45.00

(7.8)

0.67

(0.18)

15.00

(2.77)

13.6

(4.5)

27.69

(6.73)

6.21

(1.74)

17.46

(4.37)

5.58

(1.45)

0.00 11.48

(2.3)

27.45

(6.37)

11.74

(1.87)

59.87

(8.65)

39.20

(6.39)

2.62

(0.63)

17.52

(3.8)

Total cereals 179.00

(3112)

136.26

(36.56)

144.82

(26.7)

179.8

(59.5)

121.92

(29.64)

116.95

(32.77)

134.33

(33.59)

187.93

(48.88)

186.39

(39.87)

96.12

(19.32)

88.11

(20.46)

129.78

(20.62)

182.59

(26.39)

150.20

(24.47)

171.66

(41.12)

142.81

(31.4)

Pulses 85.00

(14.8)

57.34

(15.4)

71.59

(13.20)

19.3

(6.39)

33.62

(8.17)

34.79

(9.75)

52.56

(13.14)

36.5

(9.49)

20.92

(4.48)

20.10

(4.04)

64.70

(15.02)

19.21

(3.05)

74.69

(10.8)

57.20

(9.32)

25.57

(6.12)

43.16

(9.5)

Sugar 41.00

(7.1)

11.94

(3.20)

9.64

(1.78)

10.2

(3.38)

15.58

(3.79)

56.73

(15.89)

18.61

(4.65)

13.41

(3.49)

12.04

(2.58)

80.89

(16.26)

38.43

(8.92)

13.27

(2.11)

32.88

(4.75)

45.50

(7.41)

12.66

(3.03)

28.07

(6.2)

Cooking oil 49.00

(8.5)

36.56

(9.81)

35.58

(6.56)

15.9

(5.26)

31.87

(7.75)

41.34

(11.58)

32.77

(8.19)

23.28

(6.05)

23.63

(5.05)

33.67

(6.77)

36.13

(8.39)

44.98

(7.15)

61.08

(8.83)

47.00

(7.66)

34.09

(8.17)

34.77

(7.6)

Spices 23.00

(3.9)

11.16

(2.99)

57.84

(10.66)

5.6

(1.85)

10.89

(2.65)

13.54

(3.79)

12.92

(3.23)

17.18

(4.47)

24.58

(5.26)

48.13

(9.68)

8.92

(2.07)

11.22

(1.78)

35.19

(5.09)

31.50

(5.13)

14.86

(3.56)

22.90

(5.0)

Milk and products 78.00

(13.5)

39.63

(10.63)

103.00

(18.99)

14.2

(4.7)

35.18

(8.55)

15.43

(4.32)

39.09

(9.77)

4.63

(1.20)

15.37

(3.29)

93.70

(18.84)

58.46

(13.58)

235.74

(37.45)

97.12

(14.04)

123.70

(20.15)

25.98

(6.23)

62.27

(13.7)

Poultry- meat 43.00

(7.5)

3.29

(0.88)

50.00

(9.22)

35.7

(11.81)

42.43

(10.32)

0.00 24.74

(6.19)

24.25

(6.3)

81.90

(17.52)

41.66

(9.67)

39.39

(6.26)

34.10

(4.93)

13.30

(2.17)

61.95

(14.84)

29.99

(6.6)

Fruits 21.00

(3.7)

25.24

(6.77)

0.0

(0.0)

15.0

(3.65)

14.03

(3.93)

12.86

(3.22)

4.44

(1.15)

12.48

(2.67)

14.12

(2.84)

22.14

(5.14)

47.52

(7.55)

12.35

(1.79)

17.40

(2.83)

3.81

(0.91)

13.59

(3.0)

Vegetables 49.00

(8.5)

44.68

(11.99)

70.00

(12.90)

13.2

(4.37)

40.65

(9.88)

64.12

(17.96)

67.76

(16.94)

69.09

(17.97)

90.17

(19.29)

95.35

(19.17)

48.35

(11.23)

53.17

(8.45)

78.89

(11.4)

77.70

(12.66)

51.19

(12.26)

61.96

(13.6)

Confectionery 3.00

(0.5)

6.62

(1.78) -

8.3

(2.75)

8.56

(2.08)

0.00 4.26

(1.07)

3.77

(0.98)

0.00 15.33

(3.08)

23.74

(5.51)

35.13

(5.58) -

9.00

(1.47)

15.71

(3.76)

8.06

(1.8)

Any other 4.00

(0.7) - - -

55.57

(13.51) - - - - - - -

82.96

(11.99)

41.4

(6.74) -

10.63

(2.4)

Total food 575.00

(43.07)

372.72

(79.8)

542.47

(72.28)

302.2

(53.0)

411.27

(77.28)

356.93

(71.86)

399.90

(54.43)

384.48

(50.43)

467.48

(86.74)

497.41

(61.87)

430.64

(51.19)

629.41

(77.49)

691.86

(70.64)

613.90

(69.2)

417.48

(65.87)

455.46

(62.7)

Education 87.00

(11.5)

13.16

(13.93)

36.00

(17.3)

17.1

(6.39)

35.43

(29.3)

0.00 26.38

(7.88)

41.55

(10.99)

11.85

(2.20)

52.13

(17.01)

54.00

(13.15)

19.96

(10.92)

36.75

(12.78)

24.40

(8.93)

20.31

(39.39)

32.33

(11.9)

Clothing 71.00

(9.3)

19.05

(20.16)

24.00

(11.54)

39.4

(14.7)

32.87

(27.18)

39.55

(28.29)

27.34

(8.17)

70.14

(18.56)

14.42

(2.68)

103.35

(33.72)

36.64

(8.92)

84.09

(46.0)

39.32

(13.67)

30.90

(11.3)

37.73

(17.44)

46.60

(17.2)

Footwear 14.00

(1.8)

11.51

(12.18)

6.25

(3.0)

12.6

(4.71)

10.63

(8.79)

15.84

(11.33)

13.04

(3.89)

12.12

(3.21)

3.97

(0.74)

9.60

(2.34)

34.72

(19.00)

10.29

(3.58)

9.40

(3.44)

11.41

(5.28)

10.67

(3.9)

Fuel 27.00

(3.6)

13.58

(14.37)

57.80

(27.78)

34.0

(12.7)

41.99

(34.73)

0.00 77.21

(23.06)

68.14

(18.03)

33.76

(6.26)

102.89

(33.57)

53.38

(13.00)

8.80

(4.81)

42.42

(14.75)

20.56

(7.52)

34.56

(15.98)

43.44

(16.0)

Other items 561.0

(73.9)

37.19

(39.4)

84.00

(40.37)

164.6

(61.49) -

84.40

(60.38)

190.84

(57.0)

185.91

(49.20)

7.45

(1.38)

48.12

(15.7)

256.98

(62.59)

35.22

(19.27)

158.83

(55.22)

188.00

(68.8)

112.28

(51.91)

138.19

(50.9)

Total Non food 760.00

(56.9)

94.50

(20.23)

208.05

(27.72)

267.7

(46.97)

120.92

(22.72)

139.79

(28.14)

334.81

(45.57)

377.86

(49.57

71.45

(13.26)

306.49

(38.13)

410.60

(48.81)

182.79

(22.51)

287.61

(29.36)

273.26

(30.80)

216.29

(34.13)

271.22

(37.3)

Total hh

expenditure

1335.00

(100.0)

467.22

(100)

750.52

(100)'

569.90

(100.0)

532.19

(100)

496.72

(100.0)

734.71

(100.0)

762.34

(100.0)

538.93

(100)

803.90

(100.0)

841.24

(100)

812.20

(100)

979.46

(100.0)

887.16

(100.0)

633.77

(100)

726.68

(100.0)

77

Table 3.6.2: Absolute and percentage break-up of MPCE by item group in 2009-10: all-

India, rural and urban – NSS 66th

Round (2009-10)

item group Monthly per

capita exp. (Rs.)

Percentage to total

MPCE

Rural urban rural urban

Cereals & cereal substitutes 145 162 13.8 8.2

Pulses & their products* 35 49 3.3 2.5

Milk & milk products 81 137 7.6 6.9

Edible oil 39 53 3.7 2.7

Egg, fish & meat 50 72 4.7 3.6

Vegetables 87 112 8.3 5.7

Fruits 26 63 2.4 3.2

Sugar, salt and spices 60 73 5.7 3.7

Beverages, refreshments & processed 78 159 7.4 8

Food total 600 881 57 44.4

Pan, tobacco & intoxicants 31 30 3 1.5

Fuel and light 85 138 8 6.9

Clothing & footwear$ 65 115 6.2 5.8

Education 38 161 3.6 8.1

Medical 57 99 5.4 5

Conveyance 36 112 3.5 5.6

Consumer services excl. conveyance 44 124 4.2 6.3

Misc. goods, entertainment 53 113 5 5.7

Rent 5 115 0.5 5.8

Taxes and cesses 2 16 0.2 0.8

Durable goods 36 81 3.5 4.1

Non-food total 453 1104 43 55.6

All items 1054 1984 100 100

Source: NSS Report No. 538: Level and Pattern of Consumer Expenditure, Ministry of Statistics and Programme

Implementation, Government of India, February 2012.

78

Table 3.7: Variability in Consumption and Income – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Description

Average household income

during the reference year (Rs.) 57234 46851 40882 32425 43244 91578 56239 55547 48236 36079 37778 41762 87867 75821 50116 37343

Average household consumption during the reference year (Rs.) 68518 24653 42882 15001 44605 30914 32748 40601 42127 21007 33864 37352 30844 6054 53502 28766

Coefficient of variation in income

across households 69.51 91.63 - 37.3 - 59.64 75.88 61.58 66.26 80.29 47.73 81.92 47.0 113 65.5 55.04

Coefficient of variation in

consumption across households 73.76 40.02 - 38.4 - 27.98 40.35 30.36 46.11 38.29 53.02 40.97 34.0 39.0 55.7 34.78

Gini coefficient of income 0.35 0.34 - 0.19 0.28 0.32 0.32 0.10 0.71 29.19 0.25 0.37 0.43 0.47 0.34 0.50

Gini coefficient of consumption 0.36 0.22 - 0.20 0.12 0.51 0.22 0.93 0.25 16.25 0.23 0.32 0.33 0.36 0.34 0.50

Table 3.7.1: Variability in Consumption and Income (Non-Participants)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Description

Average household income during

the reference year (Rs.) 93144 54595 41610 35508 48305 335362 42661 62832 55452 29456 42976 67873 170440 82886 58319 49963

Average household consumption during the

reference year (Rs.) 78178 25471 42804 15533 41059 88902 28376 38381 40284 20207 39216 51685 44833 5210 58725 32494

Coefficient of variation in income across households 314.9 118.6 - 40.4 - 59.49 51.68 74.77 48.15 71.78 71.82 120.9 102 102 80.7 104.6

Coefficient of variation in consumption

across households 91.8 24.4 - 32.8 - 21.62 28.04 42.57 39.71 30.71 51.94 48.76 33.0 24.0 70.6 67.41

Gini coefficient of income 0.70 0.38 - 0.21 0.34 0.33 0.29 0.11 0.74 - 0.34 0.52 0.92 0.47 0.43 0.48

Gini coefficient of consumption 0.43 0.14 - 0.18 0.05 0.50 0.15 0.96 0.22 - 0.20 0.37 0.27 0.27 0.35 0.49

79

Table 3.8: Determinants of participation in NREGA (Logit function) (Dependent variable: Dummy HH participation in NREGA)

States

Employment

other than

NREGA

HH Income

other than

NREGA

HH

Size

Land

ownership

Dummy

Value of

HH Asset

Dummy

AAY

card

holding

Dummy

BPL card

holding

Dummy

SC

Dummy

ST

Dummy

OBC

Dummy

General Constant

No of

obser-

vation

Pseudo

R²

Log

Likeli-

hood

Karnataka Coffiencient 0.0004 -0.0000 0.216** -0.596*** -0.00*** 0.687 0.80*** 0.455 - -0.037 0.422 -0.081 254 0.10 -118.8

t-value 0.39 -0.95 2.2 -1.63 -1.91 1.45 1.65 0.7 - -0.06 0.66 -0.09 - - -

Uttar

Pradesh

Coffiencient - -0.000004 -.27*** 1.056*** -0.00001* -0.75 0.115 0.456 30.7 1.137 - 3.54 - 0.383 -

t-value - -1.09 -2.07 2.09 -5.306 -1.398 0.212 0.53 0.00 1.29 - 3.41 - -

Sikkim Coffiencient -0.0026* -0.000021 0.013 0.78 -0.000005 - 2.017* 2.70 3.222* 2.414 - -1.08 200 0.308 -69.28

t-value -2.15 -1.24 0.06 1.13 -1.71 - 3.86 1.64 2.47 1.91 - -0.69

Andhra

Pradesh

Coffiencient 0.002** - 0.675* 0.298 - - 0.523 1.607** 2.476* 1.095*** - -1.409 250 0.25 179.6

t-value 2.0 - 4.17 0.72 - - 1.09 2.44 3.23 1.96 - -1.65 - - -

Kerala Coffiencient - 0.0002* 0.311 - - - - - - - - - 0.369 -

t-value - 25.2 2.1 - - - - - - - - - - -

Haryana Coffiencient -0.002*** - 0.326* 0.00 - - 1.04*** 0.228 - - - -0.853 250 0.60 234.6

Significant - - - - - -

- - - - - - -

Madhya

Pradesh

Coffiencient -0.0019** -0.00** 0.305** 0.00 -0.00** 0.4229 0.337 1.465 2.099 1.347 0.148 -0.096 245 0.179 -101.75

t-value -2.36 -2.00 3.11 0.95 -2.44 0.58 0.83 1.13 1.57 1.09 0.11 -0.07 - - -

Chhattisgarh Coffiencient -0.009*** -0.00002** 0.26***

-0.007E-

08 -1.41E-06 0.5213 0.385 20.6*** 20.5*** 19.9*** - -0.00 240 0.134 -104.03

t-value -3.74 -1.96 2.57 -0.06 -0.06 0.71 0.62 15.64 16.27 16.04 - -12.63 - - -

Assam Coffiencient 0.086 -0.00 -0.049 0.063 -0.00*** - -0.013 0.134 0.045 -0.051 - -4.62* 250 0.075 -125.1

t-value 1.23 -0.381 -0.985 0.476 -1.602 - -0.08 0.797 0.206 -0.294 - -14.07 - - -

Punjab Coffiencient - -2.56E-05* 0.27* - -1.83E-05* 0.1 - -0.49 - -0.39 - 1.77 - 0.1 -170.21

Std. Error - -6.79E-06 0.13 - -4.59E-06 0.31 - -0.83 - -0.94 - 1.02 - - -

Maharashtra Coffiencient - -0.00004* 0.272 - - - - - 1.699 - - - - 0.2049

t-value - -4.04 2.18 - - - - - 2.27 - - - - - -

Himachal

Pradesh

Coffiencient 0.002*** -7.20E-06

**

-

0.19*** 2.18E-06 -3.00E-06 0.325 -0.027 -0.074 - 0.583 -0.252 2.87* 250 0.127 216.22

t-value 1.848 -2.1 -1.72 1.56 -0.965 0.455 -0.069 -0.136 - 0.855 -0.43 3.72

West

Bengal

Coffiencient -0.00073 -0.000008 0.293* 0.423 -0.000004

* 0.393 0.155 -0.108 -1.6* -0.487 - 1.33* 250 0.168 -104.09

t-value -1.04 -0.93 2.03 1.04 -3.61 0.44 0.41 -0.26 -2.92 -0.57 - 2.09 - - -

80

Table 3.9: Determinants of participation in NREGA (Logit function)

(Dependent variable: Dummy HH Member participation in NREGA)

States

Ka

rn

ata

ka

Sik

kim

Pu

nja

b

Ma

hara

shtr

a

West

Ben

gal

Age 0.036* 0.062* 0.0019 0.043* -0.008

Education -0.193** 0.182 0.09 -0.154* -0.070*

HH Size -0.133* -0.370* - - -0.036

Dummy Sex 0.251*** 0.58* 0.90* - 0.077

Dummy AAY card holding 0.527** - - - 0.542

Dummy BPL card holding 0.348 0.208 - - 0.127

Dummy SC -0.322*** 1.18 - 0.684* 0.429*

Dummy ST 0.083 1.25 - 1.143* -1.066*

Dummy OBC -0.291 1.001 - 0.829* 0.345

Marital status - - 1.37* -

Constant -0.930** - -2.63* - 1.99

No of observation 1024 615 - - 737

Log Likelihood -584.8 307.8 -418.5 - -351.17

Pseudo R2 0.12 0.14 0.08 0.128 0.035

81

Table 3.10: Determinants of participation in NREGA (OLS) (Dependent variable: No. of days per HH worked in NREGA)

States

Ka

rn

ata

ka

Sik

kim

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Employment

other than NREGA

-0.020** -0.0004* 0.022 -0.00179 -0.095* -1.791 -0.0033 -0.0117 0.0137 0.021***

HH Income

other than

NREGA

0.0000 -0.000003 0.0000 0.0001*** -0.00014 -0.0002* 0.0000 0.000044 -0.000024 -0.0003***

HH Size 0.414 0.0114 3.815 -0.393 2.87* 2.18** 0.837 2.12*** 1.00 -0.112

Dummy AAY card holding

8.505*** -10.95*** 13.25 - 11.003* -9.092 -7.82 5.795

Dummy BPL card holding

8.887*** 0.364* 33.35* -2.057 10.69 -4.112 1.318 10.68** 2.39 1.803

Dummy SC 0.805 0.430* -60.78*** 16.45** 33.07** 4.545 2.132 20.32 -2.19 -7.356

Dummy ST 2.989 0.460* -1.175 22.67** 25.63*** 13.057* -5.080 28.31 2.21 -11.51

Dummy OBC -5.844 0.386* -62.7*** 19.53** 24.06*** 7.073*** 2.127 16.34 -6.95 -11.92

Wage rate in NREGA

0.406* - 0.131 0.056 -0.998* - 0.289* -0.027 0.884* -

Value of Land

Owned

-0.0000 0.094 -1.37E-05 -8.90E-07 3.15E-06 1.791*** -0.000014* -0.00001*** 0.000004 5.796

Constant 1.806 0.271 81.81 54.17 109.84 43.135* 128.0* 33.21 2.198 47.41

No of observation 254 200 200 195 192 200 200 250 250 199

F* 10.64* 10.71 2.537 0.077 - 2.35 3.57 2.236 24.87 3.23

R² 0.28 0.337 0.107 0.036 0.205 0.1002 0.228 0.0473 0.489 0.146

82

Chapter 4

Work Profile under MGNREGA, Wage Structure and Migration Issues

4.1 Work profile under MGNREGA

Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is being

implemented in India since 2006. The basic objective of the Act is to ensure livelihood and food

security by providing unskilled work to people through creation of sustainable assets. Under the

provisions of the Act, the State has to ensure enhancement of livelihood security to the

households in rural areas by providing at least one hundred days of guaranteed wage

employment to every household whose adult members volunteer to do unskilled work. In-built

with various transparency and accountability measures and provisions for social audits this Act

for the first time brings the role of the state as provider of livelihood.

In Chapter 2, we presented functioning of MGNREGA in different states based on the secondary

data. We observed that on average, at the all India, a total number of 45 person days per family

employment has been provided since the inception of the MGNREGA programme. To further

probe the various aspects of functioning of the MGNREGA, a primary field survey was carried

out in five districts each in 16 states with the participation of all AERCs in this study. The details

of the selected sample and households were discussed in Chapter 3. This chapter presents various

details of working of the MGNREGA in the selected states. Table 4.1 presents the work profile

under MGNREGA in the 16 selected states. According to our survey data, on average, less than

two members (1.7) per family were employed under MGNREGA. Among the selected states, the

average exceeded 2 members per family working in MGNREGA in Sikkim, Gujarat,

Chhattisgarh and Andhra Pradesh (Figure 4.1). It was between 1.5 and 2 members in Karnataka,

Haryana, Madhya Pradesh, Maharashtra and West Bengal. The states that employed less than 1.5

members per family were Uttar Pradesh, Bihar, Kerala, Assam, Punjab, Himachal Pradesh and

Rajasthan. The highest numbers of members employed under MGNREGA among the selected

households was found 2.8 members in Sikkim and lowest, 1.07 in Kerala.

83

Out of 1.68 members employed under MGNREGA at the aggregate, 0.98 members belonged to

male households and 0.70 members belonged to female households. Only in Gujarat and

Rajasthan, the numbers of female member per household working in MGNREGA exceeded that

of male and in Sikkim and Maharashtra their percentage was same. Against the average of 1.68

aggregate members per family, the average was 1.47 for the SCs, 1.67 for STs and 1.53 for the

OBCs. The SC and ST households’ average was highest 2.63 and 2.53 members in Gujarat and

lowest 0.22 and 0.19 members in Bihar, respectively.

4.2 How successful has been MGNREGA in providing 100 days employment

Under the MGNREGA Act, every family is guaranteed for 100 days employment. In Chapter 2,

we observed that only 2.43 crore families were provided 100 days employment in the country as

a whole during the whole period of MGNREGA under operation. Table 4.1 presents number of

days of work obtained by the selected households in different states. On an average, 68 days per

household employment was generated at the aggregate during the reference period in selected

states among our selected participants. Thus, number of days of employment generated among

our selected households was above the national average of 45 days of employment since the

84

inception of the programme and 54 days of employment generated at the all India during the year

2009-10 which coincides with our survey period.

Figure 4.2 shows the numbers of days of employment generated in different states among our

selected participants. The states that topped in employment generation included Maharashtra

(100 days), Haryana (94 days), Himachal Pradesh (92 days) and Rajasthan, Sikkim and Gujarat

(slightly above 80 days). The states that were slightly above or below the national average were

Madhya Pradesh, Karnataka, Kerala and Uttar Pradesh (between 80 to 60 days). The states that

lied at the bottom were Bihar (32 days), Andhra Pradesh (43 days) and Assam (48 days).

Among all households employed in MGNREGA, those who belonged to Scheduled Caste (SC)

and Scheduled Tribes (ST), observed 60 and 68 days of respective employment at the aggregate.

Maharashtra, Karnataka, Himachal Pradesh and Gujarat had highest employment among the SCs

and STs While Assam, Bihar, Andhra Pradesh, Chhattisgarh and Sikkim had the lowest

employment among these communities. Looking at the ratio of employment among the male and

female workers, numbers of days of employment was shared by male (37 days) and female (30

days) with a per cent share of 56 for male and 44 for female. Our sample percentage of male and

85

female work days compares well with the national average of 53 per cent for male and 47 per

cent for female employed in MGNREGA as shown in Chapter 2.

The households completing 100 days employment in the selected states is shown in Table 4.1

and Figure 4.3. Out of 16 states for which analysis is done only in 10 states information about

households completing 100 days of employment was available. Among these ten states, the

percentage of households who completed 100 days, only in Himachal Pradesh their percentage

was exceptionally high (85 per cent). In Haryana and Rajasthan, 48.5 and 44.5 per cent

households completed 100 days under MGNREGA. In Karnataka and Sikkim around 1/4th

of the

participant households completed 100 days of employment. In Bihar, Assam, Gujarat and West

Bengal only less than 5 per cent households completed 100 days and in Uttar Pradesh around 10

per cent households completed 100 days. At the aggregate, only 1/4th

of the selected participants

in these 10 states completed 100 days and thus at the aggregate only 68 days of employment was

generated under MGNREGA in the selected 16 states. In other words, MGNREGA was not quite

successful in providing social security to the households as households had to depend on other

activities for earning their livelihood as MGNREGA provided only 18 per cent share of the total

employment to the selected households (see Chapter 3).

86

Looking at the wage rate on which employment was provided, average wage rate at the

aggregate was recorded at 100 and it was not particularly different among male and female

(Table 4.1 and Figure 4.4). The highest wage was recorded in Haryana ( 150), followed by

Kerala ( 125), Punjab ( 123) and Himachal ( 110). Among the selected states lowest wage

rate was paid in Rajasthan ( 80), Chhattisgarh ( 83) West Bengal ( 84) and Karnataka ( 86).

However, in most of the states actual wage rate obtained under MGNREGA was below the

stipulated minimum wage rate fixed by the states under the Minimum Wages Act 1948. The

states that were found paying equal to stipulated minimum wages were Uttar Pradesh, Kerala,

Chhattisgarh, Himachal Pradesh and West Bengal. The other states paid less than the stipulated

minimum wages. The difference between the actual payment and minimum stipulated wages was

specifically high in Karnataka ( 33), Maharashtra ( 22), Rajasthan and Assam ( 21), Madhya

Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat and Haryana ( 12) and Bihar

( 10)3. The wage difference among male and female and among various other socio-economic

communities was, however, not observed as is clear from Table 4.1. Last but not the least, the

average distance of work place form the residence or village of the households was less than 2

kilometers in all the states with few exceptions. In Gujarat, Rajasthan, Maharashtra, Haryana and

Uttar Pradesh work place was slightly more than two kilometers away from the residence/village

of the selected households. In other states, distance was less than 2 kilometers.

3 Source: Ministry of Labour New Delhi.

87

4.3 Major employment activities, assets created and their durability

There were mainly 9 major activities under which work was provided in MGNREGA. These

were rural connectivity, flood control and protection, water conservation and water harvesting,

drought proofing, micro irrigation, provision of irrigation to Panchayat land, renovation of

traditional water bodies, land development and any other work approved by the Ministry of

Rural Development (MRD). Table 4.2 shows activities in which employment was provided

under MGNREGA in the selected states. Among the selected households at the aggregate, the

highest work under MGNREGA was concentrated on rural connectivity which shared around 40

per cent of the total employment followed by water conservation and water harvesting which

shared 17 per cent of employment under MGNREGA (Figure 4.5). Land development (12 per

cent), renovation of traditional water bodies (11 per cent), flood control and protection (8 per

cent) and micro irrigation (5 per cent) were the other major activities of employment under

MGNREGA. Drought proofing and other irrigation works contributed less than 2 per cent

employment. The observations at the field level match well with the information compiled from

MGNREGA website presented in Chapter 2 according to which the highest employment was

recorded for water conservation, followed by rural connectivity, provision of irrigation, land

development, drought proofing, renovation of traditional water bodies and micro irrigation in the

descending order.

Box 4.1: Work participation in MGNREGA in Karnataka

1. Work participation in MGNREGA reveals that the household belonging to scheduled

castes were invariably over represented compared to their share in total households, while

participation of upper castes was less than their share in the population in all the selected

districts.

2. Marginal and small farmers among the land holding groups were observed also working

in the MGNREGA whereas large holding size did not have any representation in

MGNREGA.

3. Job cards were not issued to several families. In some cases, applications were pending

while in other cases people did not know how to apply. Provision should be made for oral

application as well for those who are illiterate.

4. Those with job cards did not know what next is to be done to obtain employment. As a

result most people with job cards did not apply for work and did not get any employment,

neither had they got any unemployment allowance as they did not know that they had a

right to unemployment allowance if not given employment.

5. It was observed that the participation rate of women was invariably equal and sometime

higher than men across all the social groups, occupational groups, farm size groups and

economic groups.

88

Among the selected states, rural connectivity and water conservation were the main activities in

Karnataka, Uttar Pradesh, Bihar, Kerala, Madhya Pradesh, Assam, Himachal Pradesh, Gujarat

and Rajasthan. Land development was the main activity in Haryana and Andhra Pradesh while

renovation of traditional water bodies was the main activity in Chhattisgarh and Punjab. The

other major activities included flood control and protection in Sikkim, Himachal Pradesh and

Gujarat; drought proofing in Karnataka and Rajasthan; micro irrigation in Bihar, Andhra Pradesh

and Rajasthan. Thus, the projects undertaken by the Panchayats under MGNREGA were based

on the local requirements that shape up very well with the basic objective of the MGNREGA

programme.

On the question of how was the quality of the assets created through MGNREGA work, a little

less than half of the households indicated that the assets created were very good while another

half of them indicated that assets created were of the good quality. Only less than 3 per cent

households pointed out that the assets created were bad or worst in quality. A clear majority of

the households indicating good quality assets created through MGNREGA programme was

across the board in all the states without any exception. The question of quality and desirability

89

of the assets created and work undertaken will be further discussed and verified in the next

chapters.

As per the provisions under the Employment Act, after registration if a household is not provided

employment, he or she is entitled for unemployment allowance. In our above discussion we have

seen that only 25 per cent of the selected households were provided hundred days employment

under MGNREGA. We enquired the selected households whether after registration if they did

not get employment did they receive any unemployment allowance, households indicated that

they did not receive any such allowance (Table 4.2) except in Maharashtra and West Bengal

where households received only a poultry amount as unemployment allowance.

4.4 Migration issues under MGNREGA

One of the main objectives of MGNREGA Programme was to provide employment to wage

earners and landless unskilled labourers within the periphery of the village so as to prevent their

mass exodus towards cities and towns. In our primary survey we tried to find out the extent of

migration among the households after implementation of MGNREGA. Among our selected

participants how many members migrated from the village because of not getting work under

MGNREGA even after registration? Table 4.3 presents the statistics whereby it is seen that

around 0.20 members per family (with average size of 4.7 members) migrated because of not

getting work under MGNREGA. Out of the selected states, the numbers of per family members

migrated because of not getting work averaged at 0.54 in Assam, 0.44 in Rajasthan, 0.31 in

Madhya Pradesh and Maharashtra each, 0.20 in Andhra Pradesh, Chhattisgarh and Himachal

Pradesh, each and less than 0.1 members in rest of the selected states. Thus, incidences of

villagers’ migration in search of work despite having been registered for MGNREGA were still

recorded in the surveyed villages. Was there any incidence of members returning back to village

because of work now being available within the village after implementation of MGNREGA?

The statistics in the table reveals that there were some such incidences observed in the villages

surveyed. Around 0.12 members per family among the participant households returned back to

the village to work under MGNREGA at the aggregate who hitherto were working elsewhere

before the implementation of this Programme. The members retuning back to work under

MGNREGA was highest in the state of Bihar where around 0.65 members per family returned

90

back to work under MGNREGA after the implementation of the Act. The high incidence of

migrated unskilled workers returning back to work in MGNREGA in Bihar supplement the

increasing shortage of agriculture labour in Punjab and Haryana who hitherto were doing wage

work in agriculture in these two states. Among other states, the incidence was recorded in

Andhra Pradesh, Rajasthan, Madhya Pradesh and Maharashtra where, on average, 0.1 to 0.2

members per family returned back to work in MGNREGA after implementation of the Act.

Punjab, Haryana and Assam were the only states where no such reverse migration incidences

were recorded. On the overall, it is difficult to say whether the MGNREGA programme has been

successful in cutting down the incidences of labour migration from villages in search of job.

Another related question is how the MGNREGA programme has affected the labour supply for

the agricultural sector. In the next two chapters, we will further elaborate the issue of migration

based on qualitative information obtained from the households surveyed as well as the group

discussion held in the surveyed villages.

To a further question to the household members who returned back to work under MGNREGA,

where were they earlier working before returning back, majority of them replied that they were

working in the same state in the nearby town or nearby district headquarters. About the activity

in which they were earlier working, an absolute 2/3rd

majority replied that they were working in

construction, manufacturing and mining and rest 1/3rd

were working in the agricultural and other

activities. A majority of the members who migrated to work under MGNREGA came back to the

village either in the previous year of the reference period or a year before. The majority of the

households who returned back to work in MGNREGA pointed out that they were now better off

compared to earlier working as a migrant labourer.

4.5 Wage differentials in different activities

As we stated earlier, the wage rate received by the households under MGNREGA averaged

around 100 and the wage rate differences across male and female were not observed.

Comparing wages among different activities for male, wage rate averaged at 100 in agriculture

compared to 127 in non agriculture. The wage obtained by the migrant male workers averaged

at 133 while wage rate was recorded at 112 for those who were working in public work

programmes other than MGNREGA where wages were sometime paid partly in cash and partly

91

in kind. Comparing wage rates across gender, male workers obtained slightly higher wage rate

compared to female workers in all activities except the wage rate in MGNREGA where male and

female wage rate was almost similar. Among different states, wages were comparatively higher

in richer states like Kerala, Haryana, Andhra Pradesh and Punjab and lower in poor states like

Madhya Pradesh, Chhattisgarh, Uttar Pradesh and Bihar. However, wages were observed

comparatively low in well off states like Maharashtra, Gujarat, Karnataka and Assam. The least

variation in wages was found in the case of MGNREGA. Last but not the least, although

MGNREGA wage rates were less than the stipulated minimum wage rate in many states but it

was not less than the prevailing wage rate for the unskilled labour in agriculture and other

activities. The wage rate earned by the migrant workers was comparatively higher than that

obtained by the people working in MGNREGA in almost all the states. That also explains why

some migration incidences were recorded whereby some people preferred to migrate to the

nearby town or city rather than working under MGNREGA in the village. Another important

observation was that the prevalence of wage rate in MGNREGA was much more symmetric

compared to all other activities.

4.6 Summary of the chapter

This chapter presents functioning of the MGNREGA in the selected states. According to our

survey data, on average, less than two members (1.7) per family were employed under

MGNREGA. Against the average of 1.68 aggregate members per family, the average was 1.47

for the SCs, 1.67 for STs and 1.53 for the OBCs. On an average, 68 days per household

employment was generated among our selected participants. Looking at the ratio of employment

among the male and female workers, numbers of days of employment was shared by male (37

days) and female (30 days) with a per cent share of 56 for male and 44 for female. Out of 16

states for which analysis is done only in 10 states information about households completing 100

days of employment was available. At the aggregate, only 1/4th

of the selected participants in

these 10 states completed 100 days. Looking at the wage rate on which employment was

provided, average wage rate at the aggregate was recorded at 100 and it was not particularly

different among male and female. The difference between the actual payment and minimum

stipulated wages was specifically high in Karnataka ( 33), Maharashtra ( 22), Rajasthan and

Assam ( 21), Madhya Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat and Haryana

92

( 12) and Bihar ( 10). Last but not the least, the average distance of work place form the

residence or village of the households was less than 2 kilometers in all the states with few

exceptions.

Among the surveyed households, the highest work under MGNREGA was concentrated on rural

connectivity which shared around 40 per cent of the total employment followed by water

conservation and water harvesting which shared 17 per cent of employment under MGNREGA.

Land development (12 per cent), renovation of traditional water bodies (11 per cent), flood

control and protection (8 per cent) and micro irrigation (5 per cent) were the other major

activities of employment under MGNREGA. Only less than 3 per cent households pointed out

that the assets created were bad or worst in quality. Households who did not get employment

after registration did not receive any unemployment allowance except in Maharashtra and West

Bengal where households received only a poultry amount as unemployment allowance. On the

issue of migration, the incidences of households migrating from village to cities were recorded

even after registration in MGNREGA and after not getting sufficient work. At the same time,

some households were retuning back to work in MGNREGA and hence it is difficult to say

whether the MGNREGA programme has been successful in cutting down the incidences of

labour migration from villages in search of jobs. The majority of the households who returned

back to work in MGNREGA pointed out that they were now better off compared to earlier

working as a migrant labourer.

93

Table 4.1: Work profile under MGNREGA (Reference period- Jan-Dec 2009)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Characteristics Aggregate

No of members

per hh employed

during the year

Aggregate 1.81 1.42 1.26 2.80 2.01 1.07 1.73 1.80 2.21 1.25 1.10 1.88 1.12 2.31 1.41 1.74 1.68

SC 1.74 1.49 0.22 1.60 2.42 1.00 1.66 1.71 2.08 0.46 1.11 1.51 1.03 2.63 0.95 1.89 1.47

ST 2.24 1.50 0.19 3.00 1.73 1.00 - 2.02 2.31 0.08 - 2.27 1.41 2.53 1.46 1.62 1.67

OBC 1.72 1.38 - 2.60 1.84 1.07 1.74 1.72 2.10 0.38 1.00 1.75 1.17 2.11 0.95 1.44 1.53

General 1.84 1.14 - 0.50 1.97 1.30 1.75 1.20 2.75 0.33 1.00 1.50 1.06 1.33 1.43 1.65 1.38

Men 1.02 0.97 - 1.40 1.09 - 1.11 - - 0.81 0.83 0.94 - 0.99 0.60 0.98 0.98

Women 0.78 0.45 - 1.40 0.92 - 0.62 - - 0.45 0.27 0.94 - 1.32 0.81 0.76 0.70

No of days per

hh employed

during

the year

Aggregate 76.00 61.33 31.79 81.20 43.10 63.29 94.20 78.73 48.57 48.23 54.15 101.89 92.28 80.94 82.14 54.00 68.24

SC 78.00 63.37 21.61 4.70 43.62 70.63 89.70 76.73 61.81 17.56 47.62 102.71 88.13 75.29 68.58 50.00 60.00

ST 125.00 67.50 23.31 46.40 59.58 77.02 - 80.83 42.44 4.35 - 114.85 91.96 91.43 84.96 46.50 68.30

OBC 58.00 60.40 - 29.70 40.85 62.84 91.00 82.05 54.23 13.47 4.47 80.64 91.95 80.39 61.99 44.80 57.12

General 76.00 57.71 - 0.40 35.89 58.96 126.30 56.00 35.83 12.86 2.06 120.08 93.04 51.00 87.53 58.60 58.15

Men 44.00 46.19 - 44.40 23.42 - - - - 38.95 40.28 50.01 - 31.60 30.06 30.40 37.83

Women 32.00 15.14 - 37.20 19.68 - - - - 9.28 13.87 51.88 - 49.34 52.08 23.60 30.41

Wage rate

obtained

(Rs.)

Aggregate 86.00 100.00 98.98 100.00 97.56 125.00 149.60 91.10 83.23 86.12 123.00 87.82 110.47 87.53 79.14 84.42 99.37

SC 82.00 100.00 98.98 100.00 97.15 125.00 149.90 91.55 78.69 88.03 123.00 76.08 111.66 82.40 62.48 84.13 96.94

ST 93.00 100.00 98.98 100.00 63.90 125.00 147.00 90.63 83.20 87.84 - 101.07 112.43 98.43 84.33 84.18 94.50

OBC 89.00 100.00 - 100.00 100.44 125.00 149.90 91.24 82.85 83.05 123.00 78.78 104.68 85.62 63.24 82.38 97.28

General 86.00 100.00 - 100.00 84.65 125.00 147.80 91.00 88.20 86.13 123.00 77.00 105.20 57.58 81.27 84.85 95.85

Men 86.00 100.00 - 100.00 97.56 125.00 149.60 91.10 83.23 86.20 123.00 87.82 110.47 88.69 78.76 84.42 99.43

Women 85.00 100.00 - 100.00 77.00 125.00 149.60 92.05 83.12 85.76 123.00 84.08 109.74 86.85 79.99 84.47 97.79

Minimum wages for unskilled

agricultural workers fixed by

state (Source: Ministry of Labour, New Delhi) as on

30.4.2010 (Rs)

119.4 100.0 109.0 - 112.0 125.0 162.0 110.0 80.8 106.7 136.8 110.0 110.0 100.0 100.0 81.0 -

Average distance from

residence where employed (Kms)

1.77 2.18 1.0 1.10 2.00 1.53 2.23 1.11 1.37 1.11 1.98 2.53 1.48 5.00 2.54 0.80 1.86

Percentage of HH employed 100 or more days

24.88 10.5 5.31 26.90 - - 48.50 - - 1.50 - - 85.00 2.35 44.50 1.00 25.04

94

Table 4.2: The activity in which employed under MGNREGA and the quality of assets created (Reference period- Jan-Dec 2009) (% of hh)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Characteristics Aggregate

Name of the activity

under which

employed

Rural connectivity 38.7 27.1 50.7 50.6 4.0 88.5 6.0 48.9 35.8 70.0 48.1 10.1 47.1 22.1 40.1 47.0 39.7

Flood control and protection 0.0 4.3 42.9 0.0 0.0 8.0 4.1 1.9 10.0 0.0 0.0 25.4 29.1 1.4 0.0 7.9

Water conservation and

water harvesting

20.4 24.3 10.2 0.0 22.5 5.0 0.0 30.0 2.6 10.0 0.0 74.6 13.0 30.3 20.3 14.4 17.3

Drought proofing 10.6 0.0 2.4 6.4 0.0 0.0 0.0 0.6 0.6 0.0 0.0 0.0 2.7 2.0 5.0 0.0 1.9

Micro irrigation works 2.0 8.1 13.9 0.0 27.0 0.0 0.0 1.1 0.0 0.0 0.5 8.1 2.4 0.6 5.3 9.3 4.9

Provision of irrigation facility to

land owned by (Panchayat)

3.1 2.3 0.4 0.0 5.0 1.5 0.0 0.0 1.3 0.0 0.0 0.0 7.9 3.6 0.8 0.3 1.6

Renovation of traditional water bodies

12.1 15.9 8.7 0.0 0.0 3.5 0.0 3.5 48.6 10.0 40.0 0.0 0.3 3.6 4.5 19.2 10.6

Land development 4.2 14.1 4.6 0.0 41.5 1.5 84.5 4.6 3.8 0.0 0.0 0.0 1.2 7.8 21.4 6.0 12.2

Any other activity approved by

the Min of R. Dev.

9.0 8.3 4.8 0.0 0.0 0.0 1.5 7.2 5.4 0.0 11.4 7.3 0.0 0.8 1.1 3.9 3.8

Quality of assets

created through NREGA

activities

Very good 24.3 43.0 0.0 81.3 24.5 80.5 78.5 51.4 45.5 32.5 15.5 34.2 33.5 60.5 40.0 13.0 41.13

Good 73.8 57.0 100.0 16.9 75.5 19.0 21.5 48.6 54.5 47.0 84.0 61.5 66.5 35.8 56.5 68.5 55.41

Bad 1.25 0.00 0.00 1.90 0.00 0.50 0.00 0.00 0.00 20.0 0.50 0.0 0.00 1.74 3.00 1.50 1.90

Worst 0.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.0 0.0 0.00 1.95 0.50 0.0 0.19

No response 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.00 0.00 0.00 0.00 17.00 1.31

Average unemployment allowances received by the

household for not getting work under NREGA after

registration (Rs. Per hh)

0.00 0.00 0.0 0.00 0.0 0.00 0.00 0.00 0.00 0.00 0.0 27.8 0.00 0.00 0.00 2.43 1.89

95

Table 4.3: The migration incidents recorded during the Reference period - Jan-Dec 2009

Characteristics

Ka

rn

ata

ka

Bih

ar

AP

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

No of members migrated from the village because of not getting work under NREGA even after registration (per household)

0.08

0.00 0.20 0.31 0.20 0.54 0.05 0.31 0.19 0.06 0.44 0.05 0.20

No of out-migrated members returned back to village because of getting work in

NREGA (per household)

0.07 0.65 0.20 0.14 0.07 0.00 0.00 0.11 0.05 0.05 0.18 0.05 0.12

In the case some members returned back to the village to work under

NREGA where were they earlier

working (% of returned members)

Nearby village 0.00 16.70 0.00 0.00 68.18 0.00 0.00 4.55 66.67 0.00 30.00 0.00 18.61

Nearby town 33.33 11.64 70.00 71.43 31.81 0.00 0.00 45.45 22.22 0.00 20.00 17.14 32.30

Same district 6.67 11.60 20.00 14.29 0.00 0.00 0.00 18.18 11.11 0.00 20.00 14.29 11.61

Same state 60.00 15.80 10.00 14.29 0.00 0.00 0.00 22.73 0.00 100.0 10.00 8.57 24.14

Other state 0.00 44.26 0.00 0.00 0.00 0.00 0.00 9.09 0.00 0.00 20.00 60.00 13.34

Other country 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

In the case some members returned

back to the village to work under NREGA which activity earlier working

in (% of returned members)

Const/ manufacturing/mining 61.54 47.75 60.00 81.48 70.37 0.00 0.00 16.39 77.78 88.89 60.00 70.21 63.44

Trading/services and transport 0.00 8.33 40.00 0.00 0.00 0.00 0.00 0.00 0.00 11.11 0.00 8.51 6.80

Private work/self business 0.00 1.75 0.00 0.00 0.00 0.00 0.00 0.00 11.11 0.00 10.00 0.00 2.29

Other government work 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.46 0.00 0.00 0.00 2.13 0.46

Agriculture labour 23.08 36.89 0.00 3.70 18.51 0.00 0.00 8.20 11.11 0.00 30.00 19.15 15.06

Any other 15.38 5.00 0.00 14.81 11.11 0.00 0.00 72.95 0.00 0.00 0.00 0.00 11.93

Year in which shifted (% of shifted hh) Shifted last year 76.92 37.40 80.00 100.0 100.0 37.04 33.00 2.44 100.0 100.0 63.30 85.71 67.98

Shifted before last year 23.08 62.60 20.00 0.00 0.00 62.96 67.00 97.56 0.00 0.00 36.70 14.29 32.02

Is your family better off now compared to previous occupation (% of shifted hh) 63.64 37.00 100.0 - 100.0 - - 67.65 100.0 77.78 50.00 97.14 77.02

96

Table 4.4: Wage differentials among different activities – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Participants (Average)

Wage rate in agricultural casual labour (Rs.)

Male 88.00 86.90 90.90 82.32 150.60 225.35 171.00 63.14 62.37 71.25 140.50 62.22 115.50 84.11 86.20 77.49 103.62

Female 76.00 65.28 87.00 78.06 91.60 193.72 160.00 52.85 61.76 64.11 55.60 49.02 100.00 82.93 66.30 67.05 84.46

Wage rate in non

agricultural casual labour

(Rs.)

Male 134.00 104.34 102.50 91.53 177.00 277.65 161.00 95.28 76.12 98.87 148.60 83.19 145.00 123.39 123.40 91.92 127.11

Female 130.00 77.00 83.10 86.93 126.80 239.43 162.00 67.27 71.87 66.92 42.30 55.91 120.00 125.01 73.60 68.35 99.78

Wage rate in public work programmers (Rs.)

Male 55.00 106.62 92.33 - 200.00 - 200.00 88.79 84.09 78.00 - 200.00 110.00 100.91 - - 119.61

Female 64.00 108.33 89.71 - 150.00 - - 77.50 60.00 - 110.00 100.00 175.00 - 103.84

Wage rate earned

by migrant workers (Rs.)

Male 118.00 118.72 128.00 - 228.60 - - 103.38 86.69 98.57 148.60 131.61 157.00 133.82 152.90 121.25 132.86

Female 125.00 - 92.43 - 188.20 - - 60.00 - 108.87 122.20 90.00 120.00 113.34

Wage rate under

NREGA (Rs.)

Male 86.00 100.00 - 100.00 97.56 125.00 149.60 91.10 83.23 86.20 123.00 87.82 110.47 88.69 78.76 84.42 99.43

Female 85.00 100.00 - 100.00 77.00 125.00 149.60 92.05 83.12 85.76 123.00 84.08 109.74 86.85 79.99 84.47 97.79

Table 4.4.1: Wage differentials among different activities - Non-Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Non-Participants (Average)

Wage rate in agricultural

casual labour (Rs.)

Male 89.00 98.05 114.00 82.50 152.40 252.78 156.00 61.81 60.75 72.05 142.80 70.74 110.00 84.44 96.50 77.19 107.56

Female 73.00 60.00 85.90 78.75 89.00 226.25 151.00 50.00 58.33 59.21 58.70 46.25 95.00 78.98 66.70 60.45 83.60

Wage rate in non agricultural casual

labour (Rs.)

Male 160.00 112.11 128.00 93.75 179.80 285.00 168.00 117.80 80.05 96.81 149.30 114.61 146.70 136.05 139.10 85.01 137.01

Female 134.00 75.30 74.00 89.06 121.20 250.00 178.00 60.00 80.00 66.03 63.50 96.33 121.50 109.17 81.00 50.50 103.10

Wage rate in public

work programmers (Rs.)

Male - 108.33 100.20 - 200.00 - - - 85.00 80.00 - - 110.00 100.00 - - 111.93

Female - 108.33 76.32 - 150.00 - - - - 60.00 - - 110.00 100.00 - - 100.78

Wage rate earned

by migrant workers (Rs.)

Male 93.00 111.42 175.12 - 228.00 - - 167.00 94.00 96.10 149.30 151.42 160.00 130.57 181.90 94.50 140.95

Female - - 81.00 - 189.00 - - - - - - 103.75 - 117.47 - - 122.81

97

Chapter 5

The Functioning of MGNREGA – Qualitative Aspects

5.1 Household assets holding

This Chapter summarizes some of the qualitative facts about the functioning of the MGNREGA.

But before looking into the qualitative factors, we briefly present the financial condition of the

selected households. Tables 5.1 and 5.1.1 presents all physical and financial assets held by the

selected households. The list of assets include agricultural land and other agricultural

implements, house property, livestock, consumer assets and belongings, business and financial

assets, household ornaments and utensils and other transport means such as two wheelers like

scooters, motor bikes and four wheelers like cars, jeeps etc. Per household land and implements

owned by the participant households averaged at slightly above 1 lakh compared to around 2

lakh by the non participant households. Similarly, house property owned by the participants was

slightly less than 1 lakh while it was slightly above that amount in the case of non participants.

The value of livestock averaged at 7.7 thousand for participants and above 10 thousand for

non participants.

Consumer assets including durables and non durables averaged slightly above 5 thousand for

the participant households and slightly above 10 thousands for the non participant category.

The participants hardly had any business or financial means while non participants recorded

more than 6000 such assets. Compared to consumer and business assets, ornaments recorded

quite high value of above 10 thousands for participants and more than double value of that for

the non participants. All the surveyed households had poor means of transportation as their

average value was almost negligible. At the aggregate, the value of assets owned by participants

were 2.2 lakh against more than double amount of 4 lakh owned by the non participants. The

above statistics indicate far better financial position of the non participants compared to

participant households. Comparing the selected states, the assets value was highest in Kerala,

followed by Maharashtra, Himachal Pradesh, Karnataka, Uttar Pradesh and Gujarat among both

participants and non participants.

98

5.2 Household status on borrowings and their financial vulnerability

Table 5.2 and 5.2.1 present borrowing by the sample households. The total loan amount by

participants was far above that of non participants. The total amount outstanding at the time of

survey among the participants was 49 thousand by participants compared to 28 thousand by

the non participants. Looking at the major sources of loan, institutional loans constituted 51 per

cent among the non participants while only 45 per cent among the participant households.

Among the non institutional sources, relatives and friends with comparatively much lower

interest rate constituted around 12 to 14 per cent share among both participant and non

participants households indicating that they highly relied on relatives and friends for providing

them the necessary insurance against the internal and external shocks and making for their

consumption smoothing4. Money lenders, commission agents, landlords and employer were the

other major sources of borrowing for both participants and non participants. Glancing at the

purpose for which loan was availed by the selected households, it is seen from the statistics that

the loan availed was mostly for consumption in both the categories. The activities like purchase

of land, purchase of machinery or vehicle constituted less than 25 per cent of the loan value

among both participant and non participant households. Construction of house was a major

investment activity which constituted around 19 per cent of loan among the participants but only

12 per cent among the non participants. Thus most of the loan taken by both these categories was

for daily or durable consumption and health treatment.

Among participants, the institutional loans constituted 100 per cent share in Uttar Pradesh,

Haryana and Himachal Pradesh while their share was above 50 per cent in Sikkim and Madhya

Pradesh. The states where non institutional loans constituted more than 2/3rd

share included

Karnataka, Bihar, Andhra Pradesh, Kerala, Chhattisgarh, Maharashtra, Rajasthan and West

Bengal. The pattern of borrowing among non participants was somewhat similar to participating

households. In the Haryana state participants used the whole loan amount for the productive

purposes like purchase of land or livestock. Among other states where participants utilized at

least 1/4th

amount for the productive uses were Uttar Pradesh, Sikkim, Chhattisgarh, Assam,

Gujarat and Rajasthan. In rest of the states almost whole amount of borrowing was used for

consumption purposes.

4 See, e.g., Kumar and Singh (in press).

99

Checking with the financial strength on borrowing (Table 5.3) around 10 per cent of

participating households indicated that they are doing wage work for those with whom they are

indebted, whereas 8 per cent of the non participating households indicated the same. Around half

of the selected households pointed out that there was a cooperative society in their village but

less than ¼th

of the households were members of such society within their village. Similarly

more than ⅔rd

majority of the household agreed that there was at least one informal credit society

or self help group in their village but only ⅓rd

of the selected households were members of such

societies. More than ¾th

of all selected households had an account in the bank or post office but

only 2 per cent of the selected households had any financial assets, like stock, bond or share of a

company. Similarly, less than 15 per cent participant households and around 20 per cent non

participant households had a life insurance policy.

Among the selected participants, around 30 per cent households in Bihar and Karnataka were

doing wage work to those whom they were indebted. In Kerala, Rajasthan and Assam, above 10

per cent households were doing wage work in lieu of borrowing. The household membership of

cooperative societies was high among participants in Kerala, Uttar Pradesh and Himachal

Pradesh (above 60 per cent of the households). Similarly, membership of informal credit

societies was found high (above 50 per cent) in Karnataka, Uttar Pradesh, Andhra Pradesh,

Kerala and Himachal Pradesh. Above 50 per cent participant households in all the selected states

indicated that they had account in a bank or post office as in most of the cases, wages under

MGNREGA were paid either through bank or post office. Among all the selected states very few

households had any financial assets but ownership of life insurance policy was found among

more than 1/4th

of the selected households in Kerala, Bihar and Uttar Pradesh.

Thus, from the above analysis it is clear that participant households were more vulnerable

compared to non participant households. Whereas, participant households owned assets around

half that of non participant households, their borrowing level was more than that of non

participant households. Not only was the loan amount higher for the participant households, their

proportion of non institutional loan was also higher. The fact that more participant members did

wage work for those whom they were indebted compared to non participant households indicate

financial vulnerability of people working under MGNREGA for whatever period they were

100

provided employment. In the next section we will go through some of the qualitative aspects of

MGNREGA functioning.

5.3 Some qualitative aspects of MGNREGA

5.3.1 Job card issues and work applications

Table 5.4 presents qualitative aspects of functioning of MGNREGA programme. Regarding job

card insurance, a majority of the households responded that they did not pay any changes or

bribe for getting a job card issued. Only 7 per cent participant households in Karnataka and 11

per cent in Rajasthan pointed out that they paid some fee or bribe to get a job card. Regarding

irregularities in the job card around 15 per cent households at the aggregate indicated that either,

no entry was made in the job card about the work performed under MGNREGA or entries were

missing or fake; entries were over written or signature column was blank, while clear cut

majority observed no such irregularities. The irregularities were reported in Maharashtra, Bihar,

Assam, Karnataka, Madhya Pradesh and Chhattisgarh. On the question where the job card was

generally kept, more than 80 per cent participants indicated that the card was kept with them

while rest of the 20 per cent indicated that the card was kept either with the sarpanch or sachiv

or contractor or gram-rojgar sevak or elsewhere but not with them. The incidence of job card not

being placed at the owner was most prevalent in Karnataka, Haryana, Kerala and Punjab.

Around 80 per cent of the household were given employment in response to their application for

work. However, only half of the participants indicated that they got a written receipt when they

put up their application for work and they obtained work within the bound period of 15 days of

their application. All households with a few exception indicated that they did not get any

unemployment allowances in lieu of not getting work within the period of 15 days after putting

up their application for work under MGNREGA.

5.3.2 Payment of wages and related issues

On the system of payment of wages almost all participating households agreed that wage rate for

male and female was same. The payment system was both daily-wage basis and piece rate/task

wage basis. The participants worked mostly on daily wage basis in Uttar Pradesh, Sikkim,

Kerala, Assam, Punjab and Himachal Pradesh. The work was piece rate or task wage basis in

101

Madhya Pradesh, Chhattisgarh, Maharashtra, Rajasthan and West Bengal. The participants

worked on partly on daily wage and partly on piece meal basis in Karnataka, Bihar, Andhra

Pradesh and Gujarat. In majority of cases, work was measured on collective or team management

basis while in a thin majority it was measured on individual work basis. A majority of participant

households pointed out that wages were paid either fortnightly or monthly basis but around 12

per cent participants pointed out that they had to wait for a longer period or at least more than a

month to realize their wages from MGNREGA work.

It is interesting to note that majority of the participants (more than half of them) obtained their

wages through bank. Another 40 per cent of the participant indicated that they obtained wage

through the post office. Only 5 per cent of the interviewed household obtained their wages

through Sachiv /Contractor/others and this fact makes MGNREGA programmes different from

all other employment generation programmes under operation in different states. Further with a

few exceptions, the bank accounts were on the individuals’ name working in MGNREGA. Out

of the interviewed participant, around 85 to 90 per cent indicated that banks followed the usual

procedure in their functioning and wages were paid in front of them by making entry into their

accounts. However, those who were not paid through bank or post office, a majority of them

indicated that wages were paid in front of the labourers either on the worksite or some other

public or private place. Among the irregularities in wage payments, the participant households

indicated that there was delay in wage payments after the work was finished; the wage paid was

less than the task performed and the participants faced problem in accessing post office or bank

account and lastly they were not aware on what basis wages were determined in case of those

whom wages were not paid on daily wage basis. Delay in wage payment was reported by highest

numbers of participants in Andhra Pradesh, Chhattisgarh, Madhya Pradesh, Gujarat and

Rajasthan.

5.3.3 Worksite facilities and economic usefulness of the work

Regarding information about the work to be performed and facilities available at the worksite,

around ⅔rd

majority of participants pointed out that they were given requisite details of the work

to be performed. About the facilities available at the worksite, around ¾th

of the participants

agreed that drinking water facility was provided at the worksite. About the facilities like shade

102

for period of rest; child care facilities; first aid kit and primary medicines available at the

worksite around 40 to 50 per cent participants replied that these facilities were not available on

the work site. Lack of drinking water, child care and medicine facility at the work place was

mostly reported by participants in Karnataka, Haryana, Madhya Pradesh and Punjab.

5.3.4 Monitoring of the work

On the monitoring of the MGNREGA functioning more than 80 per cent participants indicated

that the work was being monitored through some authority but majority of them did not know

whether any auditing of the accounts take place or not. In Haryana around 80 per cent

participants indicated that there was no monitoring taking place while 16 per cent expressed their

unawareness and only 4 per cent participants indicated that there was monitoring of MGNREGA

work was being held. In all other states more than 60 per cent participants indicated that the work

was being monitored. Very few participants lodged any complaint, or in other words, very few

participants were aware how to lodge a complaint if the households were not satisfied with the

functioning of MGNREGA. Even a thin majority who indicated that they lodged a complaint

only 7 per cent of them said that their complaints were taken care of.

5.3.5 Nature of assets created and their durability

In another set of questions, we enquired about the nature of work and about the assets created.

Around 90 per cent of the participated households pointed out that the work done was useful to

the villagers. Only less than 10 per cent households pointed out that the work done was not

particularly useful for the villagers. To the question of how long the constructed structure may

last, around 30 per cent opined that it may not last more than one year while around 40 per cent

expressed hope that the structure will last up to five years. Only 30 per cent interviewed

households expressed that structure will continue five to ten years or may even last more than ten

years. More than ¾th

majority of the participant households pointed out that it was worth to

create the structure or in other words, created structure would be useful for the villagers.

Similarly, slightly above ⅔rd

majority of the households indicated that the structure created was

adequate with due attention being paid to it.

5.3.6 Labour migration and MGNREGA

103

In Chapter 4, we presented cases of migration of labourers from the village for not getting work

under MGNREGA and also those cases where labourers migrated back to village for working

under MGNREGA. In this chapter, we further elaborate some qualitative factors of labour

migration related to MGNREGA functioning. After implementation of MGNREGA in 2005-06,

was there any case whereby household members migrated out of the village in search of job?

Around 18 per cent of the respondents indicated yes to the above question and a majority of them

pointed out that only one member of the family migrated in search of job. Only in Andhra

Pradesh, Kerala and Haryana, no migration of any member was reported while all other states

some migration incidents were reported. The migrated members obtained higher wages

compared to the prevailing wage rate under MGNREGA as was also seen in chapter 4.

Regarding members migrating back to the village for working under MGNREGA or migrating

from the village not being satisfied working under MGNREGA, only a few cases (8 per cent

households in the former and 5 per cent households in the latter case) were found affirmative on

the above question. Thus, some incidents of migration out of the village as well as migration

back to the village (to work under MGNREGA) were cited, but the extent of the same was only

miniscule, not leading to the conclusion that MGNREGA had any conclusive evidence of

affecting labour migration into any particular direction. Some household members migrating out

for job after implementation of MGNREGA among the selected states was observed

comparatively higher in Bihar, Gujarat, Assam, Rajasthan and Maharashtra. However, in Bihar

and Maharashtra the incidence of family members migrating back to village to work under

MGNREGA was also found higher than the other states indicating the reverse migration

occurring along with the incidence of migration among the participant households.

5.3.7 Respondents’ awareness about MGNREGA implementation

Regarding the question of villagers’ awareness about ‘MGNREGA Act’ under implementation in

the village, around 88 per cent of the respondents pointed out that people in the village were

aware about the same. About 67 per cent respondent pointed out that they were aware about their

right to apply for work and get employed within a period of 15 days after getting registered for

the same. Around 62 per cent respondents indicated that they were aware about the work

application procedure and 69 per cent knew about the right to minimum wages. Similarly, a clear

majority of the respondents knew about the level of minimum wages in the state and how wage

104

rate was being worked out under MGNREGA. In last chapter we saw that unemployment

allowance was not being paid to those who registered for work and were not being provided

work within the stipulated period of 15 days. On our further questioning, we observed that

households were completely unaware about the provision of unemployment allowance under

MGNREGA. More than 70 per cent households were not aware or not sure about the right to

unemployment allowance. Similarly, majority of the respondents were not aware about provision

of the worksite facilities, mandatory availability of muster rolls at the worksite and list of

permissible works under the MGNREGA.

5.3.8 Potential benefits of MGNREGA

To understand how the MGNREGA programme has affected the general life of villagers we

enquired few questions related to participants’ day-to-day life. Around 67 per cent participants

were of the view that MGNREGA has enhanced food security of the villagers by providing them

employment and thus purchasing power to have better access to food. Around 60 per cent

participants pointed out that MGNREGA has given greater independence to women. Around 65

per cent agreed that MGNREGA provided protection against extreme poverty. On the migration

issues, around 49 per cent indicated that MGNREGA has helped to reduce distress migration

from the village to cities. Similarly, around 50 to 60 per cent pointed out that MGNREGA has

reduced indebtedness by generating purchasing power at the local economy.

5.3.9 MGNREGA and food security

We further probed the food security issues among the participants. To our question did your

family get full two square meals throughout the reference year, around 24 per cent households

answered in negative. If the households did not have sufficient food how did they cope up with

the situation? Around 37 per cent affected households indicated that they borrowed from some

sources to cope up with the situation. Around 13 per cent pointed out that they reduced the

numbers of meals during the crisis period while others took other measures like catching fishes

or rats etc. The states where maximum number of households indicated not having two square

meals among the selected states were the poor states of Assam and Bihar while in the states of

Haryana and Andhra Pradesh no household reported not having sufficient meal during any

month of the reference year.

105

Box 5.1: Impact of MGNREGA on the Villagers – A Case from Karnataka

The employment created through MGNREGA is expected to have an impact on the individual workers

who participate in the programme at the household level and at the village level. Prima facie

evidences collected from the households during the discussion with the villagers indicated that per

household employment gain under MGNREGA for the state during the years 2007, 2008, 2009 was

around 20 to 40 man days. It varied across the districts. At the aggregate level, the number of wage

days worked under non MGNREGA was high for participates signifying that MGNREGA has played

a complementary role and not a substitute. Self employment days were less for participating

households indicating that they had substituted MGNREGA work to their regular self employment

work, which fetched them perhaps regular and higher income as compared to income from the self

employment. Participates prefer to remain unemployed or not available for work instead of taking up

low paid or unwanted work. Wage employment from MGNREGA was found competing with non-

MGNREGA wage employment. Still MGNREGA has not been successful in substituting non

MGNREGA employment in the chosen districts. Number of days of self-employment has come down

sharply for participating households as compared to non-participants. This indicates that wage

employment (under MGNREGA) has been substituted for self-employment, in the latter there is also a

higher degree of disguised unemployment and that explain the reason for the shift towards

MGNREGA employment. The survey revealed that guarantee of employment at the minimum wage

has increased the staying power of workers and they prefer to wait rather than to accept low paid

work, and hence the number of days of unemployment has increased. This also means that

MGNREGA has not provided adequate employment to the workers and the programme has widened

the choice of employment for the participant households to some extent. Participants felt that due to

MGNREGA migration has been avoided. The participants across the selected districts were of the

view that MGNREGA has contributed to useful assets for the villagers. Both the participants and non-

participants felt that there was a rise in market wages due to MGNREGA and also labour scarcity is

happening in peak season in agriculture. Participants felt that MGNREGA has helped them in

sending their children to school. MGNREGA was also useful for the debt repayment. The improved

purchasing power through MGNREGA also contributed to coping illness among the participating

members. Average wage earned by male participants under the programme was around Rs 100 that

were found equal to the prevailing market rate in the village. On the other hand, female average wage

under MGNREGA was around Rs 90 that was much higher than the average market wage that

prevailed somewhere around Rs 50. For that reason women appear to have substituted self

employment with MGNREGA work relatively more than their male counterpart. Wage rates have

increased in agriculture as well as non agriculture for male as well as female. While talking to

farmers it was observed that in agriculture, the percentage increase in wage rate ranged up to Rs 100

and for women up to Rs 150. After MGNREGA wage rate in village tend to be equal for both male

and female. The equalization of wages across gender and space has improved labour ties in the

village.

106

5.4 Some quantification of qualitative questions

We further tried to quantify some aspects of the functioning of MGNREGA. We probed those

participants who indicated that the job card was not kept with them, what was the reason for the

same. A 3/4th

majority of those who did not have job card with them were not knowing the real

reason for not having card with themselves while rest 1/4th

of them replied that the head of the

Panchayat (Sarpanch) or contractor had kept it with themselves to make entries in the card or for

security reasons (Table 5.5). To our question who monitored the functioning of MGNREGA?

Around 11 per cent participants said it was supervisor while around the same numbers also

indicated that the person was some government official at the block or district level. However, a

clear majority (around 50 per cent) named the Gram Panchayat or Panchayat Secretary mainly

functioning for the monitoring work of MGNREGA. The rest of the participants (less than 1/3rd

)

were not knowing whether there was any monitoring being carried out or if so who carries out

the same. The matters on which complaint was lodged by the participants included, tools not

working properly, job card not returned, wage rate paid was low or wage rate not paid on time

and complaints for not following rules in the functioning of the MGNREGA. Among the

participants who lodged complaint only less than 10 per cent of them pointed out that either

action was taken or they were assured that proper care will be taken in the future. However, a

majority of those who lodged the complaints were not sure whether any action was taken or not.

5.5 The effect of MGNREGA on rural livelihood

During our field survey, we tried to capture how have the MGNREGA affected the livelihood of

the participant households. We further probed some question related to food security, poverty,

indebtedness and distress migration. We asked the participants how MGNREGA has enhanced

food security, a majority of the participants pointed out that by providing employment

MGNREGA has helped their food security during the working days, moreover by saving some

money when they are employed, they now have better food security when they are not employed

in MGNREGA as well. However, overwhelming majority indicated that MGNREGA can ensure

better food security by guaranteeing at least 100 days employment to every household and the

programme would be more useful in ensuring food security if they are also provided food at the

work place.

107

To the question how MGNREGA provided protection against extreme poverty, the respondents

were of the view that although MGNREGA provided extra purchasing power and reduced

migration but it could be more effective if it could provide full 100 days work; provide wage on

daily basis; stipulated minimum wage are ensured; and poorest people are given top priority. To

the question of migration, a significant number of respondents pointed out that to some extent

MGNREGA have been successful in reducing the distress migration but it can be more effective

in stopping unnecessary migration if 100 days work and minimum stipulated wages are ensured.

Similarly, respondents agreed that indebtedness to informal sources would also be checked if

MGNREGA provides employment to people at higher wage rate compared to prevailing wage

rate within the village.

5.6 Suggestions to raise efficacy of MGNREGA

Finally we enquired the households what problems they faced during the reference year and how

to ameliorate them. For example, those households who did not have sufficient food last year in

their opinion what was the reasons for the same. Around 30 per cent of them responded that no

opportunity for work was the reason for the same. Another 20 per cent indicated that low wage

rate, lack of access to PDS food was the reason. The other reasons pointed out by the households

were low household income, indebtedness etc. The major problems other than food during the

last year faced by the households included health, unemployment, high education expenditure,

shelter and indebtedness.

The suggestions given by households to ameliorate their problems includes providing

employment opportunities throughout the year; provision of concessional food and other

essentials through improved efficacy of government programmes; additional employment during

the off-season of agriculture among many others. Among the major suggestions to improve

MGNREGA functioning, an absolute majority of the respondents (40 per cent) pointed out that

the number of working days and wage rate should be increased under MGNREGA and work

should be available throughout the year. Respondents pointed out that the stipulated minimum

wages should be ensured in practice. A significant numbers of them pointed out that the

implementation should be improved though local bodies and job card should be given in the

hands of the workers. The other minor suggestions included quick payment after work, hundred

108

days mandatory work for all, provision of concessional loans, food facility at the work place,

preference to manual work rather than machine, proper measurement of the work, better

implementation with in-built monitoring system, transparency and accountability in

implementation, better awareness and more innovative work should be allowed under

MGNREGA. Last and the least, private farm work should be allowed to maintain continuity in

the MGNREGA works.

Box 5.2: Field observations and recommendations - Karnataka

Planning process at the Gram Sabha level was found to be far from satisfactory. The awareness level at

the village/mandal clearly points out the need for altering the administrative machinery at all levels

including district, mandal/block and village level. Applications for work deserves much higher attention

as paying unemployment allowance and provision of work were all attached to the application for work

which the households were found completely unaware because ground level procedure was not found in

proper order for putting up an application for work. Simplifying and strictly imposing these provisions

will go a long way in making the MGNREGA programme much more effective. Working conditions at

the worksite were mostly found to be satisfactory. Worksite facilities and child care facilities require

much attention. Overall, wherever the PRI officials at the village and mandal level were active, the

MGNREGA work was implemented with enthusiasm. Enough funds should be provided to Panchayats

to ensure minimum wages to the workers. Officials need to take interest frequently visiting the

worksites, enthusing gram sarpanch and other village officials to take up work actively and also assist

in conducting gram sabhas. Services of village organizations, e.g., Self Help Groups, NGOs and other

existing organizations should also be used to increase the efficacy of MGNREGA. Earlier employment

programmes like Food for Work (FFW) encountered problems in implementation like leakages and

involvement of contractors. There is a need for innovative administrative arrangements to overcome

such problems in the case of MGNREGA. The agriculture sector is undergoing structural change

whereby the large holdings are getting fragmented into small and marginal holdings and because of

increasing cost in agriculture the latter are finding it difficult to make earning in the agriculture sector.

The challenge Karnataka state is facing is to ensure higher participation of women, providing hundred

days employment to all who wish to participate in MGNREGA including the small and marginal

farmers, ensure stipulated minimum wage under MGNREGA and create productive assets under

MGNREGA at the village level that can sustain in the long run.

Suggestions to improve the programme:

A large scale, intensive awareness campaigns about MGNREGA and bringing into notice of the

people about its benefit and other legal provisions in all villages/communities.

Women need to be involved in the monitoring through their grass root organizations such as

SHGs and SHG federations which need to be empowered for the task through amendments in

the law.

Representative of women organizations should be invited to attend the quarterly review

meetings on MGNREGA at the district level.

Regular orientation and sensitization programmes for selected representatives need to be

conducted.

Panel provisions relating to the violations of MGNREGA law needs to be made rigorous in

order to deter corrupt practices and such panel provisions need to be publicized widely.

109

5.7 Summary of the Chapter

The analysis in this chapter points that participant households were much more vulnerable

compared to non participant households. Whereas, participant households owned assets less than

half that of non participant households, there borrowing level was almost double that of non

participant households. Not only was the loan amount higher for the participants, their proportion

of non institutional loan was also much higher. On the qualitative questions, a majority of the

households indicated that they did not have to pay any bribe to get a job card issued. Around 80

per cent of the household were given employment in response to their application for work. All

households who did not get work within 15 days indicated that they did not get any

unemployment allowances. On the system of payment of wages almost all participating

households agreed that wage rate for male and female was same. The payment system was both

daily-wage basis and piece rate/task wage basis. It is interesting to note that majority of the

participants obtained their wages through bank or post office. On the monitoring of the

MGNREGA functioning more than 80 per cent participants indicated that the work was being

monitored through some authority but majority of them did not know whether any auditing of the

accounts take place or not. Around 90 per cent of the participated households pointed out that the

work done was useful to the villagers. Some incidents of migration out of the village as well as

migration back to the village (to work under MGNREGA) were cited, but the extent of the same

was only miniscule, not leading to the conclusion that MGNREGA had any conclusive evidence

of affecting labour migration into any particular direction. Regarding the question of villagers’

awareness to the programme they were hardly aware about the provision of unemployment

allowance under MGNREGA. On the efficacy of MGNREGA in providing food security,

removing poverty and providing safeguards, the participants agreed that MGNREGA has been

successful in helping the poor on all these aspects, but they were of the view that MGNREGA

could have done far better if it could ensure hundred days of work to every participant and could

provide the minimum stipulated wage rate to all those who worked in MGNREGA programme.

The major suggestions given by the households to improve MGNREGA functioning included,

increased number of working days and wage rate; improved implementation through local

bodies; quick payment after work; hundred days mandatory work for all; provision of

concessional loans; and food facility at the work place.

110

Table 5.1: Assets holding (Rs per HH) – Participants

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

greg

ate

Particulars Participants

Land and

agricultural

implements

111038 155919 83500 69996 3349 467816 47275 124979 151282 36704 1150 262166 245705 66283 55000 40909 121047

House

Property

89139 71890 85500 50200 1284 312359 30823 83038 55101 25351 36748 51121 76990 39642 95225 35645 71493

Live stock 6499 9755 8900 4324 281 3263 3728 3630 9964 1368 3385 24279 16796 9834 13866 3322 7768

Consumer

assets

5659 1198 - 4446 190 29828 4363 2715 3279 1151 4703 3886 9055 4448 5954 3067 5254

Business

assets

272 35 - 2309 273 11001 250 0 0 3209 775 0 750 1033 1228

Ornaments 10853 8943 550 5362 218 61290 196 4940 6897 10762 2067 4849 33605 10502 12961 3883 11180

Utensils 3160 635 1000 3369 20 1205 1017 573 487 1838 1524 3420 1964 2383 1168 1462

Transport

means

2984 733 2475 392

Others 154 3008 1200 2413 169 38750 1112 50 1200 231 5102 240 3007 0 23 3557

Total 229758 251383 180650 142418 5784 924306 88952 220367 228296 79263 50624 352927 386586 135680 188612 89050 223382

111

Table 5.1.1: Assets holding (Rs per HH) - Non Participants

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

greg

ate

Particulars Non- Participants

Land and

agricultural

implements

349037 263902 109500 81407 26472 705532 30000 455584 242364 29301 12100 828921 395860 267350 77300 134394 235392

House

Property

111944 110440 120000 62375 5192 550000 27260 113500 76660 17702 53784 74512 116420 53548 100300 112810 104247

Live stock 20074 42100 15000 6823 918 4063 3380 5800 11524 3370 6360 22870 16500 9810 6130 4126 10915

Consumer

assets

7750 1403 - 8450 1015 89615 5160 5674 5560 1000 7870 13907 21260 8352 8742 8698 11911

Business

assets

4259 - 2500 14531 994 72500 0 0 0 4680 1610 800 0 1075 1700 6074

Ornaments 23750 10740 1050 14656 1990 118000 126 17462 11159 3659 5636 10122 51840 12952 24600 13370 19351

Utensils 4352 828 900 4313 168 1391 3568 980 747 1761 2643 6680 1956 4347 1863 2234

Transport

means

5178 - 7939 4274 1534

Others 537 5072 1500 988 944 35200 1028 200 0 724 33885 2420 3416 100 92 4920

Total 526881 434485 250450 193542 37694 1574910 68345 601788 348247 61183 95450 988470 611780 357384 226868 277053 396578

112

Table 5.2: Borrowing by sample households (percentage of household) – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Participants

Source

of loan

Institutional loan (banks) 32.54 100.00 34.14 73.48 27.20 28.18 100.00 58.98 22.19 23.41 100.00 43.05 38.90 32.56 44.66

Traders-cum-Money Lenders 13.61 29.15 8.26 10.37 7.72 0.00 10.09 13.99 77.43 72.34 63.46 0.00 0.00 35.70 32.95 23.44

Commission Agent 7.10 - 3.91 1.05 0.00 0.00 2.85 6.77 22.57 0.00 0.00 0.00 2.20 0.73 2.95

Landlord/Employer 4.73 10.50 3.91 5.22 20.51 0.00 0.00 33.52 17.58 1.35 0.00 10.72 3.30 3.13 7.15

Friends/Relatives 12.43 26.21 10.43 0.17 43.59 0.00 16.06 21.97 10.07 10.66 0.00 40.18 19.70 12.30 13.99

Others 29.59 - 56.00 0.00 - 12.03 1.55 1.12 0.00 6.05 0.30 18.34 7.81

Purpose of loan

Daily consumption 15.12 17.43 1.67 10.00 41.10 15.03 0.00 1.97 2.30 4.97 3.41 4.69 15.45 22.96 13.00 18.57 11.73

Social ceremony 22.09 15.62 6.63 10.43 2.03 9.06 0.00 41.27 39.07 22.57 44.14 58.48 3.09 0.00 16.50 15.53 19.16

Health treatment 9.88 1.26 24.02 4.35 7.52 9.47 0.00 10.88 2.87 9.70 12.82 8.23 0.62 1.26 13.60 10.21 7.92

Purchase of land/ livestock 0.58 23.29 13.27 33.04 7.67 12.26 100.00 0.00 35.43 29.80 9.16 2.61 15.96 26.79 30.30 14.07 22.14

Purchase of machinery/vehicle

2.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.15

Consumer durables 5.81 0.00 0.00 0.00 3.91 11.89 0.00 0.00 0.00 0.37 0.00 2.87 3.30 0.00 1.76

Construction of house 19.19 16.04 54.41 24.78 5.67 19.57 0.00 15.72 12.59 32.96 21.43 10.63 36.05 0.00 4.60 23.24 18.55

Purchase of livestock/land 3.49 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 0.00 0.22

Others 21.51 26.36 - 17.39 32.11 22.73 0.00 30.16 7.75 9.16 14.99 28.84 46.12 18.70 18.38 18.39

Amount

Borrowed

Total loan borrowed

(Rs. Per household)

57147 3585 4768 1438 59380 341254 250 3866 7384 2215 2730 10461 4855 2613 9221 2399 32098

Total loan outstanding at the

time of survey

(Rs. Per household)

37548 3585 3768 1438 33250 659974 250 3816 4569 2215 2730 10461 4855 2613 9221 2399 48918

Rate of interest (Per cent per annum)

9.50 13.96 17.75 24.00 10.53 13.00 25.30 10.56 10.00 36.00 16.50 8.70 10.00 27.00 36.26 16.82

113

Table 5.2.1: Borrowing by sample households (percentage of household - Non Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Non-Participants

Source

of loan

Institutional loan (banks) 48.48 100.00 33.94 82.96 31.92 100.00 0.00 38.76 53.20 0.00 0.00 76.52 100.00 0.00 73.31 25.48 50.97

Traders-cum-Money Lenders 9.09 0.00 27.52 5.14 10.47 0.00 0.00 0.00 0.00 0.00 16.67 7.88 0.00 5.08 31.29 7.54

Commission Agent 9.09 0.00 0.00 6.11 0.00 0.00 0.00 54.26 0.00 59.09 0.00 0.00 0.00 0.00 8.57

Landlord/Employer 9.09 0.00 27.52 0.00 3.81 0.00 0.00 0.00 0.00 83.33 3.28 64.38 2.48 0.00 12.93

Friends/Relatives 3.03 0.00 11.01 5.79 0.00 0.00 0.00 3.88 38.57 40.91 0.49 27.04 18.82 36.19 12.38

Others 21.21 0.00 0.00 53.81 0.00 3.10 8.23 11.82 8.58 0.31 7.03 7.61

Purpose

of loan

Daily consumption 9.09 18.03 14.68 9.97 43.85 0.00 0.00 0.00 14.45 100.00 22.75 6.25 16.51 17.04

Social ceremony 21.21 17.05 24.77 5.14 0.00 0.00 0.00 15.50 18.45 26.36 83.33 3.28 72.96 15.73 0.00 20.25

Health treatment 18.18 1.25 5.50 0.00 8.69 8.06 0.00 6.98 6.47 8.64 31.20 0.00 4.33 16.82 7.74

Purchase of land/ livestock 3.03 19.84 20.18 27.01 12.16 27.42 0.00 38.76 36.89 38.86 13.79 4.29 49.54 11.21 20.20

Purchase of

machinery/vehicle

9.09 0.00 0.00 0.00 0.00 - - 0.00 0.00 0.00 0.00 0.00 0.61

Consumer durables 3.03 0.00 0.00 3.86 6.02 0.00 0.00 0.00 0.00 3.28 0.00 4.95 0.00 1.41

Construction of house 6.06 15.41 34.86 2.57 0.00 64.52 0.00 0.00 24.64 26.14 0.00 0.00 3.72 1.53 11.96

Purchase of livestock 0.00 0.00 0.00 0.00 0.00 - 0.00 0.00 0.00 0.00 0.00 0.00

Others 30.30 28.43 - 51.45 29.28 0.00 - 38.76 13.55 16.67 33.99 0.00 15.48 53.92 20.79

Amount

Borrowed

Total loan borrowed (Rs. Per household)

32426 3050 5450 3888 31530 92857 - 2580 2631.7 4400 1440 6767 2600 4660 16150 1962 14159

Total loan outstanding at the time of survey

(Rs. Per household)

30815 3050 5450 3888 17265 310000 - 2580 4066 4400 1440 6767 2600 4660 16150 1962 27673

Rate of interest

(Per cent per annum)

10.00 13.00 19.33 24.00 10.00 36.40 18.87 10.00 36.00 8.80 10.00 10.80 12.00 28.82 16.53

114

Table 5.3: Household saying yes to the following questions on strength on borrowing (Percentage of households) – Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Participants

Doing wage work to those

whom they are indebted

28.64 0.00 30.00 0.00 4.00 17.50 - 7.00 8.00 13.50 5.00 9.80 0.00 2.50 10.50 4.00 10.22

Availability of co-operative credit society in village

47.24 67.50 60.00 37.50 0.00 90.00 20.00 69.00 78.50 0.00 74.00 47.55 56.50 50.00 50.00 40.00 49.24

Family member being member

of such society

26.06 64.50 30.00 31.30 7.60 64.00 5.00 0.00 0.00 0.00 0.00 11.27 60.50 13.50 13.00 10.50 21.08

Availability of informal credit

society/SHG in village

88.44 78.50 20.00 50.00 80.40 85.50 13.00 71.50 69.00 40.50 60.00 97.06 88.00 70.00 30.00 90.00 64.49

Family members being member of such society

57.73 54.00 10.00 18.10 80.40 68.00 7.00 6.50 5.50 3.50 3.50 45.59 51.00 10.00 35.00 42.00 31.11

Having account in a bank/post

office/other institution

85.07 100.00 90.00 100.00 56.00 95.00 53.00 88.00 86.50 100.00 74.00 93.63 99.50 100.00 100.00 100.00 88.79

Having any stocks/bond/

shares/other similar assets

11.17 0.00 0.00 0.00 11.40 3.50 8.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.50 2.35

Having life insurance policy 19.47 22.50 40.00 8.10 8.40 57.50 10.00 5.50 4.00 15.50 0.50 4.90 2.50 7.00 9.50 13.00 14.27

115

Table 5.3.1: Household saying yes to the following questions on strength on borrowing (Percentage of households) - Non

Participants

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Occupation Non-Participants

Doing wage work to those

whom they are indebted

10.91 8.00 16.00 2.50 2.60 0.00 - 0.00 0.00 18.00 0.00 13.33 4.00 18.00 14.00 2.00 7.96

Availability of co-operative

credit society in village

54.72 24.00 50.00 37.50 0.00 76.00 10.00 76.00 82.00 0.00 82.00 57.78 10.00 50.00 52.00 40.00 43.88

Family member being member

of such society

15.79 30.00 10.00 30.00 2.00 48.00 10.00 8.00 6.00 0.00 3.00 22.22 20.00 26.00 0.00 14.00 15.31

Availability of informal credit

society/SHG in village

87.04 62.00 10.00 50.00 80.00 62.00 8.00 82.00 76.00 38.00 65.00 91.11 50.00 70.00 26.00 90.00 59.20

Family members being member of such society

46.00 52.00 8.00 20.00 80.00 48.00 8.00 14.00 12.00 3.10 5.00 35.56 50.00 18.00 8.00 32.00 27.48

Having account in a bank/ post office/other institution

75.93 72.00 30.00 100.00 43.20 70.00 44.00 50.00 52.00 62.00 56.00 71.11 40.00 56.00 60.00 90.00 60.77

Having any stocks/bond/

shares/other similar assets

10.00 0.00 0.00 30.00 3.20 12.00 8.00 0.00 0.00 0.00 0.00 2.22 2.00 0.00 0.00 0.00 4.21

Having life insurance policy 28.85 20.00 20.00 40.00 2.20 68.00 14.00 14.00 12.00 14.00 2.00 28.89 0.00 22.00 12.00 22.00 20.00

116

Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Description Yes

Job card

issuance

Paid any fees/Charges or bride to get a job

card

7 0 0 0 1 0 0 0 1 0 5 11 2

Irregularity

in the

Job card

No entries were made , even though the job

card holder(s) had worked on MGNREGA

17 0 30 10 9 3 16 16 22 4 45 0 23 20 13

Some entries were incomplete or missing or

fake information was entered

20 0 30 12 1 7 7 60 9 9 0 21 31 13

Some entries had been over-written 18 0 10 7 1 4 4 0 7 2 0 16 7 5

The signature column was blank or partly blank

27 2 15 15 5 11 30 60 9 7 1 23 18 14

Where

was the card

generally

kept

With the card holders 33 95 60 100 100 77 50 95 95 70 81 88 92 96 80 100 82

With Sarpanch or Sachiv 35 5 0 21 40 6 6 0 19 1 8 4 6 9

With Contractor 18 20 1 6 0 0 0 0 1 0 3

With the Gram Rojgar Sevak 7 20 1 0 0 0 30 0 0 1 4

Elsewhere 7 0 0 5 0 0 0 0 0 14 2

Work

application

Are you employed in response to an

application for work

77 72 60 100 90 75 67 96 18 100 94 56 100 91 93 100 80

If applied, did you get a dated receipt for the

application

48 72 50 78 80 74 65 37 35 48 55 99 88 28 19 55

If applied, did you get work within 15 days of application

55 83 100 85 100 66 77 3 0 70 7 73 100 91 75 73 66

In case of failure to provide work within 15

days, is unemployment allowance paid

6 32 0 80 0 71 0 0 0 9 0 0 0 5 13

Payment of wages

Are the wage rates same for men and women 78 100 100 100 90 100 71 100 100 100 100 99 100 97 98 84 95

Wage rates higher for men 18 0 0 10 0 22 0 0 0 0 4 3 17 4

Wage rates higher for women 1 0 0 0 8 0 0 0 0 0 0 1

Wage paid on "Daily-wage" basis 58 88 60 100 30 99 22 0 0 100 100 0 73 24 1 47

Wage paid on "Piece-rate/Task-wage" basis 42 2 40 70 2 78 100 100 0 0 100 27 76 100 100 52

Measureme

nt

of work

Work was measured by individual's work 51 98 60 10 86 24 14 0 9 5 3 11 1 10 24

Work was measured by team measurement 28 0 30 70 13 69 87 100 70 94 93 49 95 80 55

Work was measured by Collective

measurement

18 0 0 100 20 1 6 0 0 100 22 0 4 41 5 10 20

Work was not measured 3 2 10 0 0 1

117

Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) - Contd.

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Period of wage

payment

Wages were paid within a fortnight 48 53 85 73 90 65 0 16 0 70 14 47 99 61 7 50 48

Wages were paid Within a month 33 28 0 27 10 33 81 82 85 20 70 43 2 36 34 50 39

Wages were paid more than a month 19 20 15 3 19 3 16 10 17 10 4 60 12

Wages were paid after one year 0 0 0 0 0 0 0 0 0 0 0 0

Who made

the wage payment

Sarpanch or Sachiv 6 0 0 2 13 2 5 0 3 1 2 0 2

Post office 25 13 80 75 100 0 8 27 28 50 34 49 59 49 47 40

Bank 51 88 20 25 98 78 72 67 50 64 29 100 35 46 54 55

Representative of line department 5 0 0 0 1 0 0 13 6 6 2

Other Government official 2 0 0 0 0 0 8 0 0 1

Contractor 10 1

Any other 2 0

In case

wage payment

made in the

bank

Bank account was on self's name 92 100 70 100 100 100 92 100 100 100 98 90 95 82 89 100 94

Spouse's name 4 20 0 8 0 2 2 5 18 8 4

Parent's name 3 0 10 0 0 0 2 1 0 2 1

Children's name 1 0 0 0 0 0 6 0 1 0

Individual account 93 83 50 100 100 100 86 99 100 95 98 78 84 83 80 100 89

Joint account 7 17 50 1 14 2 0 5 2 22 17 17 21 11

Did bank follow usual procedure of banking 94 87 70 100 99 82 100 100 100 97 87 100 92 100 100 88

In case

wages were not

paid

through bank

Wages paid in front of all labourers 86 33 100 8 76 87 84 85 26 7 92 43

Wages paid on the worksite 9 0 59 8 8 3 0 5 3 6

Wages paid in panchayath Bhavan 5 5 30 4 3 1 2 2 4 3

Wages paid on other public/ Private place 0 96 11 0 6 25 0 92 14

Wages paid on some one's private residence 0 0 1 0 0 7 0 1 1

Other private faces 0 0 0

Complaints

regarding wage

payments

There were delays in wage payments 44 - 30 15 100 17 21 89 92 10 25 40 70 69 50 42

Wage paid less than the minimum wage 15 - - 59 8 0 0 0 19 8 59 10

Wage paid less than asked for sign/thumb impression

11 - - 7 8 0 0 0 2 8 7 3

Task was too much compared to the wages

paid

39 - 30 9 11 8 5 0 12 14 16 39 11

Faced problems in accessing post office/bank accounts

17 - 50 65 50 30 8 34 55 0 37 2 35 34 23 27

On what basis wages are calculated not clear 20 - 80 25 8 8 11 11 0 18 6 46 25 16

118

Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) – Contd.

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Details of worksite

facilities

A Board/GP member gave details of the sanctioned amount, work dimensions and

other requisite details

76 83 40 100 100 10 38 76 76 72 63 71 78 59 74 57 67

The worksite had drinking water facility 49 98 40 50 100 64 97 95 95 0 100 87 99 81 95 60 76

Worksite had shade for periods of rest 18 82 20 50 100 100 62 8 8 100 17 25 80 65 82 60 55

Worksite had child care facility 11 68 20 50 100 100 11 13 13 100 2 1 55 56 73 10 42

Worksite had first aid kit/medicines 21 88 - 50 100 100 17 7 93 100 10 89 92 53 91 80 62

Monitoring Was there any authority to monitor the

functioning of the MGNREGA administration

59 100 80 100 100 91 4 94 94 100 79 93 100 91 97 100 86

Any complaint lodged relating to worksite

etc., to the Gram Panchayat, Programme Officer or other officials

9 0 10 0 29 0 2 0 0 0 5 14 0 1 11 5

If yes, was any action taken on your

complaint

4 0 8 0 19 0 1 0 0 0 30 24 - 0 50 9

Economic usefulness

of the work

Work is very useful to the villages 61 86 60 76 100 99 88 86 85 83 74 48 85 92 40 69 77

Work is quite useful to the villagers 27 14 0 19 0 12 13 13 0 24 45 15 8 57 19 16

Work is not particularly useful to the

villagers

10 0 40 3 0 0 2 2 17 2 6 0 0 3 6 6

Work is useless for the villagers 1 0 0 0 0 0 1 0

Not sure 2 3 2 1 7 1

Nature of assets

and their

durability in

which the

interviewee involved

The structure created may last up to one year 20 4 90 25 10 95 66 32 39 50 35 5 0 7 8 30

The structure created may last up to five year 64 19 10 15 10 6 28 45 59 50 39 77 18 85 73 31 39

The structure created may last up to ten year 13 72 - 34 10 0 7 17 2 0 13 16 75 9 10 63 21

The structure created may last more than ten year

3 6 - 26 70 0 0 8 1 0 15 1 8 0 9 6 10

It is worth creating the structure 79 100 70 100 100 92 67 96 99 60 91 80 100 89 75 72 86

Was the structure created adequate 69 70 20 73 90 91 62 82 92 20 72 51 74 87 61 60 67

How has

MGNREGA

affected

labour

migration

Did any your family members migrated out

for job after implementation of MGNREGA (year 2005 onwards)

10 15 50 0 - - 10 10 43 5 27 15 47 28 24 18

Are wages higher in city or other states than

MGNREGA

73 90 100 100 - - 7 7 100 9 80 80 73 74 14 50

Any family members migrated back to village to work under MGNREGA

5 6 40 - - 0 5 0 - 27 4 9 13 23 8

Any family member migrated as wage labourer with dissatisfaction from

MGNREGA

3 0 20 - - 0 0 12 - 27 0 12 6 2 5

119

Table 5.4: Qualitative questions related to functioning of MGNREGA (Percentage of HH) – Contd.

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Respondents '

awareness

about MGNREG

A

implementation

Are respondents aware about MGNREGA implementation

68 97 50 100 100 90 80 100 100 100 100 79 96 100 92 64 88

Right to apply for work and get employed

within 15 days

35 97 30 56 100 73 77 91 91 72 69 60 96 53 68 8 67

The work application procedure 32 95 30 57 100 74 57 77 97 21 65 34 94 44 60 56 62

Right to minimum wages 37 97 80 57 100 87 38 97 100 100 66 28 95 29 59 29 69

The level of minimum wages 27 96 50 57 100 0 20 96 96 100 93 20 96 22 33 46 59

The wage calculation method 28 78 50 29 100 78 25 27 27 100 45 30 72 12 14 17 46

Right to the unemployment allowance 12 94 25 36 63 30 0 0 0 25 37 87 16 14 15 28

Minimum worksite facilities (drinking water,

first aid,)

21 90 25 47 100 70 31 11 89 22 20 71 91 45 93 39 54

Mandatory availability of muster rolls at the worksite

25 92 25 47 100 92 22 67 93 37 52 38 92 36 78 7 56

The list of permissible works under the

MGNREGA

15 76 - 60 100 73 17 71 71 0 60 13 65 33 44 6 44

Potential benefits of

MGNREG

A

MGNREGA enhanced food security 55 100 40 79 100 43 67 94 94 12 42 77 100 0 100 73 67

MGNREGA provided protection against

extreme poverty

37 100 85 83 100 48 83 85 58 15 35 51 100 0 96 68 65

MGNREGA helped to reduce distress

migration

45 100 50 0 100 18 85 39 39 7 34 37 100 0 75 59 49

MGNREGA helped to reduce indebtedness 30 100 30 82 90 8 78 31 61 12 32 25 100 0 76 60 51

MGNREGA gave greater economic

independence to women

61 100 60 75 100 44 80 34 35 12 30 51 100 0 98 49 58

MGNREGA generated purchasing power at local economy

35 100 60 71 100 36 78 51 59 27 46 28 100 93 75 60

Questions

related to

food security

Did your family get full two meals

throughout year 2009

62 96 50 70 100 95 100 74 90 26 69 78 96 69 77 71 76

How did you cope with the situation – take loan

76 - 15 33 0 - 73 73 20 100 26 0 18 10 69 37

Catch fish/rat/crab etc 5 0 30 0 0 - 0 0 10 0 0 7 2 4

Near/sometime starvation/take meal only

once

13 0 20 56 0 - 0 0 0 56 0 6 10 29 13

Begging 0 0 - 10 0 - 0 0 5 6 0 1 1 2 2

Any other 7 100 35 0 100 - 27 28 65 12 100 69 78 0 44

120

Table 5.5: Some quantification of qualitative questions (Percentage of households)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

If the Job card is generally with the card holder, what is the reason for the same?

Sarpanch or Sachiv kept with themselves either for

security purpose or to make entries or attendance

30 0 0 0 0 22 0 92 95 70 19 0 8 6 19 0 23

Not applicable, no response or reasons not known 70 100 100 100 100 78 100 8 5 30 81 100 92 94 81 100 77

Is there any authority that monitors the functioning of the NREGA administration?

Contractor/Supervisor/Manager/Engineer 26 6 16 21 100 11

GP member/Panchyath secretary/RD Department 14 70 100 100 40 100 100 72 86 40 55 49

Name not specified 11 100 7

Do not know whether editing is done 49 11 100 21 7 12

Some Govt. Officer 13 60 5 14 60 24 11

Any Other or no reply 100 79 11

What complaint lodged to the GP, Programme officer or other officials?

For the provision of drinking water 5 0

Complaint for returning job card 5 0

Complaints for less wage payment or late payment 53 62 10 0 0 0 0 0 0 0 0 66 0 0 0 0 12

Complaint against contractors/secretary for not functioning properly

11 1

Complaint lodged but not able to specify properly or

verbal complaint lodged

26 29 2 15 10 100 5 1 11 12

Complaint was not lodged 38 90 100 71 100 98 85 90 95 34 100 100 89 100 74

Any action being taken on the complaint lodged?

They took action quickly 3 43 19 1 30 37 8

They assured that proper care will be taken next time and will not give any opportunity for complaint next

time

1 8 1

Either no action being taken or not sure whether any

action was taken on the complaint

96 2 100 100 100 25

No response 57 90 100 81 100 99 70 63 100 100 100 100 66

121

Table 5.5: Some quantification of qualitative questions (Percentage of households) – Contd.

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

IF you did not have sufficient food last year what do you think are the reasons?

No opportunity for work, especially in the summer

season

57 55 70 50 5 50 56 5 16 20 80 29

Low household income and low purchasing power 7 50 50 41 23 20 12

Earning members having bad habits like drinking 2 0

Low wage rate 15 30 6 16 4

Rainy season caused fallen of kaccha house 4 27 28 4

Others like no access to PDS food, indebtedness,

health problem and so on

15 19 2 100 100 16 0 38 42 21

Sufficient food was there 100 95 98 100 95 31

What problems other than food did you face during the last year?

Health problem 31 11 25 66 65 44 17 5 11 17

Poor economic condition, lack of purchasing power for other necessities

29 30 50 30 73 28 7 20 20 18

Unemployment 14 10 8 16 35 5

Education expenditure too high 6 11 34 5 36 3 12 6 7

Other problem including shelter, water, cloth and so on 18 36 25 30 20 27 25 11 23 80 18

No response 3 2 19 50 6 5

No Deprivation 100 70 100 100 100 29

Your suggestions to improve NREGA functioning?

Should increase wage rate and number of working days and work should be available throughout the year

50 51 35 90 100 12 10 20 100 57 10 5 40 36

Payment should be made within a week at the time of

work

5 8 30 26 5 10 25 7

Hundred days guarantee work and stipulated minimum wages should be ensured in practice

20 15 6 22 4

Any other 25 20 18 7 20 25 100 6 59 17

New types of work should be added 6 24 4 20 6 4

Better monitoring and proper measurement with

suitable timing of the work

32 7 38 28 20 2 25 21 20 12

Transparency and accountability in implementation 30 33 12 15 6

Better arrangement / worksite facilities 35 20 22 15 6

Compulsory work allocation for exclusively landless 100 6

Awareness towards Government schemes/ Rural development programmes/ legal rights in MGNREGA

20 15 2

122

Chapter 6

MGNREGA Impact on Village Economy

This Chapter is based on group discussion held among the ten villages that were surveyed in

each state. Our study carried out group discussion at the village level among the Panchayat

members and other learned people in the village at the time of field survey during the reference

year 2009. Our selected sample was 5 districts in each state and 2 villages from each district. In

this way we had group discussion in 10 villages in each state where study was carried out. The

results are present for 16 states and 160 villages. The issues discussed in the group discussion

were especially focused on the infrastructure available within the selected villages; the

implementation issues of MGNREGA; how MGNREGA has affected the village economy;

MGNREGA’s effect on agricultural wages and cost of production etc.

6.1 Infrastructure available within the village

Among the villages surveyed, most of the villages were connected with the city or nearby town

by a pucca/metal road (Table 6.1), except the case of Bihar where 3 out of the 10 villages were

not connected by pucca road. The villages that were not connected with pucca road their average

distance of un-metal road was around 3 kilometers. About the railway connectivity, only 9 per

cent of the selected villages or less than one out of the ten villages had railway connectivity.

Only in Kerala, 5 out of 10 villages had railway connectivity. The average distance of selected

villages to the nearest railway connectivity was around 31 kilometers (Table 6.1.3). The distance

for the railway connectivity was higher among the hilly terrain states like Himachal Pradesh and

Sikkim and it was higher for Chhattisgarh among the other selected states. More than 90 per cent

of the villages had telephone access while only 50 per cent of them had access to post office

within the village. The average distance to the post office in those selected villages where the

facility was not available within the village, it was available at an average distance of 4

kilometers. Only in Kerala, all the villages where group discussion was held had post office

facility within the village.

123

About access to institutional credit, around one half of the villages surveyed had cooperative

credit society within the village and another 15 per cent had commercial or regional rural banks

(RRB) within the village. Others who did not have bank access within the village had to travel 5

to 8 kilometers for the same. Only Sikkim and Kerala were the two states where all the selected

villages had cooperative society within the village. In Madhya Pradesh, there was no village

having the post office facility while only 20 per cent of the villages in Bihar, Andhra Pradesh,

Madhya Pradesh and West Bengal had cooperative society existing within the village periphery.

The APMC or agricultural produce market was available within an average distance of 11

kilometers at the aggregate while in Himachal Pradesh its distance was found up 36 kilometers

and in Sikkim it was available within a distance of 22 kilometers. Majority of the villages had

some self help group (SHG) within the village. Similarly, almost all the villages had access to

primary or secondary school within the village or in the nearby periphery. Primary health centre

was accessible either within the village or within the range of 4 kilometers while proper hospital

was available within 8 kilometers. Gram Panchayat Office (GPO) and Fair Price Shop (FPS)

were mostly available within the village or in the nearby periphery. In all the above infrastructure

indicators, Kerala was at the top, while Bihar, Madhya Pradesh and Chhattisgarh were at the

bottom.

Thus surveyed villages had mixed picture with some villages having perfect infrastructure like

road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel

some distance to approach the same.

6.2 Changes in the occupation structure in the selected villages

We tried to capture the structure of occupation in the selected villages and change that has

occurred during the last one decade. At the aggregate, around 40 per cent of the households in

the villages were cultivators and another 33 per cent were working as agricultural labourers

during the reference period and thus adding up the dependency of all households on the

agriculture sector up to 73 per cent (Table 6.2). Around 5 per cent were working in

manufacturing or mining and rest of the 20 per cent were working in service sector like

construction, trade, business, transport and other services. A slight change in the occupation has

been observed during the last ten years period. Agriculture occupied around 80 per cent of the

124

workforce in the selected villages during the year 2001, while manufacturing had no change

having 5 per cent share around that time as well while trade and services occupied only 15 per

cent share in 2001 compared to 20 per cent seen during the reference period. These results from

our primary survey are in consonance with the occupation structure revealed by the secondary

sources, e.g., Agriculture Census data and Agricultural Statistics at a Glance.

Comparing the occupational structure among different states, the data reveals interesting trends.

The highest percentage of households as cultivators were found in Haryana, followed by

Maharashtra, Karnataka, Punjab and Uttar Pradesh while their percentage was lowest in West

Bengal, Assam, Kerala, Bihar and Gujarat during the reference period. The highest percentage of

households working as agricultural labourers were found in Chhattisgarh followed by Andhra

Pradesh and West Bengal while Himachal Pradesh, Assam and Gujarat observed lowest

percentage of households working as agricultural labourers during the reference period. The

overall households working in agriculture topped in Haryana, Andhra Pradesh, Maharashtra and

Madhya Pradesh while lowest percentage was seen in Assam, Bihar and Gujarat. During the

period of a decade from 2001 to 2009, the percentage of households working in agriculture

declined by 2 to 6 per cent in different states. The proportion of households working in non

agriculture sector at the aggregate averaged around 26 per cent during the reference period while

it was only 20 per cent in 2001. The highest percentage of households working in non agriculture

was found in Assam, Bihar, Himachal Pradesh, Kerala, Rajasthan and West Bengal. The lowest

percentage of households working in non agriculture was worked out in Haryana, Andhra

Pradesh, Maharashtra, Madhya Pradesh and Chhattisgarh.

6.3 Changes in cost and wage rate in agriculture and non agricultural sector

The observations collected through village group discussion further substantiate our findings of

household survey data. The prevailing wage rates in agriculture were fluctuating widely both

across the states as well as across gender. The prevailing average wage rate in agriculture

according to our group discussion data was around 121 for male and around 94 for female at

the aggregate (Table 6.3). The corresponding figures according to our household survey data for

male and female, respectively were 104 and 84 for the participants and 107 and 84 for the

non participants. In our group discussion, the wage rate for agriculture labour topped in Kerala

125

(above 200) followed by Haryana (between 150-200), Andhra Pradesh, Punjab, Rajasthan,

Gujarat, Himachal Pradesh, Karnataka and Bihar ( 100-150) and the states having lowest wage

rates were Uttar Pradesh, Madhya Pradesh, Chhattisgarh, Maharashtra, West Bengal, Assam and

Sikkim ( 50-100).

In comparison, prevailing wage rate in non agricultural sector were much higher and the level of

skilled wages was almost double that of unskilled wages (e.g. electrician, plumber, construction,

mining). The average wage rate for male at the aggregate was 142 for non agriculture unskilled

labour, 183 for construction work, 167 for mining work, 224 for the trained electrician,

239 for the plumber and 284 for the pump-set boring. Comparing the wage rate over the last

five years, i.e. since the time MGNREGA has come into implementation, the wage rate in

agriculture sector has increased by slightly less than 50 per cent for male and slightly above 50

per cent for the female (Table 6.3.1). By the same estimates, wage rate for unskilled as well as

skilled labour in the non agricultural sector increased by slightly less amount compared to

agriculture labour except the wage rate in mining during the same time period. The wage rate for

unskilled labour in non agriculture and construction work increased slightly less than the wage

rate increase in agriculture while wage rate for skilled labour in mining increased slightly more

than agriculture. The wage rate for technical work like electrician, plumber and pump set boring

increased by less than that of agriculture (between 35 to 47 per cent). Thus, increase in wage rate

in agriculture more than most of the other activities within the village indicate the enhanced

demand for wage labourers due to employment works in MGNREGA that goes parallel with the

agriculture sector thereby causing a competition in the labour market for the agriculture sector.

Comparison of wage rate increase in agriculture versus non agriculture sector in different states

as revealed by our group discussion shown in Tables 6.3 and 6.3.1 presents interest trends. The

states that observed increase in wage rate in agriculture more than non agriculture sector

especially for the skilled wages, e.g., electrician, plumber etc., were Bihar, Sikkim, Andhra

Pradesh, Kerala, Madhya Pradesh, Chhattisgarh, Punjab, Himachal Pradesh and Rajasthan. On

the other hand, agriculture wages increased less than that of skilled labour force in non

agriculture sector in the states of Karnataka, Uttar Pradesh, Haryana, Maharashtra, Gujarat and

West Bengal. At the overall agriculture wages (male) increased by 49 per cent compared to

126

combined skilled wages that increased by 41 per cent during the period before to after

MGNREGA.

Similar to the change in wage rate there was around 40 to 50 per cent hike in the cost of

agricultural operations also (Tables 6.4 and 6.4.1). Machine charges like tractor or charges for

manual operations like ploughing, leveling, weeding and transplantation per acre increased from

45 to 55 per cent during the period before to after MGNREGA. Charges for ploughing increased

from 620 in 2005 to 920 in 2009. Similarly, weeding charges increased from 594 to 862

and threshing of paddy charges increased from 1084 to 1459 during the same time period.

Overall, increases in charges for agricultural operations per acre on an average were almost

similar to increase in agricultural wages as overall wages observed an increase of around 49 per

cent compared to around 46 per cent increase in cost of per acre agricultural operations as per

our group discussion data.

6.4 Various changes in village economy after implementation of MGNREGA

Table 6.5 presents some aspects of MGNREGA implementations. There has been a lot of hue

and cry on shortage of labour force in the agricultural sector because of the implementation of

MGNREGA programme. In the group discussion, we especially discussed this point with the

villagers. Out of the 160 villages where group discussion was held in more than 90 villages

(around 57 per cent of the villages) we found that there was truly shortage of labour in

agriculture during few months of the reference year. The shortage has further increased after the

implementation of MGNREGA as around more than 100 villages constituting around 63 per cent

of all the villages where group discussion was held indicated shortage of agricultural labour has

increased after the implementation of MGNREGA. In majority of the villages the shortage of

labour was observed during the sowing and harvesting months of kharif and rabi seasons

especially in the months of July, August and September and March and April. This was more so

after the implementation of MGNREGA. The shortage of labour was expressed in all the states

while out of ten villages where group discussion was held in each state shortage of agriculture

labour was found in more than five villages, in the states of Karnataka, Uttar Pradesh, Sikkim,

Andhra Pradesh, Kerala, Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra, Himachal

Pradesh, Gujarat and West Bengal in the post MGNREGA period. Out of 16 states where group

127

discussion was held, shortage of labour was found less severe only in Bihar, Assam, Haryana and

Rajasthan where less than 5 villages expressed shortage of labour after the implementation of

MGNREGA.

The majority of villagers were of the view that after MGNREGA implementation cost of

production in agriculture has increased by 10 to 20 per cent because of scarcity of labour.

Around 63 per cent villages expressed increase in cost in the agriculture sector by 10 to 20 per

cent in the post implementation of MGNREGA Programme. The villages where participants in

the discussion expressed cost increase by 20 to 50 per cent constituted only 20 per cent of the all

villages where group discussion was held while cost increase by more than 50 per cent was

expressed by 8 per cent of the villages. Among the selected states, only in Rajasthan, Kerala and

Uttar Pradesh more than 20 per cent of the villages participating in discussion indicated increase

in agricultural wages by more than 50 per cent after the implementation of MGNREGA. To our

question on how the wage rate of casual labour has changed during the last five years after

implementation of MGNREGA, around 84 per cent of the discussants pointed out that rate of

change in wages have increased and another 13 per cent indicated that rate of change in wages

after implementation of MGNREGA have remained constant while only 3 per cent were of the

view that the rate of change in wages have come down.

Discussion was held on labour migration issues. On the question, whether workers who earlier

migrated out of the village to work in city are now coming back to work in MGNREGA, only 24

per cent discussant agreed that it was true while same percentage of participants expressed the

opposite view that in the post MGNREGA period the exodus of labour to the cities is continuing

or the trend has increased because the wage rate in the city is much higher than that existing

under MGNREGA. The trend of villagers returning back to the village to work in MGNREGA

was found more prevalent in Andhra Pradesh, Himachal Pradesh, West Bengal, Bihar and

Karnataka while reverse was the case in Gujarat and Kerala. Around 20 per cent of the villages

indicated that the migration is happening both the ways, some people are retuning back to the

village to work under MGNREGA but some others are migrating to the cities or town because of

wage difference in MGNREGA and manual work in the city/town. Against all the above trends

around 41 per cent of the participating villages in the discussion indicated that MGNREGA has

128

not made any significant changes in the migration pattern in the village. The states in which no

change in migration trends came up predominantly were Madhya Pradesh, Chhattisgarh, Punjab,

Gujarat and Sikkim.

Another point of debate was how the MGNREGA has affected living standards of villagers, a

clear majority indicated that MGNREGA has not been successful in raising their living standards

or their consumption level and the reasons was quoted that the programme has not provided

enough numbers of days of work to make a significant dent on the poverty level, although a

minority of them were of the view that MGNREGA has been successful in doing so, to some

extent. The latter ones indicated that MGNREGA has improved living standards by providing

work within the village and by ensuring same wage rate to female as equal to that of male.

To another question, whether school enrollment or attendance has increased with MGNREGA,

54 per cent indicated no while 46 per cent expressed yes. Those who said yes pointed out that as

they were now getting better payment so they could afford to send their children to school now.

Whether MGNREGA has changed the trend of attached labour in agriculture, a significant

majority (44 per cent) said yes as people were getting better payments within the village

compared to agricultural work so the trends of attached labour for the agricultural work were

declining.

Has MGNREGA increased people awareness towards Government schemes, around 80 per cent

of the discussants were of the view that it has done so through increase in the showcasing by

television, newspaper, Gram Panchayat and Gram Sabhas and by other means like posters,

banners etc. Among the steps needed to ensure better implementation of MGNREGA, the major

ones suggested by the discussants included: increasing working days and wage rate; providing

food within the programme; allowing private land development through MGNREGA work for

longevity of the programme; and by providing proper information on various aspects of the

programme. Among the selected states, in Sikkim, Andhra Pradesh, Kerala, Rajasthan, West

Bengal, Uttar Pradesh, Maharashtra and Gujarat, a clear majority of the discussants expressed

that the household consumption as well as enrollment of children in the school have increased

after implementation of MGNREGA that has provided extra purchasing power in the hands of

129

the villagers. On the question of awareness almost all states observed increased awareness of the

households towards existing government schemes because of their participation in the gram

sabha and also because of joint working opportunities in MGNREGA.

6.5 Summary of the Chapter

The surveyed villages had mixed picture with some villages having perfect infrastructure like

road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel

some distance to approach the same. During the last ten years there has been slight change in the

occupation structure in the selected villages. The prevailing wage rates in agriculture were

fluctuating widely. Prevailing wage rate in non agricultural sector were much higher compared to

the agricultural sector and the level of skilled wages were almost double that of unskilled wages.

Comparing the wage rate after implementation of MGNREGA, the wage rate in agriculture

sector has increased by around 50 per cent. By the same estimates, wage rate for unskilled as

well as skilled labour in the non agricultural sector increased by slightly less amount compared

to agriculture labour except the wage rate in mining during the same time period. The wage rate

for technical work like electrician, plumber and pump set boring increased by less than that of

agriculture. Thus, increase in wage rate in agriculture more than most of the other activities

within the village indicate the enhanced demand for wage labourers due to employment works in

MGNREGA that goes parallel with the agriculture sector thereby causing a competition in the

labour market for the agriculture sector. A majority of the villages indicated shortage of

agricultural labour has increased after the implementation of MGNREGA.

On labour migration, there were opinions on both sides expressing that after MGNREGA people

are not migrating to the cities as work is available within the village but also stating that people

who migrated are not coming back to work in MGNREGA. Another point of debate was how the

MGNREGA has affected living standards of villagers, a clear majority indicated that

MGNREGA has not been successful in raising their living standards or their consumption level

and the reasons was quoted that the programme has not provided enough numbers of days of

work to make a significant dent on the poverty level. However, MGNREGA has certainly

increased people awareness towards Government schemes.

130

Table 6.1: Infrastructure available within the village (percentage of villages)

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Item Within the Village

Road connectivity 100 100 70 87.5 100 100 90 100 100 100 100 100 100 90 100 100 96

Railway connectivity 10 20 10 0 0 50 0 0 0 0 0 0 10 20 20 10 9

Landline or mobile connectivity 100 100 40 87.5 90 100 100 100 100 100 100 70 100 100 100 100 93

Post Office 80 30 10 75 80 100 60 0 20 70 40 60 70 70 80 50 56

Co-operative credit society 60 30 20 100 20 100 40 20 40 30 50 70 40 60 60 20 48

Regional Rural Bank 20 20 0 0 0 80 0 10 10 20 0 20 10 20 0 10 14

Commercial Bank 30 10 10 0 0 70 0 0 0 0 0 30 20 30 20 20 15

Agricultural Produce Market 0 100 0 62.5 0 50 0 0 0 10 0 0 0 0 0 10 15

Self Help Group Centre 100 100 30 62.5 80 80 70 40 50 100 30 100 100 100 40 70 72

School Primary 100 100 80 87.5 100 100 100 100 100 100 100 100 100 90 100 100 97

School Secondary 90 60 40 75 50 100 80 60 60 20 30 70 80 20 90 30 60

School Higher Secondary 70 30 10 37.5 0 90 50 20 10 20 0 30 40 0 20 10 27

Primary Health Centre 50 20 30 62.5 30 80 60 30 30 30 20 30 20 40 80 50 41

Hospital/Dispensary 10 10 10 50 0 90 40 0 0 20 20 30 40 10 20 10 23

Gram Panchayat Office 70 100 40 50 100 90 100 80 100 20 0 100 100 100 80 30 73

Fair Price Shop 90 50 50 87.5 70 70 40 0 10 90 0 100 80 80 90 50 60

Any other 0 0 0 0 100 0 0 0 0 0 0 20 0 0 100 0 14

131

Table 6.1.1: Infrastructure available nearest village (percentage of villages)

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Item Nearest Village

Road connectivity 0 0 30 12.5 0 0 10 0 0 0 0 0 0 10 0 0 4

Railway connectivity 90 80 90 100 100 50 100 100 100 100 100 100 90 80 80 90 91

Landline or mobile connectivity 0 0 60 12.5 10 0 0 0 0 0 0 30 0 0 0 0 7

Post Office 20 70 90 25 20 0 40 100 80 30 60 40 30 30 20 50 44

Co-operative credit society 40 70 80 0 80 0 60 80 60 70 50 30 60 40 40 80 53

Regional Rural Bank 80 80 100 100 100 20 100 90 90 80 100 80 90 80 100 90 86

Commercial Bank 70 90 90 100 100 30 100 100 100 100 100 70 80 70 80 80 85

Agricultural Produce Market 100 0 100 37.5 100 50 100 100 100 90 100 100 100 100 100 90 85

Self Help Group Centre 0 0 70 37.5 20 20 30 60 50 0 70 0 0 0 60 30 28

School Primary 0 0 20 12.5 0 0 0 0 0 0 0 0 0 10 0 0 3

School Secondary 10 40 60 25 50 0 20 40 40 80 70 30 20 80 10 70 40

School Higher Secondary 30 70 90 62.5 100 10 50 80 90 80 100 70 60 100 80 90 73

Primary Health Centre 50 80 70 37.5 70 20 40 70 70 70 80 70 80 60 20 50 59

Hospital/Dispensary 90 90 90 50 100 10 60 100 100 80 80 70 60 90 80 90 78

Gram Panchayat Office 30 0 60 50 0 10 0 20 0 80 100 0 0 0 20 70 28

Fair Price Shop 10 50 50 12.5 30 30 60 100 90 10 100 0 20 20 10 50 40

Any other 100 100 100 100 0 100 100 100 100 100 100 80 100 100 0 100 86

132

Table 6.1.2: Infrastructure available nearest village, average distance (percentage of villages)

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Item If Nearest Village, Average Distance (kms.)

Road connectivity 0 0 6 45 0 0 2 0 0 0 0 0 0 2 0 0 3

Railway connectivity 14 12 13 112 19 9 22 33 59 - 5 23 102 19 16 14 31

Landline or mobile

connectivity

0 0 3 30 4 0 0 0 0 0 0 4 0 0 0 0 3

Post Office 4 4 2 16 6 0 7 5 4 3 2 4 2 2 5 2 4

Co-operative credit society 13 4 2 0 7 0 4 4 5 2 6 4 4 12 9 4 5

Regional Rural Bank 13 8 7 13 10 6 5 4 7 4 5 6 8 12 12 6 8

Commercial Bank 5 9 6 14 12 5 6 6 5 4 5 8 10 12 12 6 8

Agricultural Produce Market 14 0 4 22 15 7 12 6 7 1 5 13 36 17 15 3 11

Self Help Group Centre 0 0 3 19 10 10 4 4 4 1 5 0 0 0 6 3 4

School Primary 0 0 3 1 0 0 0 0 0 0 0 0 0 3 0 0 0

School Secondary 3 2 3 17 4 0 5 1 2 1 5 6 1 12 2 4 4

School Higher Secondary 3 5 6 15 6 3 4 4 4 1 4 5 5 12 9 5 6

Primary Health Centre 5 7 2 18 6 3 4 3 2 2 2 5 6 6 3 5 5

Hospital/Dispensary 13 14 4 16 10 3 7 9 5 2 5 4 12 14 9 8 8

Gram Panchayat Office 9 0 2 10 0 7 0 0 0 2 0 0 0 0 3 4 2

Fair Price Shop 18 3 1 30 9 6 14 4 1 1 3 0 1 2 3 2 6

Any other 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

133

Table 6.2: Occupational structure (% of households in the village)

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

ha

rash

tra

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Occupation Reference

period

Cultivators 2009 54 50 22 49 44 21 65 43 27 21 51 59 43 24 41 20 40

2001 56 53 31 51 46 28 65 48 31 26 55 61 - 25 30 20 42

Agricultural Labour 2009 31 34 27 36 49 37 31 45 56 12 32 31 10 29 21 46 33

2001 31 37 31 36 49 60 33 35 62 11 35 31 - 26 30 46 37

Household Small

Industry 2009 0 1 3 2 2 7 1 0 1 3 1 1 5 6 1 2 2

2001 0 1 2 2 2 3 1 4 1 4 1 1 - 4 2 2 2

Other

Manufacturing./mining 2009 6 2 3 1 2 8 0 0 0 0 2 0 0 5 7 8 3

2001 5 1 5 0 2 0 0 7 0 0 2 0 - 4 7 8 3

Construction 2009 3 10 17 3 1 12 1 7 4 35 10 4 14 4 14 11 9

2001 2 6 12 2 0 5 1 6 4 34 5 4 - 4 16 11 7

Trade, Commerce and

Business 2009 3 2 7 5 0 5 1 2 2 19 2 2 5 2 3 6 4

2001 3 1 5 5 0 5 1 0 1 17 1 1 - 1 3 6 3

Transport and

Communication 2009 1 1 11 3 2 4 1 0 5 5 1 1 5 2 2 2 3

2001 1 0 9 3 1 0 0 0 0 3 1 1 - 2 2 2 2

Other Services 2009 2 1 10 2 0 5 3 3 3 5 1 2 18 9 12 6 5

2001 1 1 6 2 0 0 2 0 2 4 1 1 - 9 11 5 3

Total 2009 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

2001 100 100 100 100 100 100 100 100 100 100 100 100 - 100 100 100 100

134

Table 6.3: Wage rates for different activities (average of all villages) ( )

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

r

h

Ass

am

Pu

nja

b

Ma

ha

rash

t

ra

HP

Gu

jara

t

Ra

jast

han

Wes

t

Ben

ga

l

Ag

gre

ga

te

Activity Reference period (2009)

Prevailing

Agricultural Wages

Male 122 60 122 85 150 269 187 80 80 88 150 70 129 127 140 84 121

Female 69 40 98 80 94 204 165 70 70 78 70 48 121 112 111 73 94

Prevailing Non

Agricultural Wages

Male 157 98 130 203 125 331 206 80 80 96 150 103 130 150 149 85 142

Female 84 75 123 145 64 216 188 70 70 84 70 71 122 110 115 72 105

Construction Male 226 120 148 216 155 358 248 250 200 120 160 146 129 185 154 114 183

Female 114 100 106 161 106 253 200 90 74 125 125 131 85 128

Mining Male 200 140 125 100 325 200 85 150 76 230 238 130 167

Female 120 100 75 325 150 75 100 76 150 133 100 128

Other

skilled

work

Electrician Male 175 100 250 231 231 356 174 300 250 150 300 270 130 224

Female 146 213 179

Plumber Male 214 150 400 219 195 350 195 250 250 150 350 192 245 246 272 141 239

Female 188 175 162 175

Pump-set

boring

Male 321 120 400 94 120 317 240 150 913 125 350 400 146 284

Female

135

Table 6.3.1: Wage rates for different activities (average of all villages) ( )

Sta

tes

Ka

rna

tak

a

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

r

h

Ass

am

Pu

nja

b

Ma

ha

rash

tr

a

HP

Gu

jara

t

Ra

jast

han

Wes

t B

eng

al

Ag

gre

ga

te

Per

cen

t

cha

ng

e fr

om

bef

ore

to

aft

er

MG

NR

EG

A

Activity Before MGNREGA 2005

Prevailing Agricultural

Wages

Male 78 38 67 55 94 193 144 60 60 70 80 49 88 81 81 62 81 49.5

Female 40 29 54 55 52 134 115 60 50 60 50 31 79 64 60 51 61 52.6

Prevailing Non

Agricultural Wages

Male 98 70 87 133 72 238 147 60 60 75 100 74 88 80 78 63 95 49.2

Female 55 50 40 110 39 156 126 60 50 65 60 50 79 65 59 52 70 50.5

Construction Male 153 100 80 156 128 256 182 200 150 100 105 105 88 120 87 86 131 39.7

Female 75 80 50 130 69 150 140 80 58 79 80 66 60 86 49.7

Mining Male 100 80 50 75 200 133 75 100 54 185 144 100 108 54.2

Female 60 80 50 150 100 65 75 48 120 73 75 81 56.7

Other

skilled

work

Electrician Male 100 65 200 154 158 238 118 250 200 120 200 220 93 163 37.9

Female

Plumber Male 143 80 200 168 142 238 134 250 200 120 250 93 200 150 162 104 165 45.0

Female

Pump-set

boring

Male 179 70 200 70 85 300 188 120 695 105 225 261 105 200 42.0

Female

136

Table 6.4: Prevailing labour charges for agricultural operations (average of all villages) ( /day)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

(R

s/acre

)

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

(Rs/

acr

e)

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

(Rs.

/day

)

Ag

greg

ate

(Rs

per

acr

e)

Per c

en

t

ch

an

ge f

rom

befo

re t

o a

fter

(Rs

per

acr

e)

Activity Reference period 2009

Ploughing 222 900 115 93 870 320 250 90 80 80 990 381 350* 339* 531** 181 920 48.9

Leveling 230 300 225 93 625 340 250 80 70 80 3455 348 340* 325* 44** 191 1460 54.5

Weeding 87 720 115 93 1690 220 215 70 70 80 113 925 298 116 120 81 139 862 45.1

Paddy transplanting 108 800 125 93 1525 221 2000** 90 90 75 1420 1408 128 110 88 116 1288 54.1

Harvesting of wheat 87 1000 150 93 2000** 80 70 75 1130 540 128 125 155 81 97 890 48.8

Harvesting of paddy 143 650 150 93 1260 257 2200** 80 80 75 1100 1021 128 120 138 88 126 1008 53.9

Harvesting of grams 97 960 150 93 675 70 70 75 425 128 150 81 97 687 44.9

Harvesting of pigeon pea 150 93 80 75 104 150 81 100 -

Harvesting of ragi 138 170 75 1500 104 150 105 835 103.7

Harvesting of jowar 108 80 75 700 116 115 152 95 700 27.3

Harvesting of maize 110 140 93 750 70 75 673 128 115 145 81 102 712 34.6

Cane-cutting 100 93 2250 192 75 3217 128 150 88 117 2733 11.3

Harvesting other crops 100 93 200 192 80 2050 128 158 88 132 2050 53.2

Digging of potatoes 100 120 93 80 90 128 150 88 102 -

Threshing of paddy 123 100 93 1940 200 70 70 979 128 120 325* 88 112 1459 34.6

Threshing of wheat 133 100 93 250 180 70 70 90 724 128 350* 352* 88 124 724 22.7

Winnowing of

wheat/paddy

100 100 93 595 300 60 60 90 350 128 325* 346* 88 116 473 51.6

Note: * Rs per hour of machinery operation like tractor etc.

** Rs per acre

137

Table 6.4.1: Prevailing labour charges for agricultural operations (average of all villages) ( /day)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

(R

s/acre

)

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

Ass

am

Pu

nja

b

Ma

hara

shtr

a

(Rs/

acr

e)

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

(Rs.

/day

)

Ag

greg

ate

(Rs

per

acr

e)

Activity Before MGNREGA

Ploughing 2005 119 600 90 58 570 200 120 60 65 65 685 315 200* 217* 318** 121 618

2001 83 65 46 415 150 70 50 50 45 480 273 150* 132* 234** 92 448

Leveling 2005 156 200 94 58 365 225 120 45 42 65 2270 300 195 215 91 123 945

2001 131 70 46 245 175 70 40 34 45 1450 266 166 137 60 97 848

Weeding 2005 49 540 58 1090 127 100 50 50 65 82 663 274 67 83 58 97 594

2001 33 46 700 78 55 40 40 45 475 241 55 52 41 72 588

Paddy

transplanting 2005 68 580 110 58 1075 141 1200** 70 70 60 800 890 89 70 64 83 836

2001 41 80 46 788 97 800** 60 60 40 572 79 55 47 63 680

Harvesting of

wheat 2005 47 700 110 58 1200** 50 50 60 725 370 89 78 103 58 66 598

2001 34 80 46 800** 40 40 40 280 79 55 76 41 51 280

Harvesting of

paddy 2005 77 400 110 58 795 168 1400** 60 60 60 750 675 89 70 80 64 85 655

2001 63 80 46 595 114 1000** 50 50 40 475 79 50 55 47 65 535

Harvesting of

grams 2005 51 700 110 58 410 50 50 60 313 89 93 58 67 474

2001 41 50 46 350 40 40 40 225 79 70 41 48 288

Harvesting of

pigeon pea 2005 58 50 60 72 100 58 60 -

2001 46 40 40 64 75 41 48 -

Harvesting of

ragi 2005 128 120 60 700 72 100 87 410

2001 88 65 40 400 64 70 64 233

Harvesting of

jowar 2005 66 70 60 550 80 65 104 69 550

2001 49 60 40 400 71 50 66 55 400

Harvesting of

maize 2005 74 120 58 575 60 60 483 89 76 86 58 77 529

2001 55 75 46 425 50 40 333 79 60 60 41 57 379

Cane-cutting 2005 80 58 1810 100 60 3100 89 100 64 77 2455

2001 60 46 1295 80 40 2200 79 75 47 61 1748

Harvesting

other crops 2005 80 58 125 100 70 1338 89 95 64 87 1338

2001 60 46 75 80 50 825 79 65 47 65 825

Digging of

potatoes 2005 80 100 58 60 70 89 100 64 76 -

2001 60 80 46 40 50 79 60 47 59 -

Threshing of

paddy

2005 87 60 58 1500 150 60 60 668 89 85 190* 64 81 1084

2001 59 40 46 895 100 50 40 471 79 65 125* 47 59 683

Threshing of

wheat 2005 96 60 58 200 80 60 60 70 590 89 180* 229* 64 86 590

2001 66 40 46 125 50 50 40 50 475 79 100* 163* 47 61 475

Winnowing of

wheat/paddy 2005 60 60 58 390 200 50 50 70 233 89 180* 225* 64 80 312

2001 30 40 46 240 150 40 40 50 177 79 120* 156* 47 59 208

Note: * Rs per hour of machinery operation like tractor etc.

** Rs per acre

138

Table 6.5: Qualitative questions on changes in the villages during last one year (% of villages)

Sta

tes

Ka

rn

ata

ka

UP

Bih

ar

Sik

kim

AP

Ker

ala

Ha

rya

na

MP

Ch

ha

ttis

ga

rh

i

Ass

am

Pu

nja

b

Ma

hara

shtr

a

HP

Gu

jara

t

Ra

jast

ha

n

West

Ben

gal

Ag

greg

ate

Description Yes

Was there shortage of agricultural wage labour at some point during last year 80 100 30 75 70 35 70 35 30 38 20 80 30 60 70 91 57

After implementation of MGNREGA has there been a shortage of agriculture labour 70 80 30 75 70 70 40 70 70 36 60 70 60 70 50 94 63

After implementation of MGNREGA the cost of production in agriculture increased by 10 per cent because of scarcity of labour

30 10 35 13 70 15 80 80 80 68 60 50 30 50 30 28 46

Cost increased by 20 per cent 50 40 20 25 20 0 10 0 0 24 30 30 60 50 0 66 27

Cost increased by 20 to 50 per cent 20 30 40 63 0 50 10 20 20 8 10 20 10 0 20 6 20

Cost increased by 50 to 75 per cent 0 0 5 0 10 35 0 0 0 0 0 0 0 0 40 0 6

Cost increased by 100 per cent 0 20 0 0 0 0 0 0 0 0 0 0 0 0 10 0 2

Cost increased by more than 100 per cent 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

After implementation of MGNREGA labour who migrated earlier to town/city are coming back to work in the village

40 20 40 0 60 30 0 10 75 20 30 57 24

More labour is migrating from the village as wage rate in the town is higher than

wage rate under MGNREGA or other activities in the village

10 20 30 0 50 55 25 20 43 10 10 0 80 10 5 23

Some labour has come back to work in MGNREGA but others are moving to the

town/city because of wage differential

20 20 40 10 0 10 30 30 25 60 30 26 19

There is no change in labour migration by MGNREGA activities 0 30 20 100 10 15 85 80 58 90 40 20 70 30 0 41

After MGNREGA change in wages of casual labourers has increased 70 100 60 100 80 100 20 90 90 80 70 100 90 100 100 100 84

After MGNREGA change in wages of casual labourers has decreased 10 0 20 0 10 0 0 0 0 0 0 0 0 0 0 0 3

After MGNREGA change in wages of casual labourers remained same 20 0 20 0 10 1 80 10 10 20 30 0 10 0 0 0 13

The trend of people living in village and going to work outside daily has increased 30 40 40 0 40 80 20 15 20 35 30 30 50 70 20 0 33

The trend of people living in village and going to work outside for longer period has

increased

20 20 40 0 40 5 30 20 20 0 20 10 0 60 10 6 19

Has living standard improved in your village since the introduction of MGNREGA 40 70 20 100 100 80 50 15 15 54 20 70 10 50 80 100 55

After MGNREGA have you witnessed increase in household consumption in village 40 100 20 100 100 93 30 20 20 35 20 90 10 50 80 100 57

After MGNREGA have you witnessed more children are now going to the school 30 40 30 100 90 40 70 0 0 45 0 40 10 60 80 100 46

After MGNREGA, have you witnessed change in trend of attached labour in agriculture

40 30 15 13 100 75 0 60 60 54 50 30 10 70 0 94 44

After MGNREGA, have villagers’ awareness towards Government Schemes

increased

70 100 30 100 100 90 20 100 100 81 100 100 10 80 100 100 80

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Chapter 7

Concluding Remarks and Policy Suggestions

7.1 Introduction

National Rural Employment Guarantee Act, now Mahatma Gandhi National Rural Employment

Guarantee Act (MGNREGA from October 2, 2009) was passed in the year 2005. The basic

objective of the Act is to ensure livelihood and food security by providing unskilled work to

people through creation of sustainable assets. The Ministry of Rural Development strives to

implement the Scheme in the most transparent and effective way. Under the provisions of the

Act, the state has to ensure enhancement of livelihood security to the households in rural areas

by providing at least one hundred days of guaranteed wage employment to every household

whose adult members volunteer to do unskilled work. In-built with various transparency and

accountability measures and provisions for social audits this Act for the first time brings the role

of the State as provider of livelihood. The programme was implemented in 100 most backward

districts in the country in the first phase during the financial year 2006-07. The second phase

started from the beginning of the next financial year (1st April 2007) whereby another 100

backward districts were added into the list of district where MGNREGA was under

implementation. From the beginning of the next financial year, i.e., 1st April 2008, the whole

country including the Union Territories were brought under the umbrella of MGNREGA Act.

Thus from the financial year 2008-09, MGNREGA has been implemented in the whole country.

The MGNREGA Scheme has high expectations in terms of employment generation, alleviation

of poverty, food security, halting migration and overall rural development. As the scheme has

already completed 6 years of its functioning, there is a need for a study to evaluate the scheme

for its impact on rural poor. Based on this background the study is conceptualized with the

following objectives:

1. Measure the extent of manpower employment generated under MGNREGA, their

various socio-economic characteristics and gender variability in implementing

MGNREGA since its inception in the selected states.

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2. To compare wage differentials between MGNREGA activities and other wage

employment activities.

3. Effect of MGNREGA on the pattern of migration from rural to urban areas.

4. To find out the nature of assets created under MGNREGA and their durability.

5. Identification of factors determining the participation of people in MGNREGA

scheme and whether MGNREGA has been successful in ensuring better food security

to the beneficiaries.

6. To assess the implementation of MGNREGA, its functioning and to suggest suitable

policy measures to further strengthen the programme.

The study is based on both primary and secondary data. Primary data was collected from the

selected villages and households in 16 states as per the guidelines of the Ministry. From the each

selected state, five districts were selected, one each from the north, south, east, west and central

locations of the state. From each districts, two villages were selected keeping into account their

distance from the location of the district or the main city/town. From each selected village,

primary survey was carried out on 20 participants in MGNREGA and 5 non-participants working

as wage employed. In this fashion, from each state, 10 villages were selected and a total number

of 250 households were surveyed in detail with the help of structured household questionnaire.

In this way around 200 participants and 50 non participants were selected from each state and

data was collected in 16 states. The total sample consists of 3166 participants and 839 non

participants. The selected states were, Karnataka, Andhra Pradesh and Kerala in the South,

Himachal Pradesh, Uttar Pradesh, Haryana and Punjab in the North, Madhya Pradesh and

Chhattisgarh in the Central, Maharashtra, Gujarat and Rajasthan in the West, Bihar, and West

Bengal in the East and Sikkim and Assam in the North-east. The data was collected through

structured questionnaires. The data pertain to the Reference Period of January to December

2009.

In addition to household questionnaire, a Village Schedule was also designed to capture the

general changes that have taken place in the village during the last one decade and to take note of

increase in labour charges for agricultural operations after the implementation of MGNREGA.

The village schedule also has qualitative questions related to change in life style of the villagers

141

taking place during the last one decade. One village schedule in each village was filled up with

the help of a ‘Group Discussion’ with the Pachayat Members, Officials, educated and other well

informed people available in the village being surveyed.

7.2 Main findings

7.2.1 Total employment generated and their socio economic characteristics

In the three phases of MGNREGA implementation in India from 2006-07 to 2013-14 (up to

October) 81 crore households were issued job cards at the country as a whole out of which

around 34 crore households were provided employment averaging around 4.5 crore households

working in MGNREGA per annum that constitutes roughly around 30 per cent of the rural

households in the country as a whole. Andhra Pradesh, Uttar Pradesh and Rajasthan each

employed more than 3 crore households during this period. A total number of 1.5 thousand crore

man days of employment was generated by MGNREGA during the above mentioned time

period. The share of Scheduled Castes and Scheduled Tribes in the total person days generated

was 26.9 and 22.0 per cent, respectively while share of women in the total employment was 48.0

per cent.

At the aggregate, a total number of 45 person days of employment was provided by MGNREGA

whereas the target set under the programme is 100 days of employment per household. Highest

number of 54 days of employment that is slightly above 50 per cent of the target was achieved

only in the year 2009-10. Among the states, highest numbers of days of employment (60 to 70

days) was provided by the north-eastern states of Mizoram, Nagaland, Tripura, Sikkim and

Manipur. Rajasthan, Madhya Pradesh and Andhra Pradesh provided between 50 to 60 days of

employment. The other states like Chhattisgarh, Himachal Pradesh, Tamil Nadu, Karnataka,

Maharashtra, Uttar Pradesh, Jharkhand and Odisha provided 40 to 50 days of employment while

Haryana, Jammu & Kashmir, Uttarakhand, Gujarat, Kerala and Assam provided 30 to 40 days of

employment. The states that lied at the bottom included Bihar (31 days), Arunachal Pradesh,

West Bengal and Punjab (28 days, each) and Goa only 25 days of employment.

Out of the total 34 crore households working in MGNREGA during its full tenure, only 2.9 crore

households completed 100 days of employment. Around 25 per cent households working in

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MGNREGA completed 100 days in Mizoram, 20 per cent in Tripura, 18 per cent in Sikkim and

Nagaland each, 16 percent in Rajasthan and 14 per cent in Manipur. Tamil Nadu and Andhra

Pradesh were the other states where around 10 to 13 per cent households completed hundred

days of employment. Goa, Punjab and West Bengal were at the bottom where only less than 2

per cent households completed hundred days of employment. At the all India aggregate, only 8.4

per cent households completed hundred days of employment during the entire period of

MGNREGA in operation up till October 2013.

7.2.2 Number of projects completed and total amount spent

Water conservation was the leading activity which occupied around 24 per cent projects under

MGNREGA followed by rural connectivity projects 17 per cent, provision of irrigation 14 per

cent, drought proofing 13 per cent, land development 10 per cent each, renovation of traditional

water bodies and Micro irrigation 6 per cent and flood control 3 per cent. During the entire

period of MGNREGA, a total number of 1 crore projects were completed and around 2.9 crore

were ongoing. Thus, out of total 4 crore projects taken up under MGNREGA around 30 per cent

were completed and rest of 70 per cent were in progress. A total amount of 2,35,084 crore was

spent on the MGNREGA with an average of slightly less than 30 thousand crore every year.

Working out the total expenditure incurred per project it turns out around 59 thousand per

project for all MGNREGA works undertaken so far at the aggregate.

During the whole period of implementation of MGNREGA a total amount of 75 thousand crore

was spent on rural connectivity, 45 thousand crore on water conservation, 27 and 25

thousand crore on renovation of traditional water bodies and drought proofing, respectively, 17

thousand crore on provision of irrigation, 16 thousand crore on land development, 12

thousand crore on micro irrigation, 11 thousand crore on flood control and around 6 thousand

crore on other activities. At the aggregate, the highest amount per project was spent on

renovation of traditional water bodies 121 thousand per project that was closely followed by

112 thousand per project on rural connectivity. Expenditure on flood control lied on the third

place with an expenditure of 79 thousand per project. Micro irrigation had a spending of 53

thousand per project, followed by drought proofing 49 thousand per project, water conservation

47 thousand per project, land development 40 thousand per project and provision of irrigation

143

29 thousand per project. Thus, whereas water conservation topped in the total numbers of

projects undertaken but spending on per project was much less on water conservation compared

to rural connectivity that topped among all projects not only in the total amount spent but also

amount spent per project. State wise highest amount per project was spent in Manipur 297

thousand followed by Nagaland ( 245 thousand), Mizoram ( 269 thousand), Tamil Nadu

( 255 thousand), Assam ( 191 thousand) and Maharashtra ( 160 thousand). The states that lied

at the bottom in spending per project were Andhra Pradesh ( 18 thousand), Gujarat ( 41

thousand), Karnataka and Goa ( 48 thousand), Kerala ( 49 thousand), and Uttar Pradesh (

54 thousand) only.

7.2.3 Qualitative indicators of MGNREGA performance

During 2008-09 to 2013-14 (up to October), a total number of 10.52 crore muster rolls were

opened in the country out of which around 85 per cent were verified by the authorities who

carried out the auditing work. Social auditing of MGNREGA work of the Gram Panchayats (GP)

was held in around 87 per cent of the GPs during the above mentioned period. The social audit

was held in above 90 per cent GPs in Tamil Nadu, Madhya Pradesh, Kerala and Nagaland

whereas, it was held in less than 60 per cent GPs in Arunachal Pradesh, around 60 to 65 per cent

GPs in Jammu & Kashmir and Karnataka. The percentage of works inspected at the district level

was very low only 12 per cent whereas the works inspected at the block level was as high as 81

per cent. Almost half of the works were inspected at the district level in Arunachal Pradesh while

proportion of inspected works was half to 1/3rd

in Assam, Sikkim, Nagaland and Kerala. In rest

of the states, less than 1/3rd works were being inspected at the district level. Complaint redressal

system was adopted under MGNREGA and a total number of 215542 complaints were registered

in all the states out of which around 84 per cent were redressed. Complaint redressal was 100 per

cent in Goa, Arunachal Pradesh and Mizoram. It was less than 80 per cent in Madhya Pradesh,

Maharashtra, Odisha, West Bengal and Gujarat while in rest of the states above 80 per cent

complaints were redressed during the above mentioned period.

The Gram Panchayats are encouraged to make payments to the workers through banks or post

office. A total number of 41 crore individual and joint accounts were operative in banks and post

offices through which payments were made for MGNREGA works during the period 2008-09 to

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2012-13. It is interesting to note that out of total amount paid through banks and post offices in

MGNREGA during the period 2008-09 to 2012-13, the average amount paid through bank/post

office per account was 1.97 lakh. State wise, the highest amount paid per account was in

Nagaland ( 24 lakh), Meghalaya ( 9.5 lakh), Mizoram ( 6 lakh), Sikkim ( 5.8 lakh) and

Tripura ( 3.8 lakh). The lowest amount was paid in Tamil Nadu (only 3 thousand), Bihar ( 1

lakh) and Gujarat ( 1.2 lakh). According to the legislation on MGNREGA, if a member of a

household has not been provided employment after issuing him/her a job card after a lapse of 15

days, the GPs are supposed to provide unemployment allowance and such amount would be

borne by the concerned state government. During the period 2007-08 to 2013-14 (up to October)

unemployment allowance was due for 4.83 crore person days for which employment was not

provided to the job card holders but only 2478 days of allowance was paid that makes only 0.01

per cent days of unemployment allowance paid and it was not more than 0.04 per cent in any

state.

7.2.4 Household characteristics their income and consumption pattern

The average household size was 4.75 with participants having average family size of 4.7 and non

participants 4.9. The average numbers of earners in the family were 2.2 members among

participating families and 2.6 members among the non participating families. Similarly, the

number of members in working age (i.e., 16-60 years) was 74.4 per cent among participants and

73.7 per cent among non participants. Looking at the education status among the selected

households, the percentage of illiterate was around 1/3rd

among the participants and less than

1/3rd

among the non participants. On the overall, non participants were better educated compared

to participant household members. Looking at the caste distribution among the participating

households, the percentage of households belonging to Scheduled Caste (SC), Scheduled Tribes

(ST) and Other Backward Castes (OBC) was 34, 17 and 34 per cent, respectively while General

category had only 16 per cent proportion among the selected households.

The trends in occupation depict that among the participating households, the proportion of work

provided by MGNREGA was only a small proportion of their aggregate employment. Out of the

total man days employed per household including all the working members, the share of

MGNREGA varied between 12 to 32 per cent among different states. It was less than 15 per cent

145

in Karnataka, Kerala, Assam, Gujarat and West Bengal. Its proportion was between 15 to 25 per

cent in Uttar Pradesh, Sikkim, Madhya Pradesh, Chhattisgarh, Maharashtra, Himachal Pradesh,

Rajasthan, Haryana and Punjab. The share of MGNREGA in total employment was above 25 per

cent only in two states namely Bihar and Andhra Pradesh. At the aggregate, MGNREGA

provided 18 per cent share in the total employment among our selected households. Casual

labour in agriculture and non agriculture sector constituted more than 40 per cent share in

employment. Self employment in agriculture and livestock constituted around 20 per cent share

and self employment in business and regular salary had around 5 and 10 per cent share,

respectively in the total employment among the selected participants.

A glance on the household income statistics reveals that the estimated per household income of

non participant households was higher compared to participant households. On an average, the

selected non participant households earned 70 thousand per annum compared to 59 thousand

earned by the participating households. Comparing the sources of income across different

activities, wage income constituted a lion’s share in the income of both participating as well as

non participating households. Earnings from agricultural wages contributed around 17 per cent

followed by wage earnings from non agricultural activities 22 per cent, while wage earnings in

MGNREGA activities contributed only 12 per cent share in the total household income of

participants. In addition to wage earnings, income from self employment in agriculture and

livestock constituted around 17 per cent share of their household income while regular salaried

job contributed around 14 per cent share in the household income of the participating

households. Trends in share of various sources were somewhat similar in the case of non

participating households.

Majority of the states observed household income less than the aggregate average of 59

thousand. Ironically, the states that observed highest household income namely Kerala and

Assam, however, had much lower percentage coming from the MGNREGA activity less than 7

per cent in Kerala and only 3 per cent in Assam in the aggregate income. Highest share

contributed by MGNREGA in total household income was observed in Maharashtra (29 per

cent), followed by Haryana and Sikkim (25 per cent, each), Andhra Pradesh and Punjab (18 per

cent, each), West Bengal, Rajasthan, Madhya Pradesh and Uttar Pradesh (each having above 13

146

per cent share). The dispersion of income across households was highest for agriculture and

livestock income for both participant and non participant households while it was comparatively

less in MGNREGA activities indicating lesser amount of wage rate differentials in MGNREGA

as compared to casual wage rate in agriculture and non agricultural activities.

On average, per capita cereal consumption satisfied the 1200-calorie norm, i.e., total cereal

consumption surpassed 10.5 kgs per capita per month by both the participant and non participant

households. The average cereal consumption was measured at 11.1 kg per capita per month in

the case of participants and 11.6 kg per capita per month in the case of non participants. The

states that reported less than 10.5 kg cereal consumption were Bihar, Punjab, Maharashtra and

Rajasthan among both participants and non participants. Pulses consumption varied between 0.5

to 3 kg per capita per month among different selected states and it averaged around 1 kg among

both the participants and non participants. The diversification of consumption from cereals and

pulses towards edible oils, milk and high value products was visible from our data. The quantity

of high value commodities like milk and milk products, fruits and vegetables was higher for non

participant households compared to participant households as non participants income was also

higher compared to participant households.

Total monthly food expenditure among our selected sample averaged at 421 for the participants

and 455 for the non participants whereas NSS food expenditure for all India averaged around

600. The difference between participants and non participants was much higher in the non food

expenditure, especially in education, clothing and other items including medical and health. The

overall non food expenditure was 237 per capita per month among the participants compared to

271 among the non participants. Our non food expenditure was under estimated as is clear

from the much above NSS amount of 453. The difference could be due to under reporting and

may be few items missing in our questionnaire like conveyance, consumer services, various

entertainment goods, rent, taxes and other durable goods. Comparing food and non-food

expenditure, the proportion of food in total expenditure was 64 per cent among the participants

and 63 per cent among the non participants. In comparison, share of food expenditure in the NSS

data was 57 per cent of total expenditure that also indicate that our non food expenditure was

slightly under estimated. Looking at the concentration ratio, the Gini coefficient of income was

147

mostly higher than that of consumption for both participants and non participants. The, higher

variation in income compared to consumption shows the more vulnerability of the household in

the case of an external shock to the household income and the necessity of households to search

for some formal or informal sources of consumption smoothening.

7.2.5 Determinants of participation in MGNREGA

The logit function provided us the probabilities of the participation of a household in

MGNREGA activities. State level regression results showed that the households who had

alternate employment opportunities and those who had higher income contribution from other

activities had less incentive to work in MGNREGA. The coefficient for employment other than

MGNREGA was negative and significant in Sikkim, Haryana, Madhya Pradesh and

Chhattisgarh. Coefficient of income other than MGNREGA was significant and negative in

Madhya Pradesh, Chhattisgarh, Punjab, Maharashtra and Himachal Pradesh. The household size

had significant and positive sign in Karnataka, Andhra Pradesh, Kerala, Haryana, Madhya

Pradesh, Chhattisgarh, Punjab, Maharashtra and West Bengal indicating with increase in family

size there was more probability of household members working in MGNREGA among the

selected households. Household size had significant but negative relationship in Uttar Pradesh

and Himachal Pradesh indicating low participation at higher family size in these two states.

The value of assets and land ownership had negative sign in the regression indicating household

members with land ownership or better assets accumulation had less probability of participating

in MGNREGA activities. The coefficient was significant with a negative sign in Karnataka,

Uttar Pradesh, Sikkim, Madhya Pradesh, Assam, Punjab and West Bengal. On the opposite, if a

household owned an AAY or BPL card or if they belonged to Scheduled Caste or Scheduled

Tribe community they had higher possibility of entering into MGNREGA work. The coefficient

of dummy BPL was found positive and significant in Karnataka, Sikkim and in Haryana.

Similarly, coefficient of social characteristics (household belonging to SC, ST and OBC) was

found significant and positive in Sikkim, Andhra Pradesh, Chhattisgarh and Maharashtra. From

the household OLS regression, the most important and significant variable emerged was wage

rate in MGNREGA with a positive sign in almost all the states indicating that with higher wage

rate households preferred to work in MGNREGA.

148

Some interesting relations were observed in the member level logit regression. Among the

members in a household, those who worked in MGNREGA had a direct and significant

relationship with age and negative relationship with education. The implication is that older age

and less educated people preferred to work in MGNREGA as the latter is known providing soft

wages. Similarly, the dummy on sex indicates that the male members had higher probability of

working in MGNREGA compared to female members although female proportion in total work

force constituted around 45 per cent varying in its degree from state to state. The members with

BPL and AAY cards and members belonging to SC and ST community had better probability of

working in MGNREGA. The above findings were generally true across the states.

7.2.6 Work profile under MGNREGA, wage structure and migration issues

According to our survey data, on average, less than two members (1.7) per family were

employed under MGNREGA. Among the selected states, the average exceeded 2 members per

family working in MGNREGA in Sikkim, Gujarat, Chhattisgarh and Andhra Pradesh. It was

between 1.5 and 2 members in Karnataka, Haryana, Madhya Pradesh, Maharashtra and West

Bengal. The states that employed less than 1.5 members per family were Uttar Pradesh, Bihar,

Kerala, Assam, Punjab, Himachal Pradesh and Rajasthan. The highest numbers of members

employed under MGNREGA among the selected households was found 2.8 members in Sikkim

and lowest, 1.07 in Kerala. Out of 1.68 members employed under MGNREGA at the aggregate,

0.98 members belonged to male households and 0.70 members belonged to female households.

Only in Gujarat and Rajasthan, the numbers of female member per household working in

MGNREGA exceeded that of male and in Sikkim and Maharashtra their percentage was same.

Against the average of 1.68 aggregate members per family, the average was 1.47 for the SCs,

1.67 for STs and 1.53 for the OBCs. The SC and ST households’ average was highest 2.63 and

2.53 members in Gujarat and lowest 0.22 and 0.19 members in Bihar, respectively.

On an average, 68 days per household employment was generated among our selected

participants. The states that topped in employment generation among our selected participants

included Maharashtra (100 days), Haryana (94 days), Himachal Pradesh (92 days) and

Rajasthan, Sikkim and Gujarat (slightly above 80 days). The states that were slightly above or

149

below the national average were Madhya Pradesh, Karnataka, Kerala and Uttar Pradesh (between

80 to 60 days). The states that lied at the bottom were Bihar (32 days), Andhra Pradesh (43 days)

and Assam (48 days). Looking at the ratio of employment among the male and female workers,

numbers of days of employment was shared by male (37 days) and female (30 days) with a per

cent share of 56 for male and 44 for female.

Out of 16 states for which analysis is done only in 10 states information about households

completing 100 days of employment was available. Among these ten states, the percentage of

households who completed 100 days, only in Himachal Pradesh their percentage was

exceptionally high (85 per cent). In Haryana and Rajasthan, 48.5 and 44.5 per cent households

completed 100 days. In Karnataka and Sikkim around 1/4th

of the participant households

completed 100 days of employment. In Bihar, Assam, Gujarat and West Bengal only less than 5

per cent households completed 100 days and in Uttar Pradesh around 10 per cent households

completed 100 days. At the aggregate, only 1/4th

of the selected participants in these 10 states

completed 100 days. In other words, MGNREGA was not quite successful in providing social

security to the households as households had to depend on other activities for earning their

livelihood as MGNREGA provided only 18 per cent share of the total employment to the

selected households.

Looking at the wage rate on which employment was provided, average wage rate at the

aggregate was recorded at 100 and it was not particularly different among male and female.

The highest wage was recorded in Haryana ( 150), followed by Kerala ( 125), Punjab ( 123)

and Himachal ( 110). Among the selected states lowest wage rate was paid in Rajasthan ( 80),

Chhattisgarh ( 83) West Bengal ( 84) and Karnataka ( 86). However, in most of the states

actual wage rate obtained under MGNREGA was below the stipulated minimum wage rate fixed

by the states under the Minimum Wages Act 1948. The difference between the actual payment

and minimum stipulated wages was specifically high in Karnataka ( 33), Maharashtra ( 22),

Rajasthan and Assam ( 21), Madhya Pradesh ( 19), Andhra Pradesh and Punjab ( 14), Gujarat

and Haryana ( 12) and Bihar ( 10). Last but not the least, the average distance of work place

form the residence or village of the households was less than 2 kilometers in all the states with

few exceptions.

150

Among the surveyed households, the highest work under MGNREGA was concentrated on rural

connectivity which shared around 40 per cent of the total employment followed by water

conservation and water harvesting which shared 17 per cent of employment under MGNREGA.

Land development (12 per cent), renovation of traditional water bodies (11 per cent), flood

control and protection (8 per cent) and micro irrigation (5 per cent) were the other major

activities of employment under MGNREGA. On the question of how was the quality of the

assets created through MGNREGA work, a little less than half of the households indicated that

the assets created were very good while another half of them indicated that assets created were of

the good quality. Only less than 3 per cent households pointed out that the assets created were

bad or worst in quality. We enquired the selected households whether after registration if they

did not get employment did they receive any unemployment allowance, households indicated

that they did not receive any such allowance except in Maharashtra and West Bengal where

households received only a poultry amount as unemployment allowance.

Our statistics on migration indicates that around 0.20 members per family (with average size of

4.7 members) migrated because of not getting work under MGNREGA. Out of the selected

states, the numbers of per family members migrated because of not getting work averaged at

0.54 in Assam, 0.44 in Rajasthan, 0.31 in Madhya Pradesh and Maharashtra each, 0.20 in Andhra

Pradesh, Chhattisgarh and Himachal Pradesh, each and less than 0.1 members in rest of the

selected states. Thus, incidences of villagers’ migration in search of work despite having been

registered for MGNREGA were still recorded in the surveyed villages. However, there were also

incidences whereby around 0.12 members per family among the participant households returned

back to the village to work under MGNREGA at the aggregate who hitherto were working

elsewhere before the implementation of this Programme. The members retuning back to work

under MGNREGA was highest in the state of Bihar where around 0.65 members per family

returned back to work under MGNREGA after the implementation of the Act. Among other

states, the incidence was recorded in Andhra Pradesh, Rajasthan, Madhya Pradesh and

Maharashtra where, on average, 0.1 to 0.2 members per family returned back to work in

MGNREGA after implementation of the Act. Punjab, Haryana and Assam were the only states

where no such reverse migration incidences were recorded. On the overall, it is difficult to say

151

whether the MGNREGA programme has been successful in cutting down the incidences of

labour migration from villages in search of job. The majority of the households who returned

back to work in MGNREGA pointed out that they were now better off compared to earlier

working as a migrant labourer.

7.2.7 The functioning of MGNREGA – Qualitative aspects – (Field Survey)

The analysis of assets and borrowing points that participant households were much more

vulnerable compared to non participant households. Whereas, participant households owned

assets less than half that of non participant households, their borrowing level was almost double

that of non participant households. Not only was the loan amount higher for the participants,

their proportion of non institutional loan was also much higher. Checking with the financial

strength on borrowing, around 10 per cent of participating households indicated that they are

doing wage work for those with whom they are indebted, whereas 8 per cent of the non

participating households indicated the same. Around half of the selected households pointed out

that there was a cooperative society in their village but less than ¼th

of the households were

members of such society within their village. Similarly more than ⅔rd

majority of the household

agreed that there was at least one informal credit society or self help group in their village but

only ⅓rd

of the selected households were members of such societies. More than ¾th

of all

selected households had an account in the bank or post office but only 2 per cent of the selected

households had any financial assets, like stock, bond or share of a company. Similarly, less than

15 per cent participant households and around 20 per cent non participant households had a life

insurance policy.

On the qualitative questions, a majority of the households indicated that they did not have to pay

any bribe to get a job card issued. Regarding irregularities in the job card around 15 per cent

households at the aggregate indicated that either, no entry was made in the job card about the

work performed under MGNREGA or entries were missing or fake; entries were over written or

signature column was blank, while clear cut majority observed no such irregularities. Around 80

per cent of the household were given employment in response to their application for work. All

households who did not get work within 15 days indicated that they did not get any

152

unemployment allowances in lieu of not getting work within the period of 15 days after putting

up their application for work under MGNREGA.

On the system of payment of wages almost all participating households agreed that wage rate for

male and female was same. The payment system was both daily-wage basis and piece rate/task

wage basis. In majority of cases, work was measured on collective or team management basis

while in a thin majority it was measured on individual work basis. A majority of participant

households pointed out that wages were paid either fortnightly or monthly basis but around 12

per cent participants pointed out that they had to wait for a longer period or at least more than a

month to realize their wages from MGNREGA work. It is interesting to note that majority of the

participants (more than half of them) obtained their wages through bank. Another 40 per cent of

the participant indicated that they obtained wage through the post office. Only 5 per cent of the

interviewed household obtained their wages through Sachiv/Contractor/Others and this fact

makes MGNREGA programmes different from all other employment generation programmes

under operation in different states. Further with a few exceptions, the bank accounts were on the

individuals’ name working in MGNREGA. Among the irregularities in wage payments, the

participant households indicated that there was delay in wage payments after the work was

finished; the wage paid was less than the task performed and the participants faced problem in

accessing post office or bank account and lastly they were not aware on what basis wages were

determined in case of those whom wages were not paid on daily wage basis. Delay in wage

payment was reported by highest numbers of participants in Andhra Pradesh, Chhattisgarh,

Madhya Pradesh, Gujarat and Rajasthan.

Regarding information about the work to be performed and facilities available at the worksite,

around ⅔rd

majority of participants pointed out that they were given requisite details of the work

to be performed. About the facilities available at the worksite, around ¾th

of the participants

agreed that drinking water facility was provided at the worksite. About the facilities like shade

for period of rest; child care facilities; first aid kit and primary medicines available at the

worksite around 40 to 50 per cent participants replied that these facilities were not available on

the work site. Lack of drinking water, child care and medicine facility at the work place was

mostly reported by participants in Karnataka, Haryana, Madhya Pradesh and Punjab.

153

On the monitoring of the MGNREGA functioning more than 80 per cent participants indicated

that the work was being monitored through some authority but majority of them did not know

whether any auditing of the accounts take place or not. In Haryana around 80 per cent

participants indicated that there was no monitoring taking place while 16 per cent expressed their

unawareness and only 4 per cent participants indicated that monitoring of MGNREGA work was

being held. In all other states more than 60 per cent participants indicated that the work was

being monitored. Very few participants lodged any complaint and even who indicated that they

lodged a complaint only 7 per cent of them said that their complaints were taken care of.

Around 90 per cent of the participated households pointed out that the work done was useful to

the villagers. Only less than 10 per cent households pointed out that the work done was not

particularly useful for the villagers. To the question of how long the constructed structure may

last, around 30 per cent opined that it may not last more than one year while around 40 per cent

expressed hope that the structure will last up to five years. More than ¾th

majority of the

participant households pointed out that it was worth to create the structure or in other words,

created structure would be useful for the villagers. Similarly, slightly above ⅔rd

majority of the

households indicated that the structure created was adequate with due attention being paid to it.

Some incidents of migration out of the village as well as migration back to the village (to work

under MGNREGA) were cited, but the extent of the same was only miniscule, not leading to the

conclusion that MGNREGA had any conclusive evidence of affecting labour migration into any

particular direction. Some household members migrating out for job after implementation of

MGNREGA among the selected states was observed comparatively higher in Bihar, Gujarat,

Assam, Rajasthan and Maharashtra. However, in Bihar and Maharashtra the incidence of family

members migrating back to village to work under MGNREGA was also found higher than the

other states indicating the reverse migration occurring along with the incidence of migration

among the participant households. Regarding the question of villagers’ awareness about

‘Mahatma Gandhi National Rural Employment Guarantee Act’ under implementation in the

village, a clear ⅔rd

majority of the respondents pointed out that people in the village were aware

about the same. However, households were hardly aware about the provision of unemployment

allowance under MGNREGA. Similarly, majority of the respondents were not aware about

154

provision of the worksite facilities, mandatory availability of muster rolls at the worksite and list

of permissible works under the MGNREGA.

To understand how the MGNREGA programme has affected the general life of villagers we

enquired few questions related to participants’ day-to-day life. Around 67 per cent participants

were of the view that MGNREGA has enhanced food security of the villagers by providing them

employment and thus purchasing power to have better access to food. Around 60 per cent

participants pointed out that MGNREGA has given greater independence to women. Around 65

per cent agreed that MGNREGA provided protection against extreme poverty. On the migration

issues, around 49 per cent indicated that MGNREGA has helped to reduce distress migration

from the village to cities. Similarly, around 50 to 60 per cent pointed out that MGNREGA has

reduced indebtedness by generating purchasing power at the local economy.

We further probed the food security issues among the participants. To our question did your

family get full two square meals throughout the reference year, around 24 per cent households

answered in negative. If the households did not have sufficient food how did they cope up with

the situation? Around 37 per cent affected households indicated that they borrowed from some

sources to cope up with the situation. Around 13 per cent pointed out that they reduced the

numbers of meals during the crisis period while others took other measures like catching fishes

or rats etc. The states where maximum number of households indicated not having two square

meals among the selected states were the poor states of Assam and Bihar while in the states of

Haryana and Andhra Pradesh no household reported not having sufficient meal during any

month of the reference year.

7.2.8 Some quantification of qualitative questions

A 3/4th

of majority of those who did not have job card with them did not know the real reason for

not having card with themselves while around 1/4th

of them replied that the head of the

Panchayat (Sarpanch) or contractor had kept it with themselves to make entries in the card or for

security reasons. To our question who monitored the functioning of MGNREGA? Around 11 per

cent participants said it was supervisor while around the same numbers also indicated that the

person was some government official at the block or district level. However, a clear majority

(around 50 per cent) named the Gram Panchayat or Panchayat Secretary mainly functioning for

155

the monitoring work of MGNREGA. The rest of the participants (less than 1/3rd

) were not

knowing whether there was any monitoring being carried out or if so who carries out the same.

On the question how MGNREGA has enhanced food security, a majority of the participants

pointed out that by providing employment MGNREGA has helped their food security during the

working days, moreover by saving some money when they are employed, they now have better

food security when they are not employed in MGNREGA as well. However, overwhelming

majority indicated that MGNREGA can ensure better food security by guaranteeing at least 100

days employment to every household and the programme would be more useful in ensuring food

security if they are also provided food at the work place.

To the question how MGNREGA provided protection against extreme poverty, the respondents

were of the view that although MGNREGA provided extra purchasing power and reduced

migration but it could be more effective if it could provide full 100 days work; provide wage on

daily basis; stipulated minimum wage are ensured; and poorest people are given top priority. To

the question of migration, a significant number of respondents pointed out that to some extent

MGNREGA has been successful in reducing the distress migration but it can be more effective

in stopping unnecessary migration if 100 days work and minimum stipulated wages are ensured.

Similarly, respondents agreed that indebtedness to informal sources would also be checked if

MGNREGA provides employment to people at higher wage rate compared to prevailing wage

rate within the village.

7.2.9 MGNREGA impact on village economy

The surveyed villages had mixed picture with some villages having perfect infrastructure like

road, post office, bank, SHG, school, primary health centre, FPS etc., while others had to travel

some distance to approach the same. During the last ten years there has been a slight change in

the occupation structure in the selected villages. The prevailing wage rates in agriculture were

fluctuating widely. Prevailing wage rate in non agricultural sector were much higher compared to

the agricultural sector and the level of skilled wages were almost double that of unskilled wages.

Comparing the wage rate over the last five years, i.e. since the time MGNREGA has come into

implementation, the wage rate in agriculture sector has increased by slightly less than 50 per cent

156

for male and slightly above 50 per cent for the female. By the same estimates, wage rate for

unskilled as well as skilled labour in the non agricultural sector increased by slightly less amount

compared to agriculture labour except the wage rate in mining during the same time period. The

wage rate for unskilled labour in non agriculture and construction work increased slightly less

than the wage rate increase in agriculture while wage rate for skilled labour in mining increased

slightly more than agriculture. The wage rate for technical work like electrician, plumber and

pump set boring increased by less than that of agriculture (between 35 to 47 per cent). Thus,

increase in wage rate in agriculture more than most of the other activities within the village

indicate the enhanced demand for wage labourers due to employment works in MGNREGA that

goes parallel with the agriculture sector thereby causing a competition in the labour market for

the agriculture sector. Increases in charges for agricultural operations per acre on an average

were almost similar to increase in agricultural wages as overall wages observed an increase of

around 49 per cent compared to around 46 per cent increase in cost of per acre agricultural

operations as per our group discussion data.

A majority of the villages indicated shortage of agricultural labour has increased after the

implementation of MGNREGA. In majority of the villages the shortage of labour was observed

during the sowing and harvesting months of kharif and rabi seasons especially in the months of

July, August and September and March and April. This was more so after the implementation of

MGNREGA. A majority of villagers were of the view that after MGNREGA implementation

cost of production in agriculture has increased by 10 to 20 per cent because of scarcity of labour.

On the question, whether workers who earlier migrated out of the village to work in city are now

coming back to work in MGNREGA, the trend of villagers returning back to the village to work

in MGNREGA was found more prevalent in Andhra Pradesh, Himachal Pradesh, West Bengal,

Bihar and Karnataka while reverse was the case in Gujarat and Kerala. But a majority of

participants in the discussion indicated that MGNREGA has not made any significant changes in

the migration pattern in the village.

Another point of debate was how the MGNREGA has affected living standards of villagers, a

clear majority indicated that MGNREGA has not been successful in raising their living standards

or their consumption level and the reasons was quoted that the programme has not provided

157

enough numbers of days of work to make a significant dent on the poverty level, although a

minority of them were of the view that MGNREGA has been successful in doing so, to some

extent. The latter ones indicated that MGNREGA has improved living standards by providing

work within the village and by ensuring same wage rate to female as equal to that of male. To

another question, whether MGNREGA has changed the trend of attached labour in agriculture, a

significant majority said yes as people were getting better payments within the village compared

to agricultural work so the trends of attached labour for the agricultural work were declining.

However, MGNREGA has certainly increased people awareness towards Government schemes

through increase in the showcasing by television, newspaper, Gram Panchayat and Gram Sabhas

and by other means. Among the selected states, in Sikkim, Andhra Pradesh, Kerala, Rajasthan,

West Bengal, Uttar Pradesh, Maharashtra and Gujarat, a clear majority of the discussants

expressed that the household consumption as well as enrollment of children in the school have

increased after implementation of MGNREGA that has provided extra purchasing power in the

hands of the villagers. On the question of awareness almost all states observed increased

awareness of the households towards existing government schemes because of their participation

in the gram sabha and also because of joint working opportunities in MGNREGA

7.2.10 Villagers’ suggestions to raise efficacy of MGNREGA

Among the steps needed to ensure better implementation of MGNREGA, the major ones

suggested by the discussants included: increasing working days and wage rate; providing food

within the programme; allowing private land development through MGNREGA work for

longevity of the programme; and by providing proper information on various aspects of the

programme; implementation should be carried out though local bodies and job card should be

given in the hands of the workers; quick payment after work.

7.3 Policy Suggestions

In the light of above discussion following policy suggestions can be made to improve the

functioning of MGNREGA.

The MGNREGA has not been successful in providing stipulated 100 days employment to

all the registered persons. The reasons expressed by the Panchayat and district officials

158

were many including lack of funds; money not being provided from the Central

authorities on time; the gap with which money reaches to the Panchayat officials; and

money being provided only for few months and not the whole year. The results of the

household survey clearly indicate that unless participants are given work for the

stipulated 100 days, MGNREGA shall not be able to make any significant dent on the

rural poverty and would fail in its basic objective. Therefore provision of 100 days

employment to all the participants should be made mandatory and strict action should be

taken against the Panchayats which fail in fulfilling this target. The issue of timely

provision of money to the Panchayats should be looked into so that MGNREGA work

does not suffer because of lack of funds with the Panchayats.

Another big anomaly was found in the wage rate paid under MGNREGA. Whereas under

the MGNREGA Act, Panchayats are ordained to pay at least equal to the minimum wage

determined for the state during a particular period. However, the actual wages paid under

MGNREGA were found much lower. Among participants in Karnataka, those who were

paid equal to or above the stipulated minimum wage, their percentage was only 1.4.

Those who were paid 100 or above constituted only 22 per cent and those who were

paid between 80 and 100 their per centage was 63, while the percentage of those paid

less than 80 was around 15. Thus, above 40 per cent of the selected participants were

paid less wages by 50 per cent or more compared to the stipulated minimum wage in the

state during the reference period. Among the corrections suggested by the households,

almost all of them wanted that the minimum stipulated wages should be ensured for all

participants irrespective to the nature of work they were involved in.

In the village analysis it was observed that there seems to be a conflicting interest

between the MGNREGA and the farming community. Farmers across the board are

feeling that they are facing labour shortage for agricultural activities because of the

diversion of labour caused by MGNREGA activities. With a meticulous planning, this

problem can be solved without affecting anyone adversely. In our secondary analysis, we

saw that MGNREGA has provided not more than 45 days of employment per household

at the all India and all states failed in providing stipulated hundred days of employment to

all households working in the programme. Even if the stipulated hundred days

employment is provided by the MGNREGA, still there is enough scope for the labour

159

force to work in the agricultural sector. There is however need to plan the MGNREGA

work at the Panchayat level in such a way that it does not clash with the sowing and

harvesting season in agriculture when the demand for agriculture labour is highest. The

projects taken up under MGNREGA should be planned in such a way that labour is

strictly employed for the project after the sowing and harvesting season of main rabi and

kharif crops is over. This planning has to be done at the Panchayat/Block and District

level depending upon the cropping pattern of the respective regions. It not only would

provide necessary labour force for agricultural operations but also would increase

employment and income opportunities for the villagers during the off-season including

that of marginal and small farmers who do not have enough work at the farm in the off-

season.

Another reason for authorities not being able to provide stipulated days of employment

to the participants, as was observed during the field survey, was that many a times

Panchayat (or other concerned authorities) ran out of ideas as in what activity labour

force should to engaged to keep them working. In many a cases labour force under

MGNREGA was used just for digging, clearing jungle, sweeping, dust-cleaning,

collecting waste and filling mud into the tractor and so forth as there was no long term

durable asset creation work available with the Gram Panchayats. In the qualitative

questions, most of the participants appeared to be worried for continuity of the

MGNREGA works and suggested for allowing the private farm work under MGNREGA.

The idea seems to be quite rational. In the villages where Pachayats fail to have any

utility work to be taken up under MGNREGA, rather than making payment for

unproductive works which make no value addition, it is better to take up development

work on the private farms. The terms and conditions of work can be planned in an

intelligent way. The farmer has to pay to the Panchayat for the work done by the

labourers at the prevailing rate in the village. The residual amount (difference of the wage

paid by the farmer and the stipulated minimum wage for MGNREGA) would be paid to

the labourers by the Panchayat. This is a win-win situation for both farmers as well as

Panchayat as the amount saved by the Panchayat from the MGNREGA fund can be used

for other development work of the village. This will also partly solve the problem of

labour shortage in agriculture as being faced at the present. Already provision of

160

irrigation facility, horticulture plantation and land development facilities to land owned

by households belonging to the Schedule Castes; Schedule Tribes; BPL families;

beneficiaries of land reforms; and beneficiaries under the Indira Awas Yojna have been

granted under the Act. Further, the benefits of works on individual lands have been

extended to small and marginal farmers vide notification dated 22.7.2009. These should

be encouraged by the Panchayat officials and permission should also be granted for land

development works for all other farmers as well, the facility to the latter one may be

granted on payment basis as explained above.

Proper punishment system should be put up in place for the unscrupulous officials who

are found guilty of indulging in corruption and other untoward activities. Similarly, those

Gram Panchayats that work efficiently in running the MGNREGA system should be

rewarded and felicitated appropriately.

The provision of food/grain at the work place and easy institutional credit can attract

more villagers, especially the poor ones towards working in MGNREGA and also

ensures better food security to the participants.

The Unique Identification (UID) should be used for the better functioning of MGNREGA

Anderson et al (2013). Bank accounts for MGNREGA workers will be linked to the

unique biometric id. As a result, the actual transfer of payments will immediately reach

the hands of who it is intended for. This would drastically reduce the alleged inherent

corruption in the current system and increase the amounts and reliability of payments to

the workers.

161

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Annexure Tables

166

ANNEXURE – I

The Details of AERCs and the Lead Person Involved in the State Report

Sl. No. States AERC who carried the

study in the state

The Lead Person Who Carried Out the Study

1. Andhra Pradesh AERC Waltare G. Gangadhara Rao and K. Adiseshu

2. Assam AERC Guwahati Jotin Bordoloi

3. Bihar AERC Bhagalpur Rajiv Kumar Sinha and Rosline K. Marandi

4. Chhattisgarh AERC Jabalpur Hari Om Sharma and Deepak Rathi

5. Gujarat AERC Vidyanagar V.D. Shah and Manish Makwana

6. Haryana AERC Delhi D.S. Bhupal

7. Himachal

Pradesh

AERC Shimla C.S. Vaidya and Ranveer Singh

8, Kerala AERC Chennai R. Arunachalam and A. Abdul Salam

9. Madhya Pradesh AERC Jabalpur Hari Om Sharma and Deepak Rathi

10. Maharashtra AERC Pune Jayanti Kajale and Sangeeta Shroff

11. Punjab AERC Ludhiana Kamal Vatta; D.K. Grover and Tinku Grover

12. Rajasthan AERC Vidyanagar Mrutyunjay Swain and Shreekant Sharma

13. Sikkim AERC Shantiniketan Jiban Kumar Ghosh and Snehasish Karmakar

14. Uttar Pradesh AERC Allahabad Ramendu Roy and Ramji Pandey

15. West Bengal AERC Shantiniketan Jiban Kumar Ghosh

16. Karnataka ADRTC Bangalore Parmod Kumar and I. Maruthi

167

ANNEXURE – II

The Details of Selected Sample State Wise

Sl. No. States Selected Districts Phases No of HHs Selected AERC who

carried out

the study in

the state

Participants Non

Participants

1. Andhra Pradesh Adilabad, Chittoor, Mahboobnagar I 200 50 Waltare

Srikakulam II

Krishna III

2. Assam Karbi Anlong, Kokrajhar I 200 50 Guwahati

Darrang, Hailakandi II

Tinsukia III

3. Bihar Kishanganj, Rohtas, Samastipur I 200 50 Bhagalpur

Banka, Gopalganj II

4. Chhattisgarh Dantewada, Kawardha I 200 50 Jabalpur

Kobra, Mahasamund II

Durg III

5. Gujarat Banas Kantha, Dahod I 200 50 Vidyanagar

Navsari II

Surendra Nagar, Jamnagar III

6. Haryana Sirsa I 200 50 Delhi

Ambala II

Bhiwani, Panipat, Faridaba III

7. Himachal Pradesh Chamba, Sirmaur I 200 50 Shimla

Mandi II

Kinnaur, Una III

8. Karnataka Bidar I 201 54 ISEC,

Bangalore Bellary, Chikmangalore II

Chamrajanagar, Dharwad III

9, Kerala Palakkad, Wayanad I 200 50 Chennai

Kasargod II

Kottayam, Thiruvananthapuram III

10. Madhya Pradesh Dhar, Sidhi I 200 50 Jabalpur

Chindawara II

Morena, Sagar III

11. Maharashtra Gondia, Nandurbar I 205 45 Pune

Thane II

Jalna, Kolhapur III

12. Punjab Hoshiarpur I 200 100 Ludhiana

Jalandhar, Amritsar II

Mansa, Firozpur III

13. Rajasthan Banswara,Karauli I 200 50 Vidyanagar

Jaisalmer II

Nagaur, Ganga Nagar III

14. Sikkim North District I 160 40 Shantiniketan

East Sikkim, South Sikkim II

West Sikkim III

15. Uttar Pradesh Bara Banki, Kushi Nagar I 200 50 Allahabad

Etah II

Allahabad, Saharanpur III

16. West Bengal Jalpaiguri, Maldah, Purulia I 200 50 Shantiniketan

Nadia II

Howrah III

Grand Total 3166 839