chapter-vii mgnrega and its impact on rural...
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CHAPTER-VII
MGNREGA AND ITS IMPACT
ON RURAL ECONOMY IN KARNATAKA - A CASE STUDY IN CHITRADURGA, DAVANGERE,
HASSAN AND SHIMOGA DISTRICTS
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MGNREGA and Its Impact on Rural Economy in Karnataka: A Case Study
The level of understanding of MGNREGA concept at different levels of
administration and workers participating in MGNREGS; preparedness of various
agencies to implement the programme; adherence to policies and procedures of the
Act, timely support by related departments for the smooth conduct of the programme;
monitoring of MGNREGS works by authorities; constraints in implementation
affecting the progress of the programme, transparency in the implementation of the
scheme, efficiency and effectiveness of the program were documented. An analysis of
extent of participation by workers in the programme; equity and women
empowerment issues addressed and benefits derived in terms of improvement in
employment opportunities, income level, savings accumulated, and creation of assets
and rejuvenation of natural resources were attempted in the present study.
7.1 : Implementation of MGNREGS in Selected Districts of CDZ and STZ
Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
guarantees, on behalf of the Government, 100 days of wage employment in a financial
year to all the rural households in the country whose adult members volunteer to do
unskilled manual work. Funding of the programme is shared by Central Government
and State Governments in the proportion of 90 per cent and 10 per cent, respectively.
In Karnataka, Rs 357.87 crores was spent on implementing MGNREGS up to
2008-09 out of the total amount released of Rs 642.50 crores. It had generated 8.97
lakh person days of employment. Table 7.1depicts a summary of the progress
achieved in the study area. An amount of Rs 87, 59, 28 and 29 crores were made
available to Davanagere, Chitradurga (CDZ), Shivamogga and Hassan (STZ) districts
respectively for MGNREGS. Performance Index of MGNREGS expenditure which is
a comparison of ratio of money spent to money allocated for the programme in the
four selected districts with that of state shows that performance in Chitradurga (137.5)
was far better than that in other districts where the index varied from 63.9 to 82.6. In
CDZ majority of the works were completed, while in STZ majority of the works were
in progress. It is reflected in the performance index of works completed Which were
higher than the state performance in Chitradurga (137,6) and Davanagere (133.33)
districts, both belonging to the economically backward region. The figures for Hassan
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(64.86) and Shivamogga (70.77) districts belonging to economically forward districts
were relatively poorer. Performance in terms of employment provided was higher in
economically backward region as compared to economically forward region as
revealed by the statistics in the table viz; Chitradurga district (1.39 lakhs person days)
followed by Davanagere district (0.85 lakhs), Shivamogga district (0.45 lakhs) and
Hassan district (0.13 lakhs). This stresses the importance of employment guarantee
through public works in severely drought prone districts which are economically
backward.
Though the proportion of workers belonging to Scheduled Castes participating
in MGNREGS as compared to their proportion in the total population of the state was
higher in all the districts, the proportion was comparatively higher in economically
backward region represented by Chitradurga (MGNREGS proportion of 41.21per cent
as against the state level proportion of 22.2 per cent) and Davanagere (31.0 per cent
as against 18.6 per cent) districts than in economically forward region represented by
Hassan (19.3 per cent as against 18.1 per cent) and Shivamogga (20.8 per cent as
against 16.4 per cent) districts.
The stipulation that one-third of the workers under MGNREGS should be
women was satisfied in both CDZ and STZ. In Chitradurga district, which is a
chronically drought prone area and identified by the NPC as one of the three most
disadvantaged districts in Karnataka along with Davanagere and Bidar, the women
employment in MGNREGS formed 61 per cent. It was followed by Davanagere
district (46 per cent), another economically backward region.
Research studies conducted by Anurekha Chari on Maharashtra’s EGS (2006),
Arun Jacob and Richard Varghese on Kerala’s REGS (2006), Kiran Bhatty on
Rajasthan’s NREGS (2006), Lalith Mathur on NREGS in Rajasthan (2007), Jayati
Ghosh on NREGS in Karnataka and Tamil Nadu (2009) and Reetika and Nandini on
NREGS in six northern states (2009) have shown that similar to the results of the
present study, participation of SC/ST category workers in the employment guarantee
schemes had been more than their proportion in the national / state population and
women worker’s participation ranged from 40 per cent to 80 per cent of the total
worker participation in those programmes, stressing the point that MGNREGS has
been fair in addressing equity and gender issues.
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Table-7.1: Performance of MGNREGS in Economically Forward and
Backward Regions of Karnataka
Note: Figures in Parentheses indicate percentage to total
Particulars / Districts
Economically Forward Region (STZ)
Economically Backward Region (CDZ) Karnataka
Hassan Shivamogga Chitradurga Davanagere
Employment to No. of
house holds (Lakhs) 0.13 0.46 1.39 0.85 8.97
Total population
(Lakhs) 17 16 15 18 528
Person
days
(Lakhs)
Total 7.05 10.20 31.05 25.70 287.64
SCs 1.36
(19.33%)
2.13
(20.87%)
12.79
(41.21%)
7.97
(31.00%)
79.90
(27.77%)
Proportion
of SCs in
total
population
(per cent)
18.10 16.40 22.20 18.60 16.21
STs
0.94
(13.33%)
0.50
(4.93%)
6.79
(21.87%)
5.14
(20.00%)
39.91
(13.87%)
Proportion
of STs in
total
population
( per cent )
01.50 03.40 17.50 11.70 6.55
Others 4.75
(67.33%)
7.57
(74.2%)
11.46
(36.93%)
12.59
(49.00%)
167.85
(58.35%)
Proportion
of Others in
total
population
80.40 80.20 60.30 69.70 77.24
Women participation
in Person days (Lakhs)
2.33
(33.09%)
4.62
(45.27%)
18.94
(61.00%)
11.80
(45.91%)
145.00
(50.42%)
Proportion of women
in total population
( per cent )
50.10 49.43 48.86 48.76 49.10
Funds released
(Rs. crore) 29.40 27.94 59.46 87.00 642.50
Expenditure (Rs.
Crore) 10.47 12.84 45.56 31.68 357.87
Performance index of
expenditure 63.90 82.60 137.50 65.40 -
Total works planned
(Number) 1703 2209 3143 2484 56538
Works completed
(Number) 673 952 2635 2016 34431
Performance index of
works completed 64.86 70,77 137.60 133.33 -
Works in Progress
(Number) 1030 1257 508 468 22107
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Graph-7.A: MGNREGS Employment Availed by Different Categories of
Workers in Sample Districts of Karnataka
7.2: Minimum Wage Laws
Gregory Mankiw states that when a minimum wage law forces the market
wage to remain above the level that balances supply and demand, it raises the quantity
of labour supplied and reduces the quantity of labour demanded compared to the
equilibrium level. There is a surplus of labour. Because there are more workers
willing to work than there are jobs, some workers are unemployed.
Figure-7(i): Unemployment from a Minimum Wage above the Equilibrium Level
WE
LD LE LS Quantity of Labour
LabourDemand
ddd Demand
Wages
O
Surplus of Labour - Unemployment Labour Supply
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WE is the market equilibrium wage rate, LE is the quantity of labour supplied
and demanded at this equilibrium wage. LD is the labour demanded and LS is the
labour supplied because of the minimum wage law. LS - LD, the resulting surplus
labour represents unemployment (Fig. 7(i)).
In Karnataka, since market wage rate for male labour (Rs. 120 to Rs.150 per
person per day in 2008-09) was above the minimum wage rate fixed by the state
government, in most of the districts this type of surplus labour and resultant
unemployment was not seen in their cases. As per the Notification No. KAE 96 LMW
2005 dated 30.07.07, Prescribed Minimum Rates of Wages per day for all the types of
cultivated land and VDA (variable DA) in Karnataka from 01.04.2009 to 31.03.2010 was
Rs. 119.41 (Rs. 100 + Rs. 19.41). However this concept might have been true to some
extent in case of women labour, whose market wage rate (Rs. 50 to Rs. 80 per woman
per day), was well below the MGNREGS wage rate.
7.3: General Awareness about MGNREGA among Workers
For the success of any programme awareness about its provisions across
different sections of the population is crucial. It was observed during the course of the
study that attempts had been made by the administration to create awareness
regarding the Act and the Programme among the intended beneficiaries through news
papers, television, radio, pamphlets and brochures. The method of dissemination
adopted influenced the extent of awareness created (Table 7.2). Information passed on
by neighbours working under MGNREGS, efforts made by Gram Panchayath
secretaries to educate the villagers and writing on walls of Panchayath offices and
schools formed the major sources of awareness about MGNREGA among the
beneficiaries. It was found that each of the first two media created awareness in 30
per cent of the beneficiaries; while wall writing created awareness in around 12 to 21
per cent of beneficiaries. Authorities in Shivamogga district adopted street plays as a
novel method to create awareness about MGNREGA and it had a positive impact on
the workers. Broadcasting through Akashavani was followed in Chitradurga district as
a means of creating awareness.
The statistics presented in Table 7.2 also reveal that awareness among the
workers about provisions and procedures of the Act was poor both in CDZ and STZ
(ranging from 2 to 21 per cent of the beneficiaries), although 88 to 93 per cent of the
beneficiaries were aware of MGNREGA in all the selected districts except in Hassan
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district where around 38 per cent of the beneficiaries were not aware of the Act.
Bhatia and Dreze (2006) also found out that MGNREGS participants in Jharkhand
were ignorant about nuances of the Act.
The works to be taken up under MGNREGS are decided in the gram sabha
meetings called by Gram Panchayaths, which provides an opportunity for the villagers
to take active role in decision making process that guides village development
activities. But, participation by the beneficiaries in such meetings was low in all the
districts. Either lack of motivation or improper timings of the meetings could be the
reason for low attendance of the workers. However, it was heartening to note that
voluntary participation of the beneficiaries in the MGNREGA activities was more
than 75 per cent.
More efforts are needed to educate the intended beneficiaries of MGNREGS
on the provisions of MGNREGA and importance of their participation in gram sabha
meetings. Better informed participants will make the best use of the facilities made
available to them and it will serve the interests of individuals as well as the
communities.
Table 7.2: Awareness Regarding MGNREGA Among the Workers
(Percentage of respondents)
Particulars
Economically
forward
region (STZ)
Economically
backward
region (CDZ) Pooled
Average
Districts
Hass
an
Sh
ivam
ogga
Ch
itra
du
rga
Davan
ager
e
General
Awareness
about
MGNREG
A through:
(a to f)
( per cent )
a Wall writing 21.5 14.5 12.2 15.4 15.9
b All India Radio 4.2 4.96 1.9 1.8 3.2
c
Announcement using auto
rickshaw 0.0 0 5.1 0.0 1.3
d Tom tom 6.6 1.31 19.0 6.5 8.4
f
Neighbors working in
MGNREGP 36.8 42.92 31.4 38.0 37.3
g
Through Village Secretary /
Local leader 30.9 36.2 30.3 38.3 33.9
Beneficiary Families still unaware of
MGNREGA (per cent) 38.7 9.0 12.2 7.0 16.7
Awareness about provisions and procedures of
MGNREGA (per cent) 0.0 21.2 2.5 15.0 9.7
Meetings attended regarding MGNREGA at
Gram Panchayaths (per cent) 3.3 12.5 1.3 3.8 5.2
Willingly participating in MGNREGA (per cent) 75.0 83.7 75.0 93.3 81.8
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Graph-7.B: Awareness Regarding MGNREGA Among the Workers
(Percentage of respondents)
7.4: Compliance with Procedures to seek Employment under MGNREGA
MGNREGA provisions include (a) any adult member of rural households,
irrespective of caste, religion, occupational background or economic status is eligible
for employment, if he or she is willing to do unskilled manual work (b) such
households willing to work under MGNREGS need to register in the local Gram
Panchayaths (c) All the households registering under MGNREGA need to be issued
job cards, with photographs of willing family members, free of cost by Gram
Panchayaths (d) After obtaining job cards the willing households should submit a
written application for employment to the gram Panchayath secretary which will be
acknowledged with dated receipt by the Gram Panchayath (e) Employment has to be
provided within 15 days of this application (f) In case the Panchayath fails to provide
employment within 15 days, the applicants have to be paid unemployment allowance.
This unemployment allowance amount has to be borne by the State Governments.
Results of the analysis related to MGNREGA procedures are presented in
Table 7.3. It was found that although almost all the employment seeking households
were issued job cards, they were partially filled with details. Even though
MGNREGA stipulates that job cards must possess photographs of all the family
members willing to work under the programme, only 29 per cent and 33 per cent of
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the beneficiaries in Hassan and Davanagere districts, respectively had photos affixed
in their job cards. Compliance with the rules was relatively better in Shivamogga and
Chitradurga districts where about 91 per cent and 51 per cent of the beneficiaries,
respectively possessed Job cards with duly affixed photos.
All the households participating in MGNREGS are supposed to have their job
cards in their possession to avoid any kind of malpractices. The analysis showed that
in Hassan, Shivamogga and Davanagere districts, over 70 per cent of the beneficiaries
had their job cards in their custody, while the others expressed that Gram Panchayaths
are the custodians of their job cards. Provision of work within 15 days from the date
of application, was comparatively better in Shivamogga (94 per cent) and Chitradurga
(82 per cent) districts when compared to Hassan (65 per cent) and Davanagere (62 per
cent) districts. However, MGNREGA records maintained in Gram Panchayaths did
not show payment of unemployment allowance to beneficiaries due to delay in
allotment of work even in a single instance. Bhatia and Dreze (2006) reported that in
Jharkhand the implementing agency failed to maintain proper records pertaining to
MGNREGS.
Contrary to the provisions in MGNREGA most gram panchayaths did not
insist on request for employment in written form. Instead, as and when the Gram
Panchayaths decided to execute a work, Panchayath authorities obtained demand
letters from the workers. Application for employment in writing would guarantee
employment to the workers when they need it.
It can also be observed from the table that economic status of the region does
not have a bearing on the adherence to procedures in execution of MGNREGS.
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Table-7.3: Job Card Details of the Workers in the Selected Districts of CDZ and STZ
7.5: Provision of Worksite Facilities to the Workers under MGNREGS
Shade, drinking water, first aid and crèche, if more than 5 children below the
age of 6 years are present, are the minimum work site facilities the programme
executors are expected to provide to the workers under MGNREGS. Table 7.4 shows
that except in Chitradurga district in all the other districts more than 75 per cent of
the beneficiaries were provided with clean drinking water at the worksite. Laxity was
observed in economically backward region viz; Chitradurga and Davanagere districts
with respect to provision of shade, in spite of workers experiencing scorching Sun
during summer months when majority of MGNREGS works are implemented. More
than 55 per cent of the beneficiaries in all the districts except Chitradurga (21 per
cent) answered affirmatively to the question on provision of first aid facility at the
worksite. Crèche facility was not extended in any of the districts.
Bhatia and Dreze (2006) in Jharkand, Kiran Bhatty (2006) in Rajasthan and
Sudha Narayanan (2008) in Tamil Nadu have also reported that administration failed
Particulars
Economically
Forward
Region (STZ)
Economically
Backward
Region (CDZ)
Av
era
ge
Ha
ssa
n
Sh
iva
mog
ga
Ch
itra
du
rga
Da
va
na
ger
e
Proportion of job card holders who applied for
employment (per cent) 33.3 83.7 53.8 15.0 46.5
Dated acknowledgement issued by gram Panchayath ( % ) 0.0 0.0 0.0 0.0 0.0
Proportion of job cards where entries were made ( % ) 57.1 87.5 45.9 51.7 60.6
Proportion of households to whom job cards are issued
without causing hassles ( per cent of beneficiaries) 100 100 100 89.6 97.4
Gap between registration and issue of job card (No. of
Weeks) 2.1 2.1 1.6 2.1 2.0
Proportion of beneficiaries working without job cards
(per cent of beneficiaries) 25 15.2 25.6 60.0 31.5
Proportion of Job cards having photos of members ( % ) 28.8 91.3 51.3 32.9 51.1
Job cards in the custody of ( % ) Households 74.7 55 70.5 96.2 74.1
Gram Panchayath 25.3 45 29.5 3.8 25.9
Work allotted within 15 days of
application ( per cent of
households)
Yes 65.0 93.7 81.9 62.1 75.7
No 35.0 6.3 18.1 37.9 24.3
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to provide adequate worksite facilities to the workers, especially crèche for small
children who accompany their mothers to worksites. This is a major constraint faced
by women workers who are coming forward in large numbers to participate in
MGNREGS. Extending these facilities earnestly may make MGNREGS more demand
oriented, attract more workers, especially women to MGNREGS and thereby reduce
rural labour migration to some extent.
Table -7.4: Provision of the Worksite Facilities in Selected Districts of
CDZ and STZ
Sl.
No.
Facilities at worksite
(per cent of
beneficiaries)
Economically
Forward Region
(STZ)
Economically
Backward Region
(CDZ)
Overall
Hassan Shivamogg
a Chitradurga
Davanager
e
1 Drinking water 75.7 81.25 61.3 78.8 74.3
2 Shade 11.4 77.25 0.0 0.0 22.2
3 Medical aid 55.7 70.0 21.3 66.7 53.4
4 Crèche 0 0 0 0 0
7.6: Wage Rate Followed and Payment made under MGNREGS
The workers participating in MGNREGS are paid gender neutral wages. Wage
rates prescribed in the Minimum Wages Act 1948 for agricultural labourers in the
states are followed. In Karnataka the MGNREGA wage rate fixed for 2008-09 was
Rs.82 per person per day. Wages have to be disbursed to workers in one week’s time
and not exceeding two weeks period. MGNREGA tries to ensure transparency, by
making it compulsory to pay wages to workers through Bank or Post Office accounts.
Banks and Post Offices have to open accounts for MGNREGA workers free of cost.
In case of households with more than one member working under MGNREGS, a joint
account has to be opened.
Results presented in Table 7.5 and Graph 7.C as well as 7.D show that market
wage rates of both men and women workers were comparatively higher in STZ than
in CDZ which are chronically drought prone. That induces higher labour migration
from CDZ to plantation areas of STZ. Market wage rates of women were lower than
the MGNREGA wage rate of Rs. 82 per person per day to an extent of 16 per cent in
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Shivamogga, 20 per cent in Davanagere and 40 per cent in Chitradurga districts. At
the same time market wage rates for men were higher than MGNREGA wage rates to
an extent ranging from 12 per cent in Chitradurga to 54 per cent in Hassan district.
That explains large scale participation of women under MGNREGP and men labour
shying away from the programme.
Table-7.5: Wage Differential Faced by MGNREGA Workers in Selected
Districts of CDZ and STZ
Graph-7.C: Market and MGNREGA Average Wage Rates in Sample
Districts of Karnataka
Sl.
No. Region
District
Sex
Market
wage
rate
(Rs.)
MGNREGA
Wage Rate
(Rs.)
Market wage rate
as per cent change
from MGNREGA
wage rate
I Economically
Forward
Region
(STZ)
Hassan Female 82.7 82 0.9
Male 125.9 82 53.5
Shivamogga Female 68.6 82 -16.3
Male 113.7 82 38.7
II Economically
Backward
Region
(CDZ)
Chitradurga Female 48.6 82 -40.7
Male 91.5 82 11.6
Davanagere Female 65.0 82 -20.7
Male 101.1 82 23.3
Average Female 66.3 82 -19.1
Male 108.0 82 31.7
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Graph-7.D: MGNREGA Wage Rate in Comparison With Market Wage Rate in
Selected Districts of Karnataka
7.7: MGNREGA Wage Rate as Floor Wages for Agricultural Operations
Women workers in some villages, mainly from Bhadravati Taluk of
Shivamogga district, stated that their farm wages had increased by, on an average, Rs.
10 per person per day after MGNREGS was implemented. It showed that MGNREGS
had an influence on the floor wages for agricultural operations.
Table 7.6 reveals that employment availed by MGNREGA workers ranged
from 18 days per household in Shivamogga district in STZ to 47 days per household
in Chitradurga district in CDZ which was less than 50 per cent of the guaranteed
employment of 100 days per household per annum in the Act. Higher market wage
rate that prevailed in all the districts was the major reason for lower participation of
workers under MGNREGS. However, indices of number of days worked under
MGNREGS shows that extent of utilization of MGNREGA provision was higher in
economically backward region represented by Chitradurga (145 for men and 149 for
women workers) and Davanagere (122 for men and 99 for women workers) districts
than in economically forward region represented by Hassan (74 for men and 86 for
women workers) and Shivamogga (57 for men and 67 for women workers) districts. It
shows that MGNREGS as a livelihood security measure would be more effective in
economically backward region.
In economically forward region wages were paid to MGNREGA workers
within two weeks as per the norms. However, in economically backward region, the
workers were forced to wait, on average from 3 weeks to a month to receive the
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wages. In some instances, the sample workers complained about delay of beyond 3
months for payment of wages under MGNREGS because of procedural delays and
poor governance. This added to the agony of workers who already suffered due to
drought proneness, poor farm incomes, lower wages and poverty induced migration.
The results are in conformity with the findings of Batia and Dreze (2006) in
Jharkhand.
Improved governance and effective execution of the programme would go a
long way in addressing the sufferings of workers in CDZ.
Table-7.6: Employment Availed and Payment Received by MGNREGA
workers in Selected Districts of CDZ and STZ
7.8: MGNREGS Wage Bill payment through Bank/Post Office Accounts
Cent per cent of the MGNREGS workers in CDZ and nearly all the
households in STZ engaged in the programme had either bank or post office accounts.
Even those workers who had not yet had bank accounts were in the process of
opening the accounts. Since the payment of wages is done on household basis
majority of the workers had joint accounts, ranging from 60 to 74 per cent in STZ and
Sl.
No. Region District Sex
No
. o
f d
ay
s o
f
wo
rk u
tili
zed
per
HH
per
yea
r
Ind
ex o
f N
o. o
f
wo
rk d
ay
s
(Av
era
ge
= 1
00
)
Wa
itin
g t
ime
for
recei
pt
of
wa
ges
(day
s)
Ind
ex o
f N
o. o
f
wa
itin
g t
ime
(Av
era
ge
= 1
00
)
I Economically
Forward
Region
(STZ)
Hassan
Female 23.2 85.9
(-14.1) 13.3
73.9
(-26.1)
Male 24.5 74.2
(-25.8) 13.9
68.1
(-31.9)
Shivamogga
Female 18.1 67.0
(-33.0) 13.0
72.2
(-27.8)
Male 18.9 57.3
(-42.7) 13.2
64.7
(-35.3)
II Economically
Backward
Region
(CDZ)
Chitradurga
Female 40.1 148.5
(48.5) 30.8
171.1
(71.1)
Male 47.9 145.2
(45.2) 33.8
165.7
(65.7)
Davanagere
Female 26.7 98.9
(-1.1) 15.0
83.3
(-16.7)
Male 40.3 122.1
(22.1) 20.6
101.0
(1.0)
Average Female 27.0 100 18.0 100
Male 33.0 100 20.4 100
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73 to 90 per cent in CDZ (Table 7.7). The study showed that the wage bill was
remitted directly to the bank / post office accounts of the beneficiary households.
Table-7.7: Bank / Post Office Account Details of the MGNREGS Workers
in Selected Districts of CDZ and STZ
7.7: Impact of MGNREGA on Household Income of the Workers
MGNREGA was conceived to ensure livelihood security to rural population,
who suffered by seasonal unemployment, by way of providing them employment and
thereby reduce migration of rural workforce to urban areas. Since MGNREGS is
supposed to provide employment when other works are not available and the rural
people volunteer to work under the programme, it is essentially a “demand driven”
programme and concept of “backward bending supply curve” is relevant for the
analysis. ‘Before-After’ approach was followed to analyze the impact of MGNREGA
and the results are presented in Tables 7.8 to 7.12.
From the Table 7.8 and Graph 7.E it can be seen that there had been an
incremental income of around Rs. 950 per person per annum, with an additional
employment for one member of a family for about 21 days. Migration of labourers to
other places had been reduced to an extent of 21 per cent. Since wage payment is
done through bank / post office accounts, possession of such accounts increased by 82
per cent. Increase in employment opportunity and family income enhanced job
satisfaction of the workers.
Absolute change in annual per capita income of workers after participating in
MGNREGS was the highest in Chitradurga district (Rs. 1,348) followed by
Shivamogga District (Rs. 883) and Hassan District (Rs. 860). Additional number of
working days per person ranged from 18 days in Chitradurga district to 28 days in
Hassan district. All the districts were benefited through enhancement in job
Region District Sex
Bank / post office
account opened
( per cent )
Type of bank / post
office account
(Per cent)
Joint Individual
Economically
Forward
Region (STZ)
Hassan Female 93.8 74.0 26.0
Male 95.8 69.0 31.0
Shivamogga Female 94.4 65.0 35.0
Male 99.1 59.5 40.5
Economically
Backward
Region (CDZ)
Chitradurga Female 100.0 73.3 26.7
Male 100.0 80.6 19.4
Davanagere Female 100.0 83.4 16.7
Male 100.0 90.2 9.8
Average Female 97.1 74.0 26.1
Male 98.7 74.9 25.2
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201
satisfaction and reduction in migration of labourers which varied between 2.5 per cent
in Hassan district and 55 per cent in Davanagere district.
Research studies conducted by Kholi (2009) at the national level and Sudha
Narayanan (2008) in Tamil Nadu have shown that MGNREGS has helped the
participant workers to increase their family income, repay old debts and reduce their
misery. These findings are in conformity with the results of the present study. The
respondents reported that increase in their income had helped them to improve their
consumption, send their children to schools and reduce burden of their indebtedness
even though they could not save money.
Table -7.8: Impact of MGNREGS in Sample Districts
Sl.
No. Particulars Before
MGNREGA After
MGNREGA Absolute
change
%
chang
e
1 Annual mean income (Rs.) 6904.0 7855.0 951.0 13.8
2 No. of workers per family 2.0 3.0 1.0 50.0
3 No. of working days per person
per year 190.0 211.0 21.0 11.1
4 Job satisfaction (per cent) 30.7 76.2 45.5 148.2
5 Bank account opened (per cent) 14.6 96.3 81.7 559.6
6 Migration of workers (per cent
of beneficiaries) 43.4 22.0 -21.4 - 49.3
Graph-7.E: Per Capita Income Earned by Workers Before and After MGNREGS
Intervention in Economically Forward Region (EFR) and Economically
Backward Region (EBR)
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The paired t test results, significant for incremental income earned per annum
and incremental person days of employment obtained per annum after MGNREGS
intervention at 5 per cent and 1 per cent confidence level, respectively, for Hassan
district shows that the scheme had significantly benefited the workers in terms of both
increasing their employment days and annual income.
Table 7.9: Impact of MGNREGS in Hassan District (STZ)
Particulars Before
MGNREGS
After
MGNREGS
Absolute
change
Percentage
change
Paired
t test
Annual mean income (Rs.) 6725 7584.5 859.5 12.8 2.16*
No. of workers per family 2.3 2.6 0.3 13.3 0.95NS
No. of working days per
person per year 187.8 216.3 28.5 15.2 3.15**
Job satisfaction (%) 30 77.5 47.5 158.3
Bank account opened (%) 7.5 95.0 87.5 1166.7
Migration of workers (per
cent of beneficiaries) 22.5 20.1 -2.4 - 10.7
*Significant at5 per cent confidence level, ** Significant at 1 per cent confidence level
NS=Non significant
The paired t test results, significant for incremental income earned per annum
at 5 per cent confidence level and number of workers per family as well as
incremental person days of employment obtained per annum after MGNREGS
intervention at 1 per cent confidence level, for Shivamogga district shows that the
scheme had significantly benefited the workers in terms of providing job to additional
members of the family, increasing their employment days and annual income.
Table-7.10: Impact of MGNREGS in Shivamogga District (STZ)
Particulars Before
MGNREGS After
MGNREGS Absolute change
Percentage change
Paired t test
Annual mean income (Rs.) 6867.5 7750 882.5 12.9 2.49*
No. of workers per family 1.9 2.3 0.4 21.1 2.72**
No. of working days per person per year
187.9 208.8 20.9 11.1 3.35**
Job satisfaction (per cent) 37.5 62.5 25 66.7
Bank account opened (%) 17.5 90 72.5 414.3
Migration of workers (% of beneficiaries)
47.5 32.5 -15 - 31.6
*Significant at5 per cent confidence level, ** Significant at 1 per cent confidence level
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The paired t test results, significant for incremental income earned per annum,
number of workers per family as well as incremental person days of employment
obtained per annum after MGNREGS intervention at 1 per cent confidence level, for
Chitradurga district shows that the scheme had significantly benefited the workers in
terms of providing job to additional members of the family, increasing their
employment days and annual income.
Table-7.11: Impact of MGNREGS in Chitradurga District (CDZ)
Particulars Before
MGNREGS
After
MGNREGS
Absolute
change
Percentage
change
Paired
t test
Annual mean income (Rs.) 6902.5 8250 1347.5 19.5 2.71**
No. of workers per family 1.9 2.8 0.9 47.4 3.59**
No. of working days per
person per year 180 198 18 10.0 3.27**
Job satisfaction (%) 35 70 35 100.0
Bank account opened (%) 7.5 100 92.5 1233.3
Migration of workers (% of
beneficiaries) 35.5 22.5 -13.0 - 36.6
** Significant at 1 per cent confidence level
The paired t test results, significant for incremental income earned per annum,
number of workers per family as well as incremental person days of employment
obtained per annum after MGNREGS intervention at 1 per cent confidence level, for
Davanagere district shows that the scheme had significantly benefited the workers in
terms of providing job to additional members of the family, increasing their
employment days and annual income.
Table-7.12: Impact of MGNREGS in Davanagere District (CDZ)
Particulars Before
MGNREGS
After
MGNREGS
Absolute
change
Percentage
change
Paired t
test
Annual mean income (Rs.) 7122.9 7835.4 712.5 10.0 -6.55**
No. of workers per family 1.9 2.6 0.7 36.8 -7.62**
No. of working days per
person per year 201.1 220.9 19.8 9.8 -6.10**
Job satisfaction (per cent) 20.4 94.6 74.2 363.7
Bank account opened (%) 25.8 100.0 74.2 287.6
Migration of workers (per
cent of beneficiaries) 67.9 12.9 -55.0 - 81.0
** Significant at 1 per cent confidence level
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Table -7.13: Benefits from Governmental Programmes for Canal Irrigated
Area Farmers (CIA) of Tumkur District: 2011
Type of programme Name of the programme/
scheme
No. of farmers
benefited out of
35 farmers (%)
Annual benefit
availed per beneficiary family (Rs)
Frequency of benefit flow
Amortized benefit from
long-term programme/
beneficiary/year (Rs)
1. Programmes concerning food & nutritional security
Ration Card 33 (94) 3984 Monthly
2.
Wage employment schemes
MGNREGA 1 (3) 5000 Once a year SHG loans &
subsidies 6 (17) 1350 Once a year
3.
Education subsidy
Premetric scholarship
13 (37) 815 Once a year
Kaliyuva Makkalige Cycle
8 (23) 2400* One time long term benefit
Amortized benefit =276
4. Integrated Child Development Scheme
Mid-day Meal 13 (37)
765 Daily
5. Social security
Old age pension 11 (31) 4800 Monthly Widow pension 2 (6) 4800 Monthly Disability pension 1 (3) 4800 Monthly
Bhagyalakshmi 2 (6) 19300* # One time long term benefit
Amortized benefit =1305
6. Housing scheme Ashraya 2 (6) 22500*
One time long term benefit
Amortized benefit =2587
Indira Awass Yojana
7 (20) 47857* One time long term benefit
Amortized benefit =5503
7. Electricity Bhagyajyothi 10 (29) 360 monthly
8. Drinking water and sanitation
Panchayath water supply
35 (100) 163 Daily
9. Health Yashaswini 5 (14) 0 Once a year
10. Animal Husbandry Dairy Entrepreneurship Dev.Scheme
1 (3) 10000* One time long term benefit
Amortized benefit =1150
11. Agricultural Department
Comprehensive crop insurance scheme
1 (3) 9000* One time long term benefit
Amortized benefit =1035
Subsidies for seeds
28 (80) 164 Twice a year
subsidies for drip irrigation
1 (3) 45000* One time long term benefit
Amortized benefit =5175
12. Horticulture Department
Suvarna Bhoomi Yojana
1 (3) 9000* One time long term benefit
Amortized benefit =1035
13. Farm Machineries and Implements
Subsidy for Tractor
1 (3) 40000* One time long term benefit
Amortized benefit =4600
Subsidy for Country plough
3 (9) 900* One time long term benefit
Amortized benefit =104
Note: Figures in parentheses indicate percentage to total * indicates benefits from long term benefits. # Under this project, Rs 19, 300 is deposited as fixed deposit in Nationalized Bank in the name of the girl child, which yields Rs 1,0 00,97 after 18 years Source: Sowndarya, D.C., 2012, Utilization of Benefits from Governmental Programmes/Schemes by farmers in Karnataka, M.Sc. Thesis (unpublished), University of Agricultural Sciences, Bangalore.
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Table-7.14: Benefits to Farmers from Governmental Programmes in
Ground Water Irrigation Area (GIA) of Tumkur District: 2011
Type of
programme
Name of the
programme/scheme
No. of
farmers
benefited
out of
35
farmers
(per cent)
Annual
benefit
availed per
beneficiary
family (Rs)
Frequency of
benefit flow
Amortized
benefit from
long-term
programme/
beneficiary/ye
ar (Rs)
1 Programmes
concerning
food and
nutritional
security
Ration Card 34 (97) 3984 Monthly
2
Education
Subsidy
Premetric
Scholarship 11 (31) 427 Once a year
Kaliyuva Makkalige
Cycle 5 (14) 2400*
One time
long
term benefit
Amortized
benefit
=276
3 Integrated
Child
Development
Scheme
Midday Meal 7 (20) 765 Daily
4 Social
Security Old age pension 9 (26) 4800 Monthly
5 Drinking
Water And
Sanitation
Panchayath Water
Supply 35 (100) 155 Daily
6 Health Yashaswini 18 (51) 0 Once a year
7 Animal
Husbandry
Feed distribution
scheme
(from cooperatives)
21 (60) 9806 Monthly
8
Agricultural
Department
Subsidies for seeds 17 (49) 332 Twice a year
Subsidy for drip
irrigation 1 (3) 60000*
One time
long
term benefit
Amortized
benefit
=6900
9
Farm
Machineries
and
Implements
Subsidy for Tractor 1 (3) 30000*
One time
long
term benefit
Amortized
benefit
=3450
Subsidy for Power
tiller 3 (9) 50000*
One time
long
term benefit
Amortized
benefit
=5750 Note: Figures in parentheses indicate percentage to total *indicates benefits from long term benefits
Source: Sowndarya, D.C., 2012, Utilization of Benefits from Governmental Programmes/Schemes by
farmers in Karnataka, M.Sc. Thesis (unpublished), University of Agricultural Sciences, Bangalore.
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206
Table -7.15: Benefits to Farmers from Governmental Programmes in Rainfed
Area (RFA) of Tumkur District: 2011
Type of programme Name of the
programme/scheme
No. of
farmers
benefited
out of
35
farmers
(per cent)
Annual
benefit
availed per
beneficiary
family (Rs)
Frequency of
benefit flow
Amortized
benefit from
long-term
programme/
beneficiary/year
(Rs)
1
Programmes
concerning food
and
nutritional
security
Ration Card 34 (97) 4008 Monthly
2 Education
Subsidy
Premetric
Scholarship 23 (66) 320 Once a Year
Kaliyuva
Makkalige Cycle 16 (46) 2400*
One time long
term benefit
Amortized
benefit =276
3
Integrated Child
Development
Scheme
Mid-day Meal 23 (66) 765 Daily
Anganawadi 4 (11) 765 Daily
4 Social Security
Old age pension 13 (37) 4800 Monthly
Widow pension 1 (3) 4800 Monthly
Disability pension 2 (6) 8400 Monthly
Bhagyalakshmi 3 (9) 19300*≠ One time long
term benefit
Amortized
benefit=1305
5 Housing Scheme
Ashraya 3 (9) 48333* One time long
term benefit
Amortized
benefit=5558
Indira Awas
Yojana 19 (54) 52632*
One time long
term benefit
Amortized
benefit=6052
6 Electricity Bhagyajyothi 30 (86) 360 monthly
7
Drinking Water
and
Sanitation
Panchayath Water
Supply 35 (100) 155 Daily
8 Health Yashaswini 10 (29) 0 Once a Year
9 Animal
Husbandry
Feed distribution
scheme (from cooperatives)
6 (17) 4620 monthly
10 Agricultural
Department Subsidies for seeds 9 (26) 120
Twice a
Year
Note: Figures in parentheses indicate percentage to sample of 35
* indicates benefits from long term
≠ Under this project, Rs 19, 300 is deposited as Fixed Deposit in Nationalized Bank in the
name of the girl child, which yields Rs 1,0 00,97 after 18 years
Source: Sowndarya, D.C., 2012, Utilization of Benefits from Governmental Programmes/Schemes
by farmers in Karnataka, M.Sc. Thesis (unpublished), University of Agricultural Sciences,
Bangalore.
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Study by Sowndarya (2012) on utilization of benefits from governmental
programmes / schemes by farmers in Karnataka shows that on an average a rural
household derived Rs. 3984 worth of benefit per annum through distribution of
subsidized food grains under public distribution system, Rs. 4800 worth of benefit per
annum in the form of old age / widow pension, Rs. 5503 worth of amortized benefit
from Indira Awas Yojana. Income from MGNREGS in the four districts where the
present study was conducted when adjusted for the inflation rate (from the
information presented in Table 7.1) and compared with benefit from other
programmes studied by Sowndarya, was found to be lesser in both economically
backward (Rs. 4240 per annum and Rs. 2,083 per annum in Chitradurga and
Davanagere districts, respectively) and economically forward (Rs. 2,282 per annum
and Rs. 2,512 per annum in Shivamogga and Hassan districts, respectively) regions.
The reason could be that, unlike public distribution system, pension schemes or Indira
Awas Yojana, MGNREGS is an intervention to provide supplementary employment
when the workers do not get any other gainful employment and not a regular
employment generating programme.
To compare incremental income earned by the workers from MGNREGS with
similar income of beneficiaries from other poverty alleviation programmes,
incremental income earned by SGSY beneficiaries in Tamil Nadu during 2003-04
(Rs. 2,500 on an average per annum per household), as reported by Arul Prakash
(2004), was adjusted for inflation (6 per cent). The incremental income per household
from MGNREGS earned by sample respondents in economically forward region (Rs.
2,236 in Hassan district and Rs. 2,031 in Shivamogga district) and economically
backward region (Rs. 3,774 in Chitradurga district and Rs. 1,854 in Davanagere
district) when compared with inflation adjusted incremental income from SGSY in
Tamil Nadu (Rs. 3,346 per annum per household), was found to be substantially lower
except in Chitradurga district. This result again stresses the positive role played by
MGNREGS in severely drought affected districts.
Some of the other studies conducted in various states to assess the incremental
income earned by the beneficiaries of poverty alleviation schemes have shown that
increase in income of the beneficiaries of IRDP, Anthyodaya and Food for Work
Programme in Bihar (1980) was 41 per cent, Anthyodaya programme in Uttar Pradesh
(1981) was about 44 per cent, IRDP in Kerala (1985) was around 28 per cent,
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208
TRYSEM (1996) was 16 per cent which were higher than the incremental income (14
per cent) earned by MGNREGS workers in the selected districts of Karnataka.
Figure-7(ii): Propensity to Consume and Save
E
N
-ve saving
In figure 7(ii) on Y- axis, consumption and savings and on X-axis, income is
measured. C is consumption line, the 45º line is Y = C. At point E, consumption =
income. Before E consumption is greater than income and in this region savings is
negative or the individual is either using his past savings or is borrowing money to
fulfill his consumption needs. After point E on the right hand side consumption is
less than income, the individual saves money.
Analysis of the data collected from the sample workers shows that all the
additional income earned by working in MGNREGS had been utilized to meet their
family consumption needs, except in case of a few women workers, who have shown
positive signs of savings, albeit small. As a result, workers’ marginal propensity to
consume turned out to be 1 and hence marginal propensity to save, in general, was 0,
indicating that the workers have not yet reached a state of Keynesian Psychological
Law of Consumption and are still in the process of fulfilling their basic minimum
needs. This calls for continued employment support through MGNREGS till the
worker households cross the point E shown in Fig. 7(ii).
So, these results have proved our hypothesis that MGNREGS has better
facilitated the enhancement of employment, income and expenditure. But, since MPC
Consu
mpti
on &
Inco
me,
Sav
ing
Positive saving
C < Y
C
Y = C
O
C > Y C=Y
Total Output or Income
Y = a + bx
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209
was 1, MPS proved to be 0, that part of hypothesis stating an enhancement in savings
because of participation in the scheme has to be rejected.
MANOVA Results presented in Table 7.16 shows that F-statistics for number
of working days per person per year was highly significant (at 1 per cent confidence
level) indicating that economically backward and forward regions were significantly
different with respect to number of additional days of employment received by
workers participating in MGNREGS, reiterating the importance of that scheme for
mitigating misery of wage earners in the economically backward regions.
Table-7.16: Difference between Economically Forward and Backward Regions with
respect to MGNREGS Performance Indicators
Particulars Annual mean
income (Rs.)
Number of
workers per
family
Number of
working days per
person per year
Economically Forward
Region (n=160) 7456.50 2.32 199.59
Economically Backward
Region (n=150) 7856.70 2.42 209.87
F-statistics 1.54 0.58 8.25**
**- Significant at 1 per cent confidence level
7.8:MGNREGA and Gender Equity
Though in discharging both farm and household duties and responsibilities
women bear the major burden, it is the men members of the households who take all
the decisions, either social or economic aspects, and opinions of women members are
rarely sought. With an objective of addressing this gender inequality in rural India
MGNREGA has stipulated to reserve 33.33 per cent of the employment generated to
women and pay the same wage rate to both male and female workers. As revealed by
Table 7.17, wage earnings per woman worker in absolute terms as well as in terms of
Index number of their wage income were higher in economically backward region
(Rs. 3,288.2 and 151.31 in Chitradurga and Rs. 2,190.60 and 101.00 in Davanagere,
respectively) than in economically forward region (Rs. 1,732.6 and 79.7 in Hassan
and Rs. 1,481.5 and 68.2 in Shivamogga, respectively). The reason behind differential
participation of women workers in MGNREGS in the two regions could be that
Chitradurga is a severely drought prone district, while Shivamogga is having high
share of irrigated area and hence is agriculturally prosperous resulting in greater
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210
demand for agricultural labour. The women workers could save on an average Rs. 59
per month after participating in MGNREGS. The savings per woman worker did not
have any relationship with the economic status of the district and were higher in
Shivamogga (Rs.74 per month), and Chitradurga (Rs.67) districts compared to Hassan
(Rs.54) and Davanagere (Rs.40) districts.
Participation of women workers in decision making pertaining to household
management varied from a higher participation to the tune of 65 per cent in
Shivamogga district to lower participation to an extent of 33 per cent in Davanagere
district, with an average participation of 59 per cent. Membership of women workers
in Self Help Groups was above 80 per cent on an average, while it was cent per cent
in the economically backward region.
MGNREGA has played a positive role in empowering women in the study
areas.
Roy (2009) in his study conducted in Tripura found that MGNREGS enabled
women workers to buy LIC policies and Recurring Deposit accounts, there by
empowering them. Economic empowerment of women through MGNREGA was also
reported by Sudha Narayan (2008) in Tamil Nadu and Naganagoud and Uliveppa
(2010) in their study at the national level. The results of the present study are in
conformity with those results.
Table -7.17: Participation of Women Workers in MGNREGS in STZ and CDZ
Region District
Wage bill
from
MGNREGP
(Rs.)
Index
number
of wage
income
(Average
= 100)
Bank /
Post
Office
account
opened
(%)
Savings
per month
(Rs.)
Participation
in house hold
decision
making
(%of
beneficiaries)
Member
-ship in
SHG
(%)
Economi
cally
Forward
Region
(STZ)
Hassan 1732.6 79.7 93.8 53.8 43.4 82.9
Shivamogga 1481.5 68.2 94.4 74.5 65.4 67.2
Economi
cally
Backwar
d Region
(CDZ)
Chitradurga 3288.2 151.31 100 66.7 44.5 100.0
Davanagere 2190.6
101
100
40.0
33.3
100.0
Average 2173 100 97.1 59 47 88
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These results show that MGNREGA has a positive influence on all the five
components of women empowerment viz; : (i) women's sense of self-worth with
MGNREGA ensuring same wage rate to women as that of men (ii) their right to have
and to determine choices provided by 100 days of employment guaranteed by
MGNREGA (iii) their right to have access to opportunities and resources ensured by
one-third of the MGNREGS employment reserved for women (iv) their right to have
the power to control their own lives, both within and outside the home as the women
workers expressed in the interviews for the study that they have a say in decision
making relating to at least family affairs now (v) Their ability to influence the
direction of social change to create a more just social and economic order, nationally
and internationally is positively affected, at least at the village level, though not at the
national / international level, facilitated by their participation in socio-economic
activity groups at the community level, like Self Help Groups (SHGs).
As Young (1993) puts it, empowerment is achieved if and when women set
the agenda, organize mutual self help in the neighbourhood, group or network,
demand accountability by the state and society for change. It is the women´s needs
and visions that are at the centre point.
This will require support from men to change those aspects of their behaviour,
roles and privileges which currently discriminate against women. The extent of
current disadvantage and inequality means that women’s empowerment may require
support by development agencies at household, community and macro levels.
MGNREGA has done exactly that by providing women equal employment
opportunity, equal wages, participation in gram sabhas to decide the works to be taken
up in the village under MGNREGS, financial inclusion through opening of bank
accounts and participating in SHGs and being part of social auditing of the scheme.
Similarly, the results of this study are in conformity with Longwe’s (1989,
1991) argument on progression in women empowerment with respect to access to
resources of production, participation in decision making process and equality of
control over distribution of benefits so that neither men nor women are in a position
of dominance.
The results also show that MGNREGS benefits are paving in the right
direction concerning gender issues to fit in to CASHE’s Empowerment Matrix
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regarding women’s economic, social and political empowerment at individual,
household and community level.
Based on the results and discussions presented in the preceding paragraphs we
accept our fifth hypothesis that participation of women workers in MGNREGS has
increased their involvement in social and economic group activities and household
decision making and has enhanced their economic empowerment.
7.9: Monitoring of MGNREGS works in STZ and CDZ
MGNREGA has twin basic objectives of providing livelihood security to rural
populace and at the same time creating durable assets, useful for the community. In
this context the issue of involvement of contractors and use of mechanical devices in
the execution of works under MGNREGP and obtaining technical guidance from the
experts from the concerned development department/s are crucial. Periodic
supervision of the progress of work by the relevant development department, and
certification of quality of works executed by the competent authority at the district /
taluk / panchyath levels are inbuilt in MGNREGA. To ensure transparency at all
levels Management Information System (MIS) has been introduced in the programme.
Details pertaining to efficacy of execution and monitoring of MGNREGS is presented
in Table 7.18.
Among the four sample districts of STZ and CDZ only in Chitradurga
evidence of use of contractors and machineries to execute works under MGNREGS
was found. The workers responded that measurement of work was done regularly and
in time. However, technical guidance regarding location and supervision of
MGNREGS works was poor which needed to be improved through coordination and
convergence among line departments to ensure quality of assets created. As
complained by Gram Panchayath officials delay in completing MB book was causing
delay in disbursement of wages. As part of monitoring process the concerned Zilla
Panchayath engineers were certifying the works executed before labour payment.
The Social Audit is an integral part of monitoring and evaluation procedures
instituted in order to appraise the performance of MGNREGS works. But, except for a
few workers in Shivamogga district, the participants in MGNREGS were unaware of
social audit. Social auditing was yet to be initiated in most of the Gram Panchayaths
under study. Prompt social audit involving all the stakeholders would ensure
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transparency in administration, financial accounting, and efficiency in implementation
of the program.
Implementation of MIS was good in economically forward region where as it
was moderate in economically backward region. Although MIS was maintained
appreciably at district level and at block levels, frequent power failure and internet
connectivity problems were affecting functioning of MIS at Gram Panchayath levels.
Computer operators had been appointed in most of the Gram Panchayaths for MIS
maintenance. Unfotunately, in some taluks like Molakalmur in Chitradurga district,
the computer operators had to periodically visit block offices to update MGNREGS
information since the Panchayath Offices did not have UPS and for that reason all the
computers of Gram Panchayaths had been installed in block offices. So, it was found
necessary to supply solar energy charged UPS systems to Gram Panchayaths for the
maintenance of unhindered ICT.
Table-7.18: Details of Monitoring of MGNREGS Works in STZ and CDZ
* The Executive Officer informed that Social Auditing was undertaken in this region,
However the workers were not aware about this process.
Particulars
Economically Forward
Region (STZ)
Economically Backward
Region (CDZ)
Hassan Shivamogga Chitradurga Davanagere
Execution
of work
Work done by
contractors and
machine labour
No No Yes No
Measurement of
work done one time
with in a fortnight
Yes Yes Yes Yes
Technical
supervision No No No No
Monitoring
Measurement of
work done Yes Yes Yes Yes
Certification of
work done Yes Yes Yes Yes
Monitoring
functionaries
Gram
Panchayath
and Block
Level Office
Gram
Panchayath
Gram
Panchayath
Gram
Panchayath
Social audit done (Yes/No) No Yes No No*
Implementation of Management
Information System Good Good Moderate Moderate
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7.10: MGNREGS and Natural Resource Conservation
MGNREGA lists nine categories of works to be taken up to create wage
employment for the needy rural people. Natural resource conservation gets priority in
creating community assets under MGNREGA. The empirical study results presented
in Table 7.19 and Graph 7.F to 7.I show that both in Economically Forward Region
and Economically Backward Region natural resource conservation activities including
construction of water conservation structures, irrigational canals and rehabilitation of
traditional water bodies were given priority and they accounted for more than 50 per
cent of the MGNREGS expenditure during the study period. However, only in
Davanagere district rural connectivity was also given importance (27 per cent of the
total MGNREGS expenditure) in selection of works by the Gram Sabha. The works
on individual cultivators’ farm accounted for a mere three per cent of the total
utilization.
Table-7.19 : Proportion of MGNREGS Expenditure in Percentage on
Different Types of Works in STZ and CDZ
Type of Work
Economically
Forward Region
(STZ)
Economically Backward
Region (CDZ)
Hassan Shivamogga Chitradurga Davanagere
Flood control 0.50 5.31 11.31 17.08
Rural connectivity 2.32 7.79 3.76 26.95
Water conservation and water
harvesting 28.45 5.22 50.10 14.00
Renovation of traditional water
bodies 33.93 17.96 7.96 5.50
Drought proofing 9.16 9.23 6.45 20.80
Irrigation canals 12.64 25.69 6.89 5.33
Irrigation facilities to SC/ST/IAY 1.78 1.72 2.34 3.35
Land development 7.00 18.26 3.26 4.03
Other works 4.21 8.83 7.94 2.95
Total 100.00 100.00 100.00 100.00
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Graph-7.F: Proportion of MGNREGS Expenditure in Percentage on
Different Types of Works in Hassan District (STZ)
Graph-7.G: Proportion of MGNREGS Expenditure in Percentage on
Different Types of Works in Shivamogga District (STZ)
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Figure-7.H: Proportion of MGNREGS Expenditure in Percentage on
Different Types of Works in Chitradurga District (CDZ)
Graph-7.I: Proportion of MGNREGS Expenditure in percentage on
Different Types of Works in Davanagere District (CDZ)
Earlier studies conducted by Arun and Richard (2006) and Kareemullah et al
(2009) have also shown that similar to the results of the present study, priority was
accorded to natural resource management in MGNREGS works selection in the
neighbouring states of Kerala and Andhra Pradesh.
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7.11: Impact of MGNREGS on Village Development
Natural resource conservation works like rejuvenation of water bodies and
water conservation activities, taken up under MGNREGP increased the area under
irrigation, improved ground water recharge, in tank as well as well command areas
and improved incomes of farmers. The details of works executed and short term
impacts are presented in Table 7.11.
Table -7.20: Types of Works Executed And the Short Term Impact of
MGNREGA on Natural Resource Conservation Sl.
No. Works executed Short term impact
Areas where impact was
felt
1 Desiltation of Tanks Improved water bodies. Improvement in water
impounding and ground water recharging.
Increased irrigated area. Double cropping.
All sample districts.
2 Construction of
Check dams
Improvement in water table.
.
All sample districts.
3 Rejuvenation of
Water bodies
Increased availability of drinking water for
livestock during the summer season.
Davanagere
(Harapanahalli Taluk) and
Hassan districts.
4 Clearing drainages
and diverting excess
water flow
Flooding of roads and houses in the low lying
areas and disruption of vehicular traffic during
rainy days, stagnant water creating health
hazards avoided.
Shivamogga (Bhdravati
Taluk), Chitradurga
(Hiriyur Taluk), and
Davanagere districts.
5 Bunding and Land
development
activities
Reduction in soil erosion and improvement in
land productivity.
Shivamogga (Bhadravati
Taluk) and Hassan
(Arasikere Taluk) districts.
7.12: Factors affecting performance of MGNREGS in sample districts of
Economically Forward and Backward Regions of Karnataka
To identify the those factors that affect the performance of MGNREGS in
economically backward and forward regions and suggest measures to improve its
efficacy in poverty alleviation from rural India, Discriminant Analysis, Factor
Analysis and Cluster Analysis were undertaken. Pertinent data for the analysis were
obtained from MGNREGA website for a time period of four years from 2008-09 to
2011-12. The results of the analysis with suggestions for improvement are presented
hereunder.
7.12(i): Discriminant Analysis
Among the 18 variables considered for the analysis seven variables were
found to discriminate the economically backward and the economically forward
regions (Table 7.21 to 7.28). In economically forward region, 10,121 families fell
under BPL category, while in economically backward region 21,791 families were
BPL. Similarly the employment provided in person days was 5,28,390 in
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economically backward region, while in economically forward region, the
employment received was 6,73,060 person days. In case of other variables, the levels
of variables were comparable. The coefficient of variation of all the variables except
that of number of BPL households and rural connectivity in kms had crossed 100 per
cent of variation and showed very high variability. These high variations resulted in
difficulty in generalizing.
The data regarding extent of MGNREGS activities under different heads are
provided in MGNREGA website. The data for eighteen variables viz; rural
connectivity in kms, flood control and protection in kms, water conservation and
water harvesting in cubic meters, drought proofing in hectares, micro irrigation Works
in kms, renovation of traditional water bodies in Cubic meters, land development in
hectares, number of workers with bank / post office account number, number of job
cards issued, number of households registered in MGNREGS, number of households
whose status is BPL, number of small farmers, number of marginal farmers, land
reform beneficiaries, IAY beneficiaries, employment provided under MGNREGS in
Person days, funds available for the scheme in lakh Rupees, between 31-90 days
delay in issuing Job cards, were obtained from the official website of MGNREGA for
the economically backward districts of Chitradurga and Davanagere and economically
forward districts of Shivamogga and Hassan. These variables were hypothesized to
discriminate the economically forward region from the economically backward region
with regard to MGNREGS works. From among those 18 variables, the canonical
discriminant function identified seven vital variables, which contributed to explaining
around 82 per cent of the Discriminant function. The balance 18 per cent of the
variation in the Discriminant function was not explained as indicated by the Wilks’
lambda value. The seven variables which discriminated the economically forward
region from that of the economically backward region were number of households
whose status has been BPL (1.794), employment Provided in Person days ( -1.264),
water conservation and water harvesting in cubic meters (-0.925), rural connectivity
in kms (0.855), renovation of traditional water bodies in Cum (0.762), drought
proofing in hectares (0.463) and IAY beneficiaries in numbers (0.347) in the order
of importance in discrimination of economically forward with economically backward
areas with regard to MGNREGS implementation.
The results of dicriminant function analysis can be validated with the field
level observation. The number of households under BPL in economically backward
region was double the number in economically forward region. The objective of
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MGNREGA is to ensure livelihood security to the rural mass and help them to move
to APL category. The results of the study show that employment provided in person
days in backward region was nearly 30 per cent more than that in economically
forward region, rural connectivity works taken up was three times more, renovation of
traditional water bodies was four times higher, drought proofing work was double,
benefits extended under IAY was ten per cent higher in economically backward
region than in the economically forward region. This shows that the activities
undertaken under MGNREGS is in the right direction as envisioned. The activities
have to be further strengthened to achieve the goal of poverty alleviation in rural
India. The results prove our seventh hypothesis that drought proneness and proportion
of cultivated area under irrigation are two of the major factors (though not the only
two) contributing to performance of MGNREGS.
Table 7.21: Variables Discriminating Economically Forward Region from
Economically Backward Region in Karnataka with Respect to
MGNREGS Activities: 2008-09 to 2011-12
Sl.
No Discriminating variables
Mean for
Economically
Backward
region (d1)
Coefficien
t of
Variation
Mean for
Economicall
y forward
region (d2)
Coefficient
of
Variation
1 Rural Connectivity in Kms. 38 37 11 114
2 Water Conservation and Water
Harvesting in Cum 4 180 4 146
3 Drought Proofing in Hect 2 257 1 178
4 Renovation of traditional
water bodies in Cum 9 232 2 132
5 BPL Households in numbers 21791 58 10121 63
6 IAY Beneficiaries in numbers 220 118 199 131
7 Employment Provided in
Person days 673060 130 528390 49
Summary of Canonical Discriminant Functions
Table-7.22: Eigenvalues
Function Eigenvalue
Per cent of
Variance
Cumulative
Percentage
Canonical
Correlation
1 4.605a 100.0 100.0 .906
a. First 1 canonical discriminant functions were used in the analysis.
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Table-7.23: Wilks’ Lambda
Test of Function(s) Wilks’ Lambda Chi-square df Sig.
1 .178 37.057 7 .000
Table -7.24: Contribution of Variables Towards Discriminant Function (in %)
Sl.
No.
Variables Standardized Discriminant
Coefficient (SDC)
1 Rural_Connectivity_KM .855
2 Water_Conservation_Water_Harvesting_Cum -.925
3 Drought_Proofing_Hect .463
4 Renovation_traditional_water_bodies_Cum .762
5 BPL_HHS 1.794
6 IAY_Beneficiary .347
7 Employment_Provided_Persondays -1.264
Discriminant function analysis shows that MGNREGS meets the ‘equity’
considerations, since the forward and backward regions cannot be treated uniformly,
according to the Hirshmanian unbalanced growth hypothesis. The Hirschman’s
unbalanced growth theory states that the economy should give selective impetus to
those sectors which contribute to growth. MGNREGS can be said to have achieved
‘Equity with Inclusive growth’, since the employment provided in economically
backward region and forward region are distinct. Hence, economically backward
region should continue to receive higher attention and higher MGNREGS
opportunities compared with forward regions. The discriminant function analysis has
apparently identified the number of BPL households and the employment
opportunities created by MGNREGS as the most important variables which are
distinct across the backward and forward regions of Karnataka. Thus, creation of
employment opportunities under MGNREGS in the region having higher number of
BPL households has led to welfare gain due to its differential focus considering the
level of development.
The economically backward areas are prone to frequent droughts. With poor
on-farm and macro agricultural infrastructure, farmers in dry land areas are cultivating
crops such as groundnut, millets, maize and frequently out migrate in search of
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employment. In order to check outmigration, it is in order for the administration to
further strengthen MGNREGS activities in economically backward region by offering
higher employment opportunities than in the forward region. This will lead to
inclusive growth as well as sustainable growth, addressing the social tensions due to
recurrent drought as well as in reducing income inequalities caused due to natural
factors including climate change. Activities including water conservation, rural
connectivity, renovation of traditional water bodies, drought proofing and
construction of houses under IAY for socially downtrodden families would address
the equity issues in the rural areas in the process of poverty alleviation.
These results along with performance index of expenditure, performance index
of works completed and performance in terms of employment provided, which were
much higher in economically backward region when compared with that in
economically forward region (Table 7.1), indices of number of days worked under
MGNREGS which show that extent of utilization of MGNREGA provision was
higher in economically backward region than in economically forward region (Table
7.6), wage earnings per woman worker in absolute terms as well as in terms of Index
number of their wage income, which were higher in economically backward region
than in economically forward region (Table 7.17), show that backward districts have
greater potential for MGNREGA activities.
7.12(ii): Factor Analysis
Factor analysis aims at determination of latent variables subsumed in a set of
original variables. It provides a means of explaining variation among relatively large
number of original variables. This corresponds to dimension reduction or information
condensation function of factor analysis, through which the variation among large set
of original variables can be accounted for by using fewer unobservable variable called
latent variable or dimensions. Further, this technique helps in interpretation of
substantive content of the latent variables or dimensions or factors which account for
variation among large set of variables. The results of the analysis are as follows.
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7.12(iii): Factor Analysis for Economically Forward Region (Hassan District)
The rotated component matrix for Hassan district, an economically forward
region, demonstrated that all the seven variables grouped under the two dimensions
were positively associated. The first dimension explained 54 per cent of the variation
in the seven variables, while the second dimension explained 25 per cent [Table 7.25
(i) and (ii)]. As the first dimension was influenced by employment provided in person
days, number of BPL households, water conservation and water harvesting in cubic
meters and rural connectivity in kms, the first dimension was accordingly termed as
“Rural Poverty and Infrastructure”.
Table -7.25: Factor Loading of MGNREGS Parameters in Hassan District
(Economically Forward Region) for the Years 2008-09 to 2011-12
7.25 (i) Total Variance Explained
Component
Initial Eigenvalues Rotation Sums of Squared Loadings
Total Per cent of
Variance
Cumulative
Percentage Total
Per cent of
Variance
Cumulative
Percentage
1 3.786 54.085 54.085 3.785 54.075 54.075
2 1.772 25.314 79.399 1.773 25.324 79.399
3 .991 14.157 93.556
4 .336 4.799 98.355
5 .075 1.074 99.429
6 .032 .463 99.892
7 .008 .108 100.000
Extraction Method: Principal Component Analysis.
7.25(ii) Rotated Component Matrixa
Variables Component
1 2
Employment Provided in Person days .988
BPL Households in numbers .963
Water Conservation and Water Harvesting in Cum .963
Rural Connectivity in Kms .939
Renovation of traditional water bodies in Cum .904
IAY Beneficiaries in number .724
Drought Proofing in Hectares .570
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
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Variables Component
1 2
Employment Provided in Person days .988
BPL Households in numbers .963
Water Conservation and Water Harvesting in Cum .963
Rural Connectivity in Kms .939
Renovation of traditional water bodies in Cum .904
IAY Beneficiaries in number .724
Drought Proofing in Hectares .570
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
The second dimension was influenced by renovation of traditional water
bodies, number of IAY beneficiary households and drought proofing. Accordingly,
the second dimension was termed as “Natural Resource Management”. However, the
empirical study results are in contradiction with the factor analysis results with respect
to person days of employment provided and expenditure on rural connectivity, while
the results are in conformity with empirical study results regarding renovation of
traditional water bodies and water conservation activities with an allocation of 63 per
cent of the total budget (Table 7.19 and Graph. 7.F).
7.12(iv): Factor Analysis for economically forward region (Shivamogga district)
The two dimensions governing development in Shivamogga district through
MGNREGS among the seven variables are provided in the rotated component matrix.
The first dimension explained 48 per cent of the variation in the seven variables,
while the second dimension explained 25 per cent of the variation (Table 7.26 (i) and
(ii)). The first dimension encompassed four variables viz; water conservation and
water harvesting, renovation of traditional water bodies, and drought proofing. Thus,
the first dimension was named as “Natural Resource Management”. The second
dimension included two variables, viz., number of BPL households and rural
connectivity which were positively associated, while the IAY beneficiary households
were negatively associated. The second dimension was termed as “Rural Poverty” as
it dealt with variables closely associated with poverty. Thus, the focus of MGNREGS
in Shivamogga district, has to be first on Natural Resource Management followed by
Rural Poverty.
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Table 7.26: Factor Loading of MGNREGS Prameters in Shivamogga District (Economically Forward Region) for The Years 2008-09 to 2011-12 7.26 (i): Total Variance Explained
Component
Initial Eigenvalues Rotation Sums of Squared Loadings
Total Per cent of
Variance
Cumulative
Percentage Total
Per cent of
Variance
Cumulative
percentage
1 3.384 48.339 48.339 3.372 48.174 48.174
2 1.747 24.964 73.303 1.759 25.130 73.303
3 1.412 20.172 93.475
4 .399 5.706 99.181
5 .038 .549 99.730
6 .019 .270 100.000
7 -2.950E-17 -4.214E-16 100.000
Extraction Method: Principal Component Analysis.
7.26 (ii) Rotated Component Matrixa
Variables Component
1 2
Water Conservation and Water Harvesting in Cum .973
Renovation of traditional water bodies in Cum .942
Drought Proofing in Hectares .932
Employment Provided in Person days .700
IAY Beneficiaries in number -.912
BPL Households in number .761
Rural Connectivity in Kms .515
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations
The empirical evidence presented in Table 7.19 and Graph 7.G validate the
factor analysis results with 62 per cent of MGNREGS expenditure for the year 2008-
09 spent on natural resource management such as renovation of traditional water
bodies, construction of irrigation canals and land development.
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7.12(v): Factor Analysis for Economically Backward Region (Chitradurga
District)
From among the most disadvantaged districts identified by the National
Planning Commission in Karnataka, Chitradurga, Davanagere and Bidar stand out. In
Chitradurga district, the first dimension was greatly influenced by employment
provision, renovation of traditional water bodies, number of IAY beneficiaries and the
number of BPL households. In the second dimension, while water conservation and
water harvesting and rural connectivity were positively associated, drought proofing
was negatively associated. Hence, the first dimension was called “Rural Poverty”
since the variables employment provided, number of IAY beneficiaries and number of
BPL Households are adequately represented by poverty. The second dimension which
includes rural connectivity, drought proofing and water conservation, was termed as
“Rural infrastructure”. The first dimension “Rural Poverty” captured 53 per cent of
the variation in the seven variables governing MGNREGS performance, while the
second dimension “Rural Infrastructure” captured 36 per cent of the variation. In
order to develop Chitradurga district, an economically backward region, the primary
focus for the policy maker is to concentrate on ‘Rural poverty” through MGNREGS,
followed by creating “Rural infrastructure” for inclusive growth (Table 7.27 (i) and
(ii)).
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Table-7.27: Factor Loadings of MGNREGS Parameters in Chitradurga District
(Economically Backward Region) for the Years 2008-09 to 2011-12
7.27(i) Total Variance Explained
Component
Initial Eigenvalues Rotation Sums of Squared Loadings
Total Per cent of
Variance
Cumulative
Percentage Total
Per cent of
Variance
Cumulative
Percentage
1 4.088 58.393 58.393 3.733 53.331 53.331
2 2.093 29.893 88.286 2.447 34.955 88.286
3 .662 9.459 97.745
4 .134 1.908 99.654
5 .024 .346 100.000
6 8.336E-17 1.191E-15 100.000
7 -1.713E-16 -2.448E-15 100.000
Extraction Method: Principal Component Analysis.
Table-7.27(ii) Rotated Component Matrixa
Variables Component
1 2
Employment Provided in Person days .954
Renovation of traditional water bodies in Cum .952
IAY Beneficiaries in number .951
BPL Households in number .909
Water Conservation and Water Harvesting in Cum .947
Rural Connectivity in Kms .850
Drought Proofing in Hectares -.750
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Among the four districts selected for the study MGNREGS had provided the
maximum employment to the tune of 3 lakh person days in Chitradurga during 2008-
09 (Table 7.1). And hence, the identification of poverty as the crucial dimension is
appropriate. With 50 per cent of total MGNREGS expenditure devoted to water
conservation and water harvesting works during the same year (Table 7.19 and Graph
7.H), the second dimension has been appropriately identified as Rural Infrastructure.
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7.12(vi): Factor Analysis for Economically Backward Region (Davanagere District)
Using the Principal component method, Varimax rotation had been employed
in extracting dimensions governing MGNREGS performance in the economically
backward region (Davanagere district). Accordingly, two dimensions were extracted,
which explained 60 per cent of the total variation in MGNREGS performance [Table
7.28 (i) and (ii)].
Table -7.28: Factor Loadings of MGNREGS Parameters in Davanagere District
(Economically Backward Region) for the Years 2008-09 to 2011-12
Table-7.28 (ii) Rotated Component Matrixa
Table-7.28 (i) Total Variance Explained
Component
Initial Eigenvalues Rotation Sums of Squared Loadings
Total Per cent of
Variance
Cumulative
Percentage Total
Per cent of
Variance
Cumulative
Percentage
1 2.435 34.779 34.779 2.319 33.135 33.135
2 1.821 26.018 60.798 1.936 27.662 60.798
3 1.476 21.082 81.880
4 1.113 15.895 97.775
5 .156 2.225 100.000
6 2.223E-16 3.175E-15 100.000
7 -1.956E-17 -2.794E-16 100.000
Extraction Method: Principal Component Analysis.
Component
Variables 1 2
Rural Connectivity in Kms .900
Renovation of traditional water bodies in Cum -.845
IAY Beneficiaries in number .643
Employment Provided in Person days .483
BPL Households .887
Water Conservation and Water Harvesting in Cum .868
Drought Proofing in Hectares -.348
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
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The first dimension comprising of four variables and the second dimension
holding three variables highlight their relative importance. Among the four variables,
rural connectivity, number of households which are beneficiaries of IAY, employment
provided in person days had a positive association with the first dimension. However,
the variable, renovation of traditional water bodies had negative association. Among
the three variables in the second dimension, the number of BPL households, and
water conservation and water harvesting had a positive association with the
dimension, while the variable drought proofing was negatively associated with the
dimension. Thus, the first dimension was named as “Rural Infrastructure” and the
second dimension was termed as “On Farm Infrastructure”, which is crucial for BPL
households in terms of water conservation and water harvesting. Rural Infrastructure,
the first dimension, captured 33 per cent of the variation in the seven variables
governing MGNREGA performance, while the second dimension, On Farm
Infrastructure, captured 28 per cent of the variation.
The empirical evidence from the study conducted in Davanagere district
during 2008-09 (Table 7.19 and Graph 7.I) showed that rural connectivity which is an
important component of rural infrastructure development with 27 per cent of the total
MGNREGS expenditure during 2008-09 had been given the utmost importance with a
high factor loading of 0.90 in factor analysis. Identification of water conservation and
water harvesting work as one of the crucial component of second dimension (farm
infrastructure) having a factor loading of 0.868 is in conformity with the findings of
present empirical study.
Hence, the policy makers need to focus on development of “Rural
infrastructure”, followed by “On Farm Infrastructure” in Davanagere district through
MGNREGS.
Thus, looking into the results of Factor Analysis for Hassan and Shivamogga
districts, it can be said that the focus of development through MGNREGS in
economically forward region should be on Natural Resource Management, while in
economically backward region consisting of Davanagere and Chitradurga districts the
onus of the scheme activity has to be on Rural Infrastructure development.
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7.12(vii): Cluster Analysis
The objective of cluster analysis is to group the variables into clusters
such that elements within a cluster have a high degree of "natural association"
among themselves, while the clusters are "relatively distinct" from one another. The
results of cluster analysis for the two regions comprising of four districts is presented
below.
7.12(viii): Cluster Analysis for Econommically Forward Region (Hassan District)
In Hassan district, an economically forward region, the cluster analysis has
identified two clusters of taluks. The first cluster included Holenarasipura,
Sakaleshpur, Belur, Arakalgud, Alur, Arasikere and Channarayapatna taluks. The
second cluster consisted of only Hassan taluk. Within the flrst cluster, Holenarasipura
and Sakaleshpur were closer with regard to seven variables considered, as indicated
by the similarity index of 98 per cent, followed by Holenarasipura, Sakaleshpur, Belur
and Arakalgud with a similarity index of 97.39 per cent, Holenarasipura, Sakaleshpur,
Belur, Arakalgud and Alur taluks with a similarity index of 97 per cent,
Holenarasipura, Sakaleshpur, Belur, Arakalgud, Alur and Arasikere taluks with a
similarity index of 95 per cent and Holenarasipura, sakaleshpur, Belur, Arakalgud,
Alur, Arasikere and Channarayapatna taluks with a similarity index of 91 per cent.
The squared euclidean distance between the two clusters was 3,96,149 (Table 7.29 (i)
and (ii) and Graph 7.J). Since there were disimilarities with regard to all the seven
varibales between seven taluks included in two clusters, all the variables have to be
addressed with equal importance to bring uniformity in MGNREGS performance and
its impact in Hassan district.
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Table 7.29(i) : Cluster Profiles in Hassan District (Economically Forward Region)
for the Years 2008-09 to 2011-12
Sl.
No. Variable Cluster1 Cluster2
Grand
centroid
1 Rural Connectivity in kms 11 48 16
2 Water Conservation and Water Harvesting in
Cubic meters 5 19 7
3 Drought Proofing in Hectares 2 0 2
4 Renovation of traditional water bodies in Cubic
meters 4 0 3
5 Number of households whose status has been
selected as BPL 6914 22442 8855
6 Number of IAY Beneficiaries 104 10 93
7 MGNREGS employment Provided in Person
days 359273 1047772 445335
Table 7.29 (ii): Similarity Index and Squared Euclidean Distance in Hassan District
Step No. of
clusters
Similarity
level
Distance
level Clusters joined
New
cluster
No. of
observations in
new cluster
1 7 98.6002 12501 7 8 7 2
2 6 97.3986 23232 3 5 3 2
3 5 96.9891 26890 2 4 2 2
4 4 95.6228 39091 2 7 2 4
5 3 91.0808 79655 1 2 1 5
6 2 64.4503 317482 1 3 1 7
7 1 55.6416 396149 1 6 1 8
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Graph-7.J: Cluster Formation in Hassan District (Economically Forward Region)
HASSAN
CHANNARAYAPATNA
ARSIKERE
SAKALESHPUR
HOLENARSIPUR
BELUR
ARKALGUD
ALUR
55.64
70.43
85.21
100.00
TALUKS
Similarity
HASSAN
7.12(ix): Cluster Analysis for Economically Forward Region (Shivamogga
District)
In Shivamogga district, an economically forward region, the cluster analysis
has identified two clusters of taluks. The first cluster comprised of Bhadravati,
Soraba, Hosanagara, Sagar and Shivamogga taluks and the second cluster had
Shikaripur and Thirthahalli taluks. Within the flrst cluster, Hosanagara and Sagar
taluks were close with regard to seven variables considered, as indicated by the
similarity index of 96 per cent. Then Hosanagara, Sagar and Shivamogga taluks were
closer with a similarity index of 95 per cent. Next, Hosanagara, Sagar, Shivamogga ,
Soraba and Bhadravthi taluks were closer with a similartiy index of 94 per cent. All
these five taluks were closer with respect to similarity in performance of MGNREGS
activities reflected in seven varibales. The two clusters had a squared euclidean
distance of 2,34,651 (Table 7.30 (i) and (ii) and Graph 7.K). Since there were
disimilarities with regard to all the seven varibales between seven taluks included in
two clusters, all the variables have to be addressed with equal importance to bring
uniformity in MGNREGS performance and its impact in Shivamogga district.
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Table-7.30 (i) : Cluster Profiles in Shivamogga District (Economically Forward
Region) for the Years 2008-09 to 2011-12
Sl.
No. Variable Cluster1 Cluster2
Grand
centroid
1 Rural Connectivity in kms 8 3 6
2 Water Conservation and Water Harvesting in Cubic
meters 3 0 2
3 Drought Proofing in Hectares 1 0 1
4 Renovation of traditional water bodies in Cubic
meters 0 0 0
5 Number of households whose status has been
selected as BPL 10851 13360 11568
6 Number of IAY Beneficiaries 232 543 320
7 MGNREGS employment Provided in Person days 714819 394557 623316
Table-7.30( ii) Similarity Index and Squared Euclidean Distance in Shivamogga
District
Step No. of
clusters
Similarity
level
Distance
level Clusters joined
New
cluster
No. of
observations in
new cluster
1 6 95.7072 17836 2 3 2 2
2 5 95.2665 19667 2 5 2 3
3 4 94.1353 24367 1 6 1 2
4 3 88.7045 46932 1 2 1 5
5 2 82.2182 73883 4 7 4 2
6 1 43.5249 234651 1 4 1 7
Graph-7.K: Cluster Formation in Shivamogga District (Economically Forward Region)
TIRTHAHALLISHIKARPURSHIMOGASAGARHOSANAGARASORABBHADRAVATI
43.52
62.35
81.17
100.00
TALUKS
Similarity
SHIMOGA
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7.12(x): Cluster Analysis for Economically Backward Region (Chitradurga
District )
The cluster analysis has identified two clusters of taluks in economically
backward region of Chitradurga. Within the flrst cluster, Chitradurga and Hosadurga
taluks were close with regard to the seven variables considered, as indicated by a
similarity index of 95 per cent. Next, Chitradurga, Hosadurga, Molakalmur and
Hiriyur taluks were closer with a similarity index of around 87 per cent. The first and
second clusters were distant, with the squared euclidean distance of 9,76,308 [Table
7.31 (i) and (ii)]. Here, Challakere Taluk alone formed the first cluster, while
Chitradurga taluk, Hosadurga Taluk, Molakalmur Taluk, Hiriyur Taluk and Holalkere
Taluk belonged to the second cluster. Considering the seven variables with which the
two clusters were identified, Water Conservation and Water Harvesting, were uniform
between the two clusters, while the remaining variables viz; (1) Rural Connectivity,
(2) Drought Proofing, (3) renovation of traditional water bodies, (4) number of BPL
households, (5) the number of IAY beneficiareis and (6) employment provided were
distinct between the two clusters. Thus, in order to achieve inclusive growth, in
Chitradurga district, it is crucial to focus on all these six variables. In addition, this
will bring closer the two clusters of Holalkere on to Chitradurga with Challakere.
Table-7.31(i): Cluster Profiles in Chitradurga District (Economically Backward
Region) for the years 2008-09 to 2011-12
Sl.
No. Variable Cluster1 Cluster2
Grand
centroid
1 Rural Connectivity in kms 41 27 29
2 Water Conservation and Water Harvesting in Cubic
meters 2 2 2
3 Drought Proofing in Hectares 0 3 3
4 Renovation of traditional water bodies in Cubic
meters 0 0 0
5 Number of households whose status has been
selected as BPL 50122 26128 30127
6 Number of IAY Beneficiaries 679 196 277
7 MGNREGS employment Provided in Person days 2744657 1063505 1343697
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Table -7.31 (ii): Similarity Index and Squared Euclidean Distance in
Chitradurga District
Step No. of
clusters
Similarity
level
Distance
level Clusters joined
New
cluster
No. of
observations
in new
cluster
1 5 95.4455 94643 2 5 2 2
2 4 91.804 170312 2 6 2 3
3 3 91.2559 181701 2 3 2 4
4 2 68.4676 655244 2 4 2 5
5 1 53.0169 976308 1 2 1 6
Graph-7.L: Cluster Formation in Chitradurga District (Economically Backward Region)
HOLALKEREHIRIYURMOLAKALMURUHOSDURGACHITRADURGACHALLAKERE
53.02
68.68
84.34
100.00
TALUKS
Similarity
CHITRADURGA
7.12(xi): Cluster Analysis for Economically Backward Region (Davanagere
District)
The cluster analysis was performed on seven variables with a view to identify
two clusters. Accordingly the analysis had identified two clusters of taluks in
economically backward region of Davanagere. Within the flrst cluster, Harapanahalli
and Jagalur taluks were close with regard to the seven variables considered, as
indicated by the similarity index of 85 per cent. Next, Channagiri, Harapanahalli,
Jagalur and Harihara Taluks were closer with a similarity index of around 70 per cent.
In the second cluseter, Davanagere and Honnali were closer with a similarity index of
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235
around 60 per cent. The first and second clusters were distant, with the squared
euclidean distance of 9,441 [Table 7.32 (i) and (ii)]. Here, Channagiri, Harapanahalli,
Jagalur and Harihara Taluks belonged to the first cluster, while Davanagere Taluk and
Honnali Taluk belonged to the second cluster. Considering the seven variables with
which the two clusters were identified, rural connectivity, drought proofing and
employment provided in person days were uniform between the two clusters, while
the remaining variables viz; (1) water conservation and water harvesting, (2)
renovation of traditional water bodies, (3) number of BPL households and (4) the
number of IAY beneficiareis were distinct between the two clusters. Thus, in order to
achieve inclusive growth, in Davanagere district, it is crucial to focus on these four
variables. In addition, this will bring closer the two clusters of Channagiri onto
Harihara with Davanagere and Honnali Taluks.
Table-7.32(i): Cluster Profiles in Davanagere District (Economically Backward
Region) for The Years 2008-09 to 2011-12
Sl.
No. Variable Cluster1 Cluster2
Grand
centroid
1 Rural Connectivity in kms 44.97 49 46.3
2 Water Conservation and Water Harvesting in Cubic
meters 2.87 11.9 5.9
3 Drought Proofing in Hectares 0.47 0.4 0.4
4 Renovation of traditional water bodies in Cubic meters 27.98 0.4 18.8
5 Number of households whose status has been selected as
BPL 8468.75 23427 13454.8
6 Number of IAY Beneficiaries 214.25 61 163.2
7 MGNREGS employment Provided in Person days 2303.5 2653.5 2420.2
Table -7.32( ii) : Similarity Index and Squared Euclidean Distance in
Davanagere District
Step No. of
clusters
Similarity
level
Distance
level Clusters joined
New
cluster
No. of
observations in
new cluster
1 5 84.3853 3256.8 3 6 3 2
2 4 78.2873 4528.65 3 4 3 3
3 3 72.4544 5745.23 1 3 1 4
4 2 64.0508 7498 2 5 2 2
5 1 54.7333 9441.36 1 2 1 6
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Graph-7.M:Cluster Formation in Davanagere District (Economically Backward Region)
HONNALI
DAVANAGERE
HARIHARA
JAGALUR
HARAPPANAHALLI
CHANNAGIRI
54.73
69.82
84.91
100.00
TALUKS
Similarity
Davanagere
7.13: Economic Analysis of MGNREGA in the Drought Prone States of
Karnataka and Rajasthan
Karnataka and Rajasthan are the two most drought prone states of India.
Karnataka has the second highest drought prone area next to Rajasthan with arid and
semi arid climatic conditions. Effect of MGNREGA on farmers in drought prone
areas is different from that in irrigated areas due to differential employment and wage
rates.
Paradoxically, even with high rates of unemployment, farmers are
experiencing economic scarcity of labor for all operations as the market wage rates
are way above the farm wages, affecting the supply of farm labor. The effect of
economic scarcity of labor is increasingly being felt relatively in drought prone states
than in irrigation dominated areas. Using macro level data from the unemployment
insurance program of the Government of India provided by MGNREGA for the two
drought prone states of Karnataka and Rajasthan and irrigation dominated state of
Andhra Pradesh, this section analyzes the reasons for such an economic paradox and
provides implications for policy considering provision of (a) employment to needy
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237
rural families; (b) gender neutral minimum wage and (c) supplementary income to
laborers without adversely affecting labour supply to agriculture.
The hypotheses of this exercise were: (a) MGNREGS has been successful in
providing 100 days of employment per annum to rural families demanding
employment (b) MGNREGS implementation is relatively efficient in Karnataka than
in Rajasthan, providing opportunities to weaker sections of the community in
employment generated; and (c) MGNREGS causes economic scarcity of labor in
agriculture
7.13(i): Employment Generation Potential outside MGNREGS
Around 50 per cent of the households who had registered under MGNREGS
actually demanded employment. Such a modest proportion availing MGNREGA
employment was due to favorable labor market outside MGNREGS and outside
agriculture. Rural families registered for MGNREGA employment for ‘job card’ with
the perception that such a registration may provide benefits in future treating job card
akin to ‘ration card’. Of the total number of households demanding employment, 92
to 97 per cent were provided employment in the drought prone states, while for
Andhra Pradesh it was 107 per cent. Thus, in Andhra Pradesh, MGNEREGS was
being offered even for those households who had not demanded MGNREGS
employment. Karnataka had to strive to accommodate all the households demanding
employment. Despite the Central Government earmarking Rs. 40,100 crores in its
2010-11 annual budget for MGNREGA1 and a high unemployment rate of 8.3 per
cent2, only 6 per cent of the total households demanding employment completed 100
days of work, in both the drought prone states. In Andhra Pradesh, job provision for
100 days or beyond was marginally higher at 12 per cent. Number of person days of
employment provided per household was around 50 days, half of the guaranteed
number of days of employment, in all the three states. Since more than 90 per cent of
the households demanding employment were accommodated, a low percentage of
households completing 100 days of work indicate that rural households were getting
gainful employment outside MGNREGS. Thus, provision of 100 days of employment
1 http://indiabudget.nic.in, 10/08/2011 2 http://planningcommission.nic.in 10/08/2011
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238
per household per annum’ need not be treated as a compelling target to be achieved,
since MGNREGS is essentially demand driven (Table 7.33).
Table -7.33: Employment Sought and Offered by MGNREGS in Sample
Drought Prone and Irrigated States of India, 2010-11
Sl.
No. Particulars Karnataka Rajasthan
Andhra
Pradesh
1 Households Registered under MGNREGS
for employment (millions) 5.3 9.9 11.7
2 Proportion of Households seeking (or
demanding) MGNREGS employment 45.6 54.7 47.7
3 Proportion of Households offered
employment under MGNREGS 92.2 97.3 107.0
4 Employment provided in No. of person
days per household 49 47 49
5 Proportion of Households availing 100
days of MGNREGS work 5.9 5.6 12.5
Source: http://nrega.nic.in/MISreport.htm (26/27-07-2011 & 02-08-2011)
7.13(ii): BPL Families and MGNREGS
A comparison of proportion of households under BPL in the State, with the
proportion of BPL families availing MGNREGS employment indicated that, the two
drought prone states of Karnataka and Rajasthan had respectively 17.4 and 13.7 per
cent of the families as BPL. However, in Karnataka 21.2 per cent of total families
registered in MGNREGS belonged to BPL category. Thus, Karnataka state had
benefitted BPL more than any other state. In Rajasthan, which is more drought prone
than Karnataka, only 6.5 per cent of the families registered under MGNREGS
belonged to BPL category. In Andhra Pradesh, being a better endowed irrigated state,
virtually no BPL family registered and/or availed the MGNREGA benefit, due to
prevalence of higher wages in agriculture and non agriculture sectors. It is in order to
note that MGNREGA does not discriminate between BPL and APL families and
hence the program can be availed by any rural person3. (Table7.34).
3 (http://planningcommission.nic.in/plans/stateplan/sdr_orissa/sdr_orich8.pdf)
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239
Table -7.34: BPL Families Employed Under MGNREGS in 2010-11
Sl.
No. Particulars
Karnatak
a
Rajastha
n
Andhra
Pradesh
1 No. of BPL Families Registered in
MGNREGS (in millions) 1.1 0.7 0.0
2 Proportion of BPL Families registered
out of the total families registered in
MGNREGS
21.2 6.5 0.0
3 Proportion of BPL families in the State 17.4 13.7 11.1
Source:http://nrega.nic.in/MISreport.htm (26/27-07-2011)
7.13(iii): Age Cohort in MGNREGS
The age cohort analysis of those registered in MGNREGS indicated that about
60 per cent of the persons employed under MGNREGS were below 40 years of age
and a modest 4 to 6 per cent of the workers were above the age of 60 years. This is a
pointer to the fact that MGNREGS employed able bodied persons more than the aged
persons (Table 7.35).
Table-7.35: Age-wise Details of Employed Persons Under MGNREGS in 2010-11
Source: http://nrega.nic.in/MISreport.htm (26/27-07-2011)
7.13(iv): Season-wise Employment in MGNREGS
About one-third of the annual demand for MGNREGS work was during Kharif
in Andhra Pradesh and Rajasthan. In Karnataka and AP, around 60 per cent of the
demand for MGNREGS work was during summer months, while in Rajasthan around
50 per cent of the demand was during summer. Especially in Karnataka, annual
demand for MGNREGS during Kharif, the peak agricultural season of the state, was
only 9 per cent, followed by 29 per cent during Rabi season and a maximum of 62 per
cent during summer season which is a gainful employment during the off season.
(percentage)
Sl.
No. Age Group Karnataka Rajasthan Andhra Pradesh
1 Below 40 years 61.2 61.9 60.6
2 40-60 years 35.6 32.3 35.7
3 Above 60 years 3.2 5.8 3.7
4 Total 100.0 100.0 100.0
5 Total No. of employed persons
(in million)
6.1
7.3
11.2
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240
Thus, this macro level data on MGNREGS season-wise employment does not support
the hypothesis that MGNREGA weans away labour force from agriculture activities
and creates labour shortage (Table 7.36).
Table-7.36: Season-wise Work Demand Pattern Under MGNREGS in 2010-2011
Sl.
No. Season
Proportion of Persons Employed in
MGNREGS as Per cent of Annual Demand
Karnataka Rajasthan Andhra
Pradesh
1 Kharif (June - September) 9.1 37.6 34.5
2 Rabi (October - January) 28.8 14.1 0.0
3 Summer (February - May) 62.1 48.3 65.5
Total 100.0 100.0 100.0
4 Total annual demand for
Employment (in million
persons) 11.1
20.0 20.8 Source: http://nrega.nic.in/MISreport.htm(26/27072011)
7.13(v):: Duration-wise Employment in MGNREGS
Majority of the households in Karnataka and Rajasthan (66 per cent each) and
Andhra Pradesh (70 per cent) were provided less than 60 days of employment by the
MGNREGS (Table 7.37). Only 6 per cent of the households both in Karnataka and
Rajasthan and 12 per cent of the households in Andhra Pradesh completed 100 days
of employment. As around 95 per cent of the households demanding MGNREGS
work were provided employment (Table 7.33) and more than half of the annual
demand for work was during summer in all the three states (Table 7.36), MGNREGS
offered supplementary employment during the off season and obviously did not
compete with the labor demand for local agricultural operations .
Table -7.37: Duration Wise Employment Provided Under MGNREGS in 2010-2011
Sl.
No.
No. of days of work attended to
by families per year
Proportion of Households attending
to work (per cent)
Karnataka Rajasthan Andhra
Pradesh
1 01 to 30 days 36.8 33.5 43.6
2 31 to 60 days 29.5 32.6 26.6
3 61 to 99 days 27.8 28.2 17.3
4 100 & more no. of days 5.9 5.7 12.5
5 Total No. of days 100.0 100.0 100.0
6 Total No. of Households attending MGNREGS work 2.2 5.2 6.0
Source: http://nrega.nic.in/MISreport.htm (26/27-07-2011)
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241
7.13(vi): Economic Scarcity of Labour and MGNREGS
A majority of the rural households possess BPL cards. The value of food grains,
on an average, received by a BPL family (Channaveer, 2011), was Rs.3,114 per
annum. For BPL families due to populist policies of the ruling Government, rice and
wheat are supplied at Rs. 1 to Rs. 3 per kg and with a provision of around 20 Kgs of
food grains per month, many wo/men, tend to be complacent since, their food
requirements of the entire month is met with one or two days wage income. In
addition, in rural areas, higher wages offered in non agriculture sector, led to the
backward bending supply of labor (Fig. 7.(iii)) at two levels. In the first level, the
backward bending supply was due to provision of subsidized food grains for BPL
families. This provision of food is independent of inflation and provides the barest
minimum food, offering food security to the rural family. In the second level, the
backward bending supply of labor operated and around 60 person days of labor in the
family were seldom interested to offer their labor. This is the reason also that in
MGNREGS, only 6 to 12 per cent of the households offered 100 days of their labour,
while 65 to 70 per cent of the households offered around 60 days of their labor per
year. A person who offers 60 days of labor, if s/he stops working beyond this
threshold, there are no compelling reasons to disbelieve that the person follows the
backward bending supply of labor. Another argument is that the village panchayaths
were not attracting MGNREGS employables. However, if the village panchayath had
provided opportunities per family with 60 days of work, then the village panchayath
was also capable of providing opportunities per family with 100 days of work.
If rural area people were food secure, their first and foremost need was met
and had every reason to avail leisure. With increasing farm mechanization and
availability of custom hire services, agriculture had become now more mechanized
than earlier and hence food production had been sustained at the national level.
Figure-7.(iii): Backward Bending Supply of Labour
Wage Rate
Labour Days Offered for Employment
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242
7.13(vii): Reservation Wage Argument
The reservation wage counts the most in attracting the rural labor for work.
Reservation wage is the threshold wage which makes a person to offer his/her labor.
Suppose that the MGNREGA wage rate is Rs.100 per person per day. The reason why
rural people are not offering their labor is the level of their reservation wage (RW).
Taking the case of Karnataka, the first level is RW1 where Rs. 150 is offered in rural
areas and a few would turn up. The rate of increase in farm wage is also modest. The
second level is RW2, where Rs. 300 is offered as nonfarm wage and rural people get
attracted to the higher reservation wage. The rate of increase in nonfarm wage is also
substantial compared with farm wage. Thus, the reason for sub-optimal utilization of
MGNREGS is the provision of food articles in the public distribution system which
renders food availability and security every month with one or two person days of
labor. One of the reasons for suboptimal supply of labor for farm operations is the
provision of relatively drudgery free labor and wage in MGNREGS. The reason for
seasonal migration and increase of labor employment in urban and peri urban areas is
due to the substantially higher reservation wage of 200 per cent in nonfarm wage over
MGNREGA wage and 100 per cent increase in nonfarm wage over farm wage. The
hike in nonfarm wage has attracted substantial youth from rural areas towards civil
works in peri urban and urban areas which pays these workers for a longer time
horizon (Figure 7.iv). Thus, there is economic scarcity of labor as the reservation
wages as well as the rate of increase in wage with increase in employment increase at
different exponential rates.
Figure-7.(iv): Hike in Non-farm Wage Level in Rural Areas
RW2 = Rs. 300
Farm wage rate
MGNREGA
wage rate
RW1 = Rs. 150
Rs.100
ega.nc.n/
MISrepo
rt.htm
(26/27-
07-2011)
http://w
ww.goo
gle.co.in
/search?
Nonfarm wage rate
Labour Days Offered for Employment
Wage rate
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243
7.13(viii): Conclusions and Implications
Using the macro level data on MGNREGS and the economic scarcity of labor
arguments, this exercise amply proves that MGNREGS is complementing the rural
wage incomes of the needy at no cost to agriculture and other sectors in rural areas.
The economic scarcity of labor in agriculture is largely due to the higher rate of wage
hike in nonfarm wages offered especially by the mining and construction sectors in
Karnataka and similar sectors in other States. The wage differential between rainfed
and irrigated agriculture is relatively smaller compared with the wage differential
between farm and nonfarm wages. Hence even in irrigation dominated state of
Andhra Pradesh, the economic scarcity of labor is not due to MGNREGA wages, but
due to hike in nonfarm wages. The provision of food security through public
distribution system as a populist measure reinforces the backward bending supply of
labor already manifested due to the hike in nonfarm wages.
The rural areas are almost becoming ‘old age homes’ due to hike in nonfarm
wages attracting rural people for employment. Parallelly agriculture needs to be
supported by subsidies for farm machinery in order to assist farmers who are facing
the economic scarcity of labor. These policies are crucial for sustaining the food
security as well as livelihood security of agriculture sector in the drought prone states
as well as in irrigation dominated state.
7.14: Impact of MGNREGA on Individual Farmers and the Farm Economy:
A Few Case Studies
MGNREGS activities can be taken up as community works or on individual
farms belonging to SC / ST farmers, where labour component of the expenditure
would be borne by village panchayath under the programme. Impact of such
activities is presented below as case studies. The first two case studies represent the
works executed on individual farms and the subsequent two represent community
works. The results reiterate that natural resource conservation received priority in
selection and execution of MGNREGP activities both in Economically Forward and
Economically Backward regions of the state.
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244
Case Study 1:
Type of work executed: Construction of farm pond, Land development and
Horticulture gardening in individual farm
Investment under MGNREGS: Rs. 1.5 Lakhs
Name of the Farmer: Sri Srinivas S/O Sri H.V. Thimmaiah
Farm Area: 30 Acres
Village: Hariyabbe in Hiriyur Taluk of Chitradurga District
Sri Srinivas, a young farmer from Hariyabbe owns a farm of 30 acres area.
Prior to MGNREGS assistance ground nut was the only crop he was cultivating on his
farm in about 20 acres area, with an average yield of 2 quintals per acre depending
upon the rainfall received. He could raise only one crop a year as his farm was purely
rainfed. Covered with shrubby jungle the remaining 10 acres of land holding had to be
left fallow. Perpetual low productivity-low production-low income-low investment
and resultant low productivity – had driven Mr. Srinivas into frustration. He was on
the verge of quitting agriculture and seeking livelihood elsewhere.
Under the individual beneficiary category of the programme Sri Srinvas
sought MGNREGS intervention for land development. The Village Panchayath
through Gram Sabha and Taluka as well as Zilla Panchayaths acceded to his request
and sanctioned Rs. 1.5 lakhs for the proposed activities on his farm. The jungle was
cleared, a farm pond was constructed and a bore well was drilled which yielded 3
inches of water (3500 gallons/hour). Establishment of Pomegranate garden in 5 acres
area was initiated and laying of drip irrigation unit was taken up in the first year. A
plan to plant Cocunut seedlings in an area of 3 acres and sweet lime seedlings in 10
acres area was executed in the second year. All the expenditure exceeding Rs. 1.5
lakhs sanctioned under MGNREGS was met by the farmer. Apart from planting
perennial crops, Sri Srinivas changed the cropping pattern from mono crop of rainfed
groundnut to sunflower in 3 acres, onion in 2 acres, ragi in 1.5 acres, and irrigated
groundnut in 1.5 acres. This enabled the farmer to achieve increased productivity of
his farm as shown in the Table 7.38.
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245
Table -7.38: Cropping Pattern and Yield Details of Sri Srinivas’ Farm
Before and After MGNREGS Intervention
Sl.
No. Crops
Before MGNREGS After MGNREGS
Acreage Yield in
Qtls. Acreage
Yield in
Qtls.
1 Groundnut (rainfed) 20 2
2 Groundnut (irrigated) - - 1.5 8
3 Ragi (irrigated) - - 1.5 16
4 Onion - - 2.0 20
5 Sunflower - - 3.0 5
6 Pomegranate - - 5.0 Newly
planted
7 Sweet lime - - 10.0 Newly
planted
8 Coconut - - 3.0 Newly
planted
9 Fallow 10.0 - 4.0* - *4 acres of land is interspersed with rocks and tree stumps. To clear it JCB machines have to be used.
Figures presented in the above table show that more land was brought under
cultivation, with assured irrigation better remunerative crops could be introduced. It can
inferred from the table that, on the positive side MGNREGS helped the farmer in better
utilization of the resources and increasing productivity as well as profitability of the
farm. The farmer was enthused to continue farming.
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246
Photograph-7.1(a): Sri Srinivas’ Farm in Hariyabbe Village with
MGNREGS Intervention
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247
Case study 2:
Type of work executed: Bunding and construction of Check dam
Investment under MGNREGS: Rs. 55 thousands
Name of the Farmer: Sri Patresha Gowda
Farm Area: 25 Acres
Village: Mediginkere, Guttidurga Gram Panchayath, Jagalur Taluk, Davanagere
District
The farm of Sri Patresha Gowda had plots which were degraded and had
been left fallow. With MGNREGS intervention a checkdam and bunds were
constructed. The farmer has incurred an expenditure of Rs. 55,000 towards raising the
nursery. Mainly runoff water was impounded and ground water recharge was
improved. As perceived by the farmer borewell yield increased from 1000 gallons per
hour to 2000 gallons per hour. More area was brought under protective irrigation (10
acres to 20 acres) which improved maize productivity by about 5 quintals per acre and
coconut plantation also started yielding 100 more nuts per tree (Table 7.34). The
additional returns farmer realized far exceeded the annual amortized cost of capital
investment on check dam and bunds construction (Rs. 14,540 at the rate of 2 per cent
opportunity cost).
Another additional benefit Sri Pathresh Gowda derived was that, after the
construction of check dam and bunds, he raised a nursery of Jatropha seedlings in
poly bags in five acres area. It generated 750 man days of employment per year. He
would realize higher returns by selling nursery seedlings in the subsequent years.
Looking in to the results of these two case studies, it can be said that
MGNREGS activity on individual farms proved to be a win-win situation for all the
stakeholders, as it addresses the issues of labour scarcity for the farmers, livelihood
security for the workers and efficient functioning of the programme for the
implementers.
.
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248
Table-7.39: Improvement in Crop Yield, Returns and Gains due to
MGNREGS Intervention in Sri Patresha Gowda’s Farm
Crops
Total
groundwater
irrigated
area before
MGNREGS
(Acres)
Total
groundwater
irrigated
area after
MGNREGS
(Acres)
Additional
area under
irrigation
(Acres)
Additional
yield
Additional gain
due to
MGNREGS
Maize 10 20 10
5 quintals
per acre 3000 per acre
Coconut 5 5 -
100 nuts per
tree 22500
Photograph-7.1 (b): Sri Pathresha Gowda’s Farm in Mediginkere Village
with MGNREGS Intervention
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249
Case Study 3:
Type of work executed: Desilting of Haluru tank and repair of its feeder channels
Investment under MGNREGS: Rs. 6.5 Lakhs
Village: : Kodakani village, Soraba Taluk, Shivamogga District
Increase in area under cultivation: 100 acres
Increase in paddy yield: 2 quintals per acre
Bore wells recharged: 42
Soraba Taluk in Shivamogga district in STZ is geographically flattest area in
Asia and boasts of about 1,600 tanks. But, it is unfortunate that due to negligence on
the part of all stakeholders, those tanks had been subject to heavy siltation and
resultant reduction in their live storage capacity. Feeder channels of most of the tanks
had been clogged and hence water inflow in to the tanks had gradually reduced.
Naturally the tank command area, cropping intensity, productivity and employment
opportunities all had been adversely affected. It was a paradox that the surrounding
areas of such tanks were flooded during heavy downpour causing considerable
damage. The agricultural workers migrated to coffee growing areas in the neighboring
districts in search of employment. Thus both the farmers and the workers underwent
misery.
Haluru tank had seen good days with a command area of over 300 acres. But of
late heavy siltation had reduced its water holding capacity and the tank could not
support more than one crop per annum. Under MGNREGS a budget of Rs.6.5 lakhs
was allocated to rejuvenate the tank by desilting the tank and repairing its feeder
channels.
This community work became highly successful because of the active support
and participation by farmers as well as landless labourers. Rejuvenation of tank taken
up as a village mass movement resulted in second crop of paddy being cultivated in
100 acres, increase in paddy productivity by 2 quintals per acre due to availability of
irrigation during all the critical stages of crop growth and recharging of 42 bore wells
in the tank command area. Women folk who often face the severity of water shortage
outnumbered the male workers by 2.5 times in execution of the work. This also
contributed in the right direction to women empowerment.
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250
Photograph -7.1(c).:MGNREGS Activity of Haluru Tank Rejuvenation in Kodakini Village
Case Study 4:
Type of work executed: Disiltation of tank and strengthening of tank bund
Investment under MGNREGS: Rs.10.3 lakhs
Village: : Nagenahalli in Merkuli Gram Panchayat, Hassan District
Employment generated through the work: 7012 person days
Increase in area under irrigation: 80 acres
Increase in returns from paddy: Rs. 20 lakhs in one year
Bore wells recharged: 5
A village tank in Nagenahalli, which had a live storage area of 23 acres
earlier, was heavily silted and had a dilapidated tank bund. Only one paddy crop a
year could be cultivated with the water available from the tank.
Gram Sabha of Nagenahalli decided to rejuvenate that tank under
MGNREGS with a budget allocation of Rs. 10.3 lakhs and the work was completed in
about 11 months period by generating 7012 person days of employment. The activity
made it possible to cultivate second crop of paddy in 80 acres benefiting 146
households in the village and generating an additional income of Rs. 20 lakhs per
annum. The community work undertaken not only recharged 5 bore wells, but also
ensured drinking water for animals in all the three seasons. These benefits accrued to
Nagenahalli economy are presented in Table 7.40.
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251
Table-7.40: Benefits Accrued to Nagenahalli Economy through MGNREGS Activity
Sl.
No. Particulars of benefits accrued
Before
MGNREGS
work
After
MGNREGS
work
1 Area irrigated by the tank (Acres) 80 160 (in two seasons)
2 Cropping intensity (per cent) 100 200
3 Paddy production in a year in the tank command area
(quintals)
2000 4000
4 Additional returns (in lakh Rupees) - 20
5 Number of families benefited by additional irrigation
water availability
- 146
6 Employment generated by MGNREGS activity
(Person days)
- 7102
7 Number of bore wells recharged - 5
8 Water availability for animals - In all the seasons
Photograph-7.1(d):MGNREGS Activity of Village Tank Rejuvenation in Nagenahalli
Thus, community works taken up under MGNREGS in these two villages
accrued benefits to the community both in terms of improved natural resource
management and enhanced returns. Properly planned, efficiently executed,
transparently monitored MGNRGS activities have the potential to add to the welfare
of rural communities.
Results presented in Tables 7.19, 7.20, 7.38, 7.39, 7.40 and case study 3
prove our sixth hypothesis that MGNRES has improved natural resource base in rural
areas and has increased cropping intensity and crop productivity.
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252
7.15: Constraints Identified in Implementation of MGNREGS:
A. Constraints from Workers’ Perspective
Wage rate under MGNREGS (Rs.82 per day per person) was lower than the
market wage rate (Rs. 100 to 150 per day per person). This wage differential
was the main reason for low demand for employment provided under
MGNREGS in both the Economically Forward Districts of Hassan and
Shivamogga and in Davanagere district, an Economically Backward District.
Workers migrating to coffee estates in Sakaleshpura region received higher
wages with fringe benefits as well as advance payment. This prompted the
workers to demand advance payment under MGNREGS in Hassan and
Davanagere districts.
In many villages, as in the case of Shivamogga district, male workers
preferred contract work to wage payment based on number of days of work.
This system enabled the workers to earn more in lesser time period through
higher efficiency and better marginal labour productivity. However, the
primary objective MGNREGA is to provide supplementary employment to
rural workers and not to serve as their main source of employment and
income.
Delay in wage Payment to the workers under MGNREGS from 20 days to
three months (20 days after the completion of work in Arasikere Taluk to
more than 3 months in Hiriyur taluk) forced the workers to shy away from
MGNREGS work in the subsequent years (Hassan and Chitradurga districts).
Some workers reported engagement of contractors, use of machinery for the
execution of works and related irregularities in payment of wages in
Chitradurga district.
It was observed in all the districts that the sense of belongingness was weak
among the workers while undertaking community works which affected the
quality of work.
Workers were in need of and demanded daily payment of wages (Shivamogga
and Chitradurga districts).
Contrary to the spirit of MGNREGA in some instances in the Economically
Backward Districts of Davanagere and Chitradurga, the Gram Panchayath
officials considered the request for employment not when the workers were in
need of work, but when the Officials were under pressure to achieve the
targets. The workers were not making the requests in writing which would
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have forced the officials to either provide employment in 15 days from the
date of application or pay them unemployment allowance. It was felt that there
is a need to create awareness on the part of workers as well as Gram
Panchayath officials regarding the aims, objectives, duties and responsibilities
under MGNREGS.
Demand for MGNREGS works during the hot summer months was low as it
involved physically exerting and tiresome manual digging works. The
Panchayath officials also found it difficult to maintain specific quantum of
work prescribed under MGNREGA to be eligible for one day wage, especially
during summer months, as many of the persons who offered to work under the
programme were women and aged (Hassan and Davanagere districts).
Ignorance among the workers regarding provisions and procedures of the Act,
has led to deprivation and exploitation, such as (a) lack of worksite facilities
like first-aid box and shade in some places of work, (b) employment and wage
details not properly entered in the Job cards, (c) job cards in the custody of
Panchayath officials in many villages, instead of in possession of workers, (d)
delay up to 3 months in payment of wages in some taluks and (e) nonpayment
of unemployment allowance in any of the districts despite the delays in
providing jobs beyond 15 days after seeking employment (Hassan,
Shivamogga and Chitradurga districts).
Neighbours and friends ridiculed men workers for working under MGNREGA
for a wage rate which is equivalent to that of women workers (Bhadravati
taluk of Shivamogga district).
Higher wage rates offered and regular demand for labour in areas with good
irrigation facilities and plantation crops deterred workers from seeking
employment under MGNREGAS (Hassan and Shivamogga districts).
The workers were not yet issued Bank/Post Office pass books in a couple of
villages (of Arasikere Taluk, Hassan district).
These constraints were not specific to implementation of poverty alleviation
programmes in Karnataka state alone, since similar survey results were reported by
many researchers in different parts of the country. Delay in wage payment, ranging
from a few days to more than 3 months, was reported in Kerala, Jharkhand, Odisha,
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Maharashtra states, use of contractors and machineries was observed in Jharkhand,
Kerala, Maharashtra, Chhattisgarh states, poor maintenance of records was revealed
in Jharkhand, Odisha, Andhra Pradesh, Uttar Pradesh states and inadequate worksite
facilities was found in Jharkhand, Rajasthan and Tamil Nadu states. These anomalies
have been defeating the basic purpose of launching such an ambitious programme.
B. Constraints from Administrators’ Perspective
Efficient execution of MGNREGS works needs a clear understanding of all
the procedures and provisions of MGNREGA. The Gram Panchayath
secretaries needed to be educated in this regard to make their discharging of
duty more effective and bring in accountability both in letter and spirit. As felt
by some of the secretaries, they were handling funds of various schemes and
projects, beyond their capacity.
The main reason for the delay in wage payment to workers, as expressed by
the Panchayath personnel, was the delay in writing the MB book by the
concerned Engineers from taluk offices (Hassan and Chitradurga districts).
Both first and second constraints could be addressed by having separate
administrative machinery for implementation of MGNREGS.
Zilla Panchayath had been taking more than 3 months to release funds for
MGNREGS (Chitradurga district).
Placing all the computers meant for Gram Panchayaths in Taluk Offices due to
frequent failure of electricity supply as well as poor internet access, had added
to the burden of Panchayath personnel who had to travel frequently to Taluk
Office to make MGNREGS related entries in the computers. As a result MIS
was not accessible to Gram Panchayaths in most of the taluks (Chitradurga
district)
With regards to job cards issued to workers without participants’ photos and
incomplete entries in job cards, the Gram Panchayath Secretaries complained
of insufficient budget allocation for taking photographs and affixing in job
cards of workers (Hassan, Chitradurga and Davanagere districts).
The MGNREGS works lacked convergence with works of other
developmental departments and suffered from inadequate technical support
from concerned departments. For instance, a visit to the worksite of check dam
construction in Srinivasapura in Mavinakere Grama Panchayath in Bhadravati
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Taluk, Shivamogga District revealed this fact. In this village the check dam
was constructed near a bridge and the space between the check dam and the
bridge was too narrow for free flow of water during heavy rains. Hence both
the structures were prone to damage by heavy overflow of water from the
check dam. The Gram Panchayath personnel bemoaned that lack of technical
support and cooperation from watershed experts led to poor planning and
execution of the check dam work.
Shortage of Staff to maintain MGNREGS records, as expressed by panchayath
secretaries (All districts).
MGNREGS is essentially a demand driven programme. But, failure to
understand and appreciate this aspect on the part of all stakeholders led to, in
some cases, middlemen acting as contractors, bringing the list of workers to
gram panchayaths demanding employment for executing their work.
The researchers came across a few instances of use of mechanical devices like
JCB and tractor in executing MGNREGS works (Chitradurga district).
The persons in Gram Panchayaths in charge of execution of MGNREGS
works have to make entries in NMR register, details of men and women
workers who have participated in the programme. But, the registers were
incomplete (Chitradurga district).
Because of poor maintenance the assets created under MGNREGS in the
previous years were in bad shape in many a Gram Panchayaths. For instance,
drainages constructed under MGNREGS in Ranganathapura of Hiriyur Taluk
(Chitradurga district) were filled either with weeds or stones.
Delays in check clearance by banks were causing delay in payment of wages
to MGNREGS workers. Supervisory staff was forced to cut down the wages of
workers because of the poor quality of works turned out under the programme.
But, the workers were demanding full wage payment. Such altercations were
creating tension between workers and the administrators in executing the work
(Davanagere district).
Assessment of works of those workers who got engaged in supplying water to
other workers and looking after small children accompanying their mothers
when large number of workers participate in MGNREGS works caused
problem (Davanagere district).
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The Gram Panchayaths had inadequate UPS and internet facilities and hence
MIS was not updated in time. This had added to delay in payment to workers
(Davanagere district).
The Panchayath officials complained that more than 20 ledgers had to be
maintained, each demanding multiple entries, which was time consuming (all
districts). This resulted in poor maintenance of MGNREGS records. It is
necessary to rationalize maintenance of accounts and avoid duplication of
entries.
Because of inadequate technical support, restriction on material cost and poor
quality of labor participating in MGNREGS, quality of assets created ranged
from average to poor (all districts).
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Photograph- 7.2 (a): Participation of Women Workers in Large Number in
MGNREGS in the Sample Districts
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Photograph- 7.2 (b): Creating Awareness about MGNREGA through Wall
Writing in the Sample Districts
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Photograph- 7.2 (c): Job Cards and Pass Books Issued to Participants of
MGNREGS in Sample Districts
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Photograph- 7.2 (d): Community Works taken up under MGNREGS for Natural
Resource Management in Sample Districts
Photograph- 7.2 (e): MGNREGS Works executed in Individual Farms
in Sample Districts
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Photograph- 7.2 (f): The Researcher Collecting Information from the
MGNREGS Workers in a Sample Village
Photograph- 7.2 (g): Modest Worksite Facilities Provided Under MGNREGS in
Sample Districts: 2008-09