a comparative study of livelihood strategies in rural and...

Mahua Bhattacharjee387–415 A Comparative Study of Livelihood Strategies in Rural and Urban Assam

A Comparative Study of LivelihoodStrategies in Rural and Urban Assam

MAHUA BHATTACHARJEE

Livelihood strategies of rural and urban Assam are becoming more interdependent.The rural–urban linkage is influencing livelihood in both positive and negative ways asmarket forces are increasingly determining all livelihood strategies. The study revealsthat the working population unanimously consider that livelihood is not as easy as itwas for the previous generation. Factors like unsuitable weather for cultivation, pricefluctuation, competition from better/cheap/substitute products, and the reluctantattitude of the younger generation towards rural livelihood activities are mainlyresponsible for making livelihoods harder. Products with a variety in different priceranges have brought significant changes primarily in rural livelihood activities.Sustainability of livelihood is now more dependent on practicing diversification as itcompels households to be more vigilant and adopt the change occurring over time.

Dr. Mahua Bhattacharjee is Senior Lecturer, Amity School of Economics, AmityUniversity.

INTRODUCTION

Households survive by drawing on its range of assets and engaging in a vari-

ety of activities. Livelihood strategies of households are multifaceted as men

and women draw on both their tangible and intangible assets for survival.

Livelihood strategies include how people combine their income-generating

activities, the choice of assets they choose to invest in, and how they manage

to preserve existing assets and income (Department for International Devel-

opment [DFID], 2000a, 2000b). Members of the household carry out a range

of activities to attain self-defined goals either by staying at one place or by

migrating temporarily or permanently to another place. With time, higher

pressure on limited livelihood capital is making livelihood strategies more

diverse. For the worsening land human ratios, falling agricultural commod-

ity prices in rural areas, and new economic opportunities and the expanding

IJSW, 71(3), 387–415, July 2010

Tata Instituteof

Social Sciences

THEINDIAN JOURNAL

OFSOCIAL WORK

Volume 71, Issue 3July 2010

manufacturing sector in the urban areas, livelihood strategies presently are

becoming more multi-locational.

On the basis of broad industry division made by the National Industrial

Classification (1998), agriculture is established as the uniquely dominating

principal status in rural Assam. However, in urban Assam, no such principal

dominating status could be determined. Though the highest concentration has

been noted in public administration, other areas like education and commer-

cial services, trade, hotel, restaurant and transport have also been found to be

equally significant. Women are found to be highly concentrated in agriculture

and are also found to be sharing the working status of trade, hotel and restau-

rant in rural areas. In urban areas, the concentration is more in public adminis-

tration, education and commercial services. The most dominant livelihood

strategy in rural Assam is self employment. More than half the number of

households in rural Assam are self employed in agriculture. As compared to

the national average, Assam has a significantly higher percentage of house-

holds who are self employed in agriculture. In the decade from 1993–1994 to

2006–2007, those self employed in agriculture increased by 10% in Assam,

along with a declining trend in agricultural labour, and other labour.

In urban Assam, the male–female working population ratio is almost

similar, but in rural Assam the female working ratio is marginally

higher. Based on the age category, it is seen that girls of 10–14 years

work more in urban Assam. As far as source of income is concerned,

wage/salary employment and non-agriculture enterprises are the two

important sources of income in both rural and urban areas. In urban

Assam, too, the percentage of those self employed is higher than that for

India. Based on the monthly per capita expenditure it is found that the

self employed and those engaged in casual labour are relatively poorer

(NSSO Reports on Household Consumer Expenditure and Employment

situation in India). Studies like Sengupta (2007), and Fan, Fang and

Zhang (2003) also revealed that casual labourers are the least protected

in urban areas, which has a significant effect on food security.

From the macro perspective of livelihood strategy, it is understood that

the percentage of agricultural labour and other labour has declined, with

self employment becoming a more preferred occupation.

METHODOLOGY

The study is designed mainly on the theoretical basis of DFID’s framework

on sustainable livelihood (Figure 1).

IJSW, 71(3), 387–415, July 2010

388 Mahua Bhattacharjee

FIGURE 1

Framework of Sustainable Livelihood

VULNERABILITY

Shocks

Natural: Flood

Man-made: Violence

against Women

LIVELIHOOD

CAPITAL

Physical

Human

Financial

LIVELIHOOD

STRATEGY

Natural,

Resource-based

Market-based

LIVELIHOOD

OUTCOME

Higher Income

Improved health and

nutrition

Gender equity

Reduced vulnerability

Good living

condition

With the limitation of considering all the variables of the model in a sin-

gle study, some adjustments were made according to the objective and pri-

orities of the current study. Vulnerability, livelihood capital and livelihood

strategies are the factors which interact to lead to a livelihood outcome.

The different elements of livelihood capital are:

• Physical: drinking water, dwelling unit, sanitation, and use of energy

for cooking and lighting.

• Human: health, nutrition and adequacy of food.

• Financial: assets and liabilities.

This article is entirely based on empirical data collected during 2006

from rural and urban Assam. A detailed account on the sex-wise range of

activities carried out in rural and urban areas was taken through individual

household survey. In addition, participatory method was also used to un-

derstand the coping and adaptive strategies for livelihood in the context of

vulnerability; dynamic nature of livelihood strategy; the inter linkage be-

tween the factors influencing livelihood; the micro element of society in-

fluencing livelihood; and the changes occurring in the time period. Gender

equity—being an important aspect of livelihood, women participation in

livelihood activities and changes occurring in their life—was specially

taken into account during the survey.

The household survey from selected occupations was done on the basis

of a structured questionnaire by a simple random sampling method. Occu-

pation-wise quantitative data was also collected from the households. Oc-

cupations in rural areas are categorically divided into four groups: (i)

agricultural labour, (ii) cultivator, (iii) self employed, and (iv) artisans. The

unorganised sector occupations in urban areas can be divided into three

groups: (i) self employed, (ii) regular worker, and (iii) casual labour.

IJSW, 71(3), 387–415, July 2010

A Comparative Study of Livelihood Strategies in Rural and Urban Assam 389

Qualitative information was collected though focus group discussions

(FGDs), key informant interviews, case studies, and direct observation.

The FGDs were carried out to elicit collective experience and take the

opinion of women, youth, and working group from the dominant occupa-

tion. Information from seven key informants (from seven villages) is also

included in the analysis. The FGDs and key informant interviews were

carried out in rural areas only.

The livelihood outcome is evaluated by Principal Component Analysis

Method (PCAM). Eighteen variables were chosen to reflect the specific

component affecting the livelihood of rural and urban areas. The theoreti-

cal foundation of the PCAM lies in expressing the components as linear

combinations of variables with the highest possible variation. If x, y and z

are three indicators to be examined as two principal components, then it

would require two linear equations to be estimated.

Component 1=�1x+�2y+�3z

Component 2=�1x+�2y+�3z

Here, coefficients of the equations either represent correlations or load-

ings of the indicator with the components which gives a particular dimen-

sion.

In order to improve the interpretation in terms of maximising the factor

load on to one component and for unique identification of factors of a com-

ponent, various rotations are normally applied both orthogonally and

obliquely. For the given set of data, orthogonal rotation varimax is applied.

In the next stage, factor scores were obtained by using the method sug-

gested by Anderson and Rubin (by SPSS programming) and the factor

score matrix is presented. Using the factor score matrix, the factor scores

for all the four components along with the total factor score for each of the

sampled villages and urban area is estimated. The mean scores were then

tested through independent t-test for rural (all villages) and urban (all

towns) areas at 5% level of significance.

Study Area

Two districts of Kamrup and Nagaon in Assam were selected for primary data

collection as they had the highest urban and rural populations, respectively, for

the state (Assam: Directorate of Economics and Statistics). Villages from

these districts were purposively selected on the basis of the dominant occupa-

tion—cultivator and agricultural labour-based on data of the Census of India

IJSW, 71(3), 387–415, July 2010


(2001). The cultivator-dominated Dhopguri and agriculture labour-dominated

Ganakpara (in Kamrup district) and cultivator-dominated Chakori Gaon and

agriculture labour-dominated Paschim Salpara (in Nagaon district), were se-

lected for the study. Another village, Kuch Gaon (in Nagaon district) was se-

lected on the basis of direct observation for having agricultural-based business

and as well as other businesses. In addition, two artisan-dominated villages in

Nagaon district—Bhakatgaon and Kalapani—were also selected. The main

sources of income for these villages were pottery and making bamboo fences.

These two villages had one major difference—in Bhakatgaon, the artisan

group is almost perishing, while in Kalapani the community is managing to

practice their art. Guwahati city (Kamrup district) was also selected to under-

stand urban living. Data on urban living conditions of Nagaon district were

collected from Haibargaon and Dhakaipatti.

Sample Design and Size

The total sample size was 400 with 240 from rural and 160 from urban

areas. Forty households were taken from each of the three villages domi-

nated by cultivators (Dhopguri and Chakori Gaon), agricultural labour

(Ganakpura and Paschim Salpara), and the self employed or agriculture

based or other businesses (Kuch Gaon). Among the 40 households, 20

households were from the dominant occupation and the remaining were

from other occupations. Twenty households were selected from each of the

artisan villages (Bhakatgaon and Kalapani). Therefore, the sample size of

the five villages in Nagaon district is 160 and the sample size of two vil-

lages in Kamrup district is 180.

The sample design for urban areas is also made on the basis of occupa-

tion. From Guwahati city, a total of 120 households were selected—with

40 households each of the self employed, casual labour and regular

workers. From Nagaon, 40 samples were collected from two towns

(Dhakaipatti and Haibargaon) of which 20 were self employed and the re-

maining were from other two categories.

Analysis

The four specific dimensions mentioned earlier—Vulnerability, Liveli-

hood Capital, Livelihood Strategy and Livelihood Outcome—are taken

into account on the basis of which the livelihoods in rural and urban areas

are compared. Each of these ‘dimensions’ are formed on the basis of some

relevant and related ‘components’. For fulfilling empirical requirements, it

IJSW, 71(3), 387–415, July 2010


is, therefore, necessary to transform the ‘constituent components’ of the

model into observable attributes either in the form of variables or indica-

tors. The following 18 indicators have been identified for the empirical

testing of the model as indicators of sustainable livelihood:

1. Percentage of households prone to flood

2. Percentage of households prone to flood with alternative options

3. Percentage of casual workers

4. Percentage of household reporting violence against women

5. Average size of homestead land

6. Literacy rate

7. Dropout ratio

8. Average annual health-related expenditure

9. Percentage of indebted households with institutional credit

10. Percentage of workers engaged in other than primary sector

11. Average annual household income

12. Percentage of households reporting no health problem during the

last year

13. Female literacy rate

14. Percentage of households with non-kutcha houses

15. Percentage of electrified houses

16. Percentage of households with access to safe drinking water

17. Percentage of household with sanitation

18. Work participation rate

These indicators are chosen to reflect the specific ‘components’ of the

model and values are obtained through the survey conducted following the

framework detailed in methodology among 400 households in seven vil-

lages and two urban centres of Nagaon and Kamrup districts of Assam

(values are given in Appendix 1). The correlation matrix of the selected

variables (presented along with significances in Appendix 2) suggests

certain important trends.

FINDINGS

It can be seen from Table 1 that casualisation tends to increase in the face of

floods, more within the primary sector, which in turn tends to reduce

IJSW, 71(3), 387–415, July 2010


income. Income is directly related to the amenities of decent living like

housing condition, electrification, sanitation and drinking water. Further,

expenditure on health acts as a significant income shock to households,

particularly among the flood-prone rural households. The size of the home-

stead is related to the creditability and decent living of the households,

while engagements in the non-primary sector lead to a higher income along

with improved standard of living and quality of life.

The results of the PCMA (see Appendix 3) shows that the four extracted

components altogether explain about 86% of the total variations and the

first two components account for more than half of the variations of the

model. The initial and rotated (by orthogonal varimax) component matrix

(see Appendices 5a and b) provides following the scheme of loadings on to

the components.

TABLE 1

Variables under the Different Components

Component 1:

Standard of Living

Component 2:

Livelihood Capital

Component 3:

Vulnerability

Component 4:

Livelihood Option

Drinking Water Homestead land Option during floods Work participation

rate

Electricity No health problem Violence against

women

Female literacy

Sanitation Literacy Dropout -

Health Expenses Credit Casualisation -

Working in a

non-primary sector

- - -

Housing - - -

Income - - -

Floods - - -

Based on this analysis, factor scores were obtained by using the method

suggested by Anderson and Rubin through SPSS programming (the factor

score matrix is presented in Appendix 5). One utility of the factor score is

that since it provides the coefficients of the linear equations of the variables

and component—revealing the relative importance of the variables to-

wards a particular component—it can be used to estimate the total factor

score of a case for a component. Using the factor score matrix, we have

IJSW, 71(3), 387–415, July 2010


estimated the factor scores for all four components, along with the total

factor score for each of the sampled villages and towns. The mean scores

were then tested through independent sample t-test for rural (all villages

taken together) and urban (all towns taken together). The concise results

are presented in Table 2.

TABLE 2

Mean Scores of Independent Sample t-test

Component Area N Mean Std. Dev SE (Mean)

Standard of Living* Rural 7 -0.37 0.77 0.29

Urban 2 1.31 0.21 0.15

Livelihood Capital* Rural 7 0.32 0.87 0.33

Urban 2 -1.13 0.37 0.26

Vulnerability Rural 7 0.03 1.09 0.41

Urban 2 -0.12 0.89 0.63

Livelihood Strategy Rural 7 -0.03 1.13 0.43

Urban 2 0.11 0.49 0.35

Total Score Rural 7 -0.01 0.57 0.22

Urban 2 0.04 0.20 0.14

Note: *Significant at 5% level

The results indicate that, as far as the sustainability of livelihood as a

whole is concerned, there is no statistically significant difference among

rural and urban households. However, in terms of two specific compo-

nents—standard of living and livelihood capital—urban households have

scored more over rural households. It is due to the visible rural-urban di-

vide in terms of housing conditions and basic amenities and services, as

well as in terms of factors like literacy and access to credit.

Qualitative data analysis indicates that cultivation is not a favourable

livelihood strategy in rural Assam, as it once was, mainly due to high ex-

penditure structure and unsuitable weather conditions in the last five years.

This, in turn, is limiting work options for agricultural labour. Therefore,

they mostly migrate to nearby towns or cities as migration is the easiest op-

tion available before them. The difference between the agricultural la-

bour-dominated villages of Ganakpura (Kamrup) and Paschim Salpara

(Nagaon) is that the labour from the former district mostly out migrate

IJSW, 71(3), 387–415, July 2010


permanently to the city or other states, while the labour from the latter dis-

trict migrate only temporarily to nearby places. This is because the villages

in Kamrup are better linked (by transport and middlemen) to the city and

other states, though the infrastructure condition of the villages themselves

are in a poor state. Families of the migrants stay back in the villages for the

sake of the children’s education as well as high living expenses in urban

areas.

In rural areas, a very insignificant percentage (3%) of households ex-

pressed satisfaction with the change. Rural households in Kamrup

(43.75%) and Nagaon (37%) districts believed that their condition had de-

graded or became worse in the last 10 years. Taking both the districts to-

gether, 41.66% of rural households expressed that changes were for the

worse. The remaining households considered there was no change in their

status. An equal percentage (37.5%) of agricultural labour from both dis-

tricts expressed that their condition had not changed or had became worse

(39%). Due to unfavourable weather conditions, the total area of land

under cultivated was shrinking, leading to restricted earnings and forcing

them to opt for the only other option available—to work as casual labour.

For this, they have to travel to other villages or towns and work as unskilled

labour at marginal wage rate.

In the cultivator-dominated villages of both the districts, unfavourable

climate and increasing cost of production were observed as the major rea-

son for the dissatisfaction. Limited rainfall had created drought-like situa-

tion in the villages in the two years prior to this study, bringing about an

unpredictable vulnerability in the livelihoods of cultivators and agricul-

ture-related households. Inadequate rainfall during the crop growing sea-

son is causing cultivators to only produce for subsistence. Droughts in

recent years have added to the uncertainty in addition to the floods in fields

of Assam. Unlike floods, droughts do not occur all of a sudden. From De-

cember 2002 to November 2003, rainfall was in a deficit by 466.9 mm

(Assam: Directorate of Agriculture, no date).

Dipen Kalita (42) of Ganakpara village could not reap the fruits of his labour.

An unprecedented drought-like situation damaged his 25 bigha of winter

paddy. Dipen and his family of five children are almost starving. Their rice

stock is almost of depleted. Though the river Sorsori flows close to the village,

there is no pumping station nearby to support the farmers. Without this

hundreds of farmers, including Dipen, are in a miserable state.

The change in the rainfall pattern is largely due to the current global cli-

mate change and increase in the global temperature levels. They are mainly

IJSW, 71(3), 387–415, July 2010


the outcome of the imbalance between humans and their environments. In-

creasing human activities, depletion of forest cover, and over exploitation

of natural resources are badly affecting the weather cycle all over the

world. Livelihoods in Assam are also, thus, found to be affected by the im-

balances. Instances of depleting forest base were observed in the study area

itself. In Paschim Salpara, people used forest reserves as a coping strategy

during floods and other natural calamities. Rise in the price of kero-

sene/diesel, wage level and other inputs without a supportive price and

procurement policy is dragging cultivation from commercial to subsis-

tence earning. Lapses in irrigation facilities, credit availability and poor ac-

cess to the market has come out clearly in the agricultural practice of

villages in the study area. The acidic nature and poor nutrient content of the

soil in Assam, and high humidity levels limits crop varieties there. Humid-

ity levels lower the selling price and increases the risk of pests and dis-

eases. In this situation, the outdated techniques used by the farmers cannot

make way for commercial cultivation and for an improved way of living.

Among the urban households, almost 50.63% expressed satisfaction

with ‘change’. It is observed that 70% of the regular workers and 77.5% of

casual labour have expressed high satisfaction with this change. Increase in

the cash flow for higher wage rate, as compared to rural wage rate, is the

major reason for their high satisfaction. On the other hand, casual labour of

the villages believe that their livelihood is in a static state. Due to decline in

cultivation, an increasing number of agricultural labour are found to be

shifting to casual labour, leading to an increase in the percentage of casual

labours in the villages. Limited work opportunities in rural areas and in-

crease in the number of casual labour are forcing many to out migrate.

Those who have permanently out migrated to cities are improving the liv-

ing condition by sending remittances to their family members in the vil-

lages.

Urban labour in the unorganised sectors are mostly migrants. Factors

like repeated crop failures, increasing expenditure structure and absence of

subsidiary earning opportunities in the villages are pushing the labour to

nearby urban centres for liquid money. Cash becomes so important for

them, that living conditions and absence of work security becomes second-

ary. What matters to them is that their remittance is giving food to their

family members and better living standards. On examining the living con-

dition, it is found that 11% of the construction workers are dwelling in the

work place itself without drinking water, sanitation and other facilities. In

IJSW, 71(3), 387–415, July 2010


the long run, this cannot be regarded as a sustainable way of living. About

52.5% of the self employed in urban areas considered they are living a

stagnant life due to increase in competition. About 13% of the self em-

ployed could not change their way of living due to illness as expenditure on

treatment was leading to huge loss of income which, in turn, is keeping

their livelihood in a static state.

Thus, we find that labour with comparably higher wage rates have found

temporary improvement, but without security and basic amenities. Such a

livelihood cannot lead to a sustainable livelihood. In a globalised world, they

are in a highly disadvantageous position as there is constant shift of technol-

ogy from labour to capital intensive and use of unskilled to skilled workers.

Thus, in the future they will need security for work, income and life so that

they can also contribute toward the success of globalisation.

In the commodity market, globalisation has influenced in increasing the

outlet with varieties and quality, which reduced the margin of profit and kept

the living condition of the self employed in the static state. Factors like low

profit margins, low self-esteem, and the need for high physical labour are re-

sponsible for keeping the younger generation away from the paddy fields.

Job expectations in the organised sector instigate the older generation to edu-

cate their children. With the limitation of absorption in the organised sector,

the additional young working group is pushed into the unorganised sector

who have to find work on self employment or remain as casual labour. Dur-

ing our previous discussion on livelihood strategies at the macro level, it has

been observed that a 10% increase in the self employed and a high decline in

the percentage of labour is evident in Assam. Casualisation obviously in-

creases vulnerability and makes livelihood unsustainable. The younger gen-

eration is getting into an unsustainable way of living, mainly because of the

poor development of the non-farm sector in rural areas and for not having

another option for livelihood. Remittances are not used for reinvestment and

a study by Lucas and Stark (1985) in Botswana has shown that it is not fa-

vourable for sustainability. The movement of the younger generation to

other places for jobs, increasing consumerism, and absence of reinvestment

in assets is ultimately making rural livelihoods unsustainable.

Saidul Huq, an 18-year old from Barpeta, has studied up to the Higher

Secondary level. He is a rickshaw-puller in Guwahati and stays with a friend

from his village. His parents earn Rupees 40,000 annually from growing

vegetables, while paddy cultivated on their land is sufficient for household

consumption. He has come to Guwahati to earn enough to buy a mobile phone.

Once he does that he will leave Guwahati, as he does not want to give up

cultivation.

IJSW, 71(3), 387–415, July 2010


About 62% of the self employed in rural areas are found to be dissatis-

fied with the changes as they are the victims of ever-increasing competi-

tion and changed climatic condition. For example, the area used to do good

business in betel nuts, but now this is not so as the buyers have found that

the quality of betel nut has declined due to climatic changes. Better quality

of betel nuts from other areas have entered the market and are taking over.

Those self-employed on the basis of livestock lack definite skills and

knowledge, which leads them to incur heavy losses.

Akbar Hussain owner of Sikni factory (a factory in which betel nut is dried,

coloured and mixed with tobacco powder and other chemicals) is not making

the high profits he used to earn in the initial period. The profit margin of his

factory and other co-factory owners have declined as the number of factories

have increased and the quality of the betel nut has declined due to insufficient

rainfall. In addition, good quality products are entering from Indonesia,

Thailand and other places.

Umakanta Kalita, a teacher, also shared similar fate in a cultivator-dominated

village. He said that the business of making and selling mithoi (a kind of ball

shaped sweet made from rice flour, pepper and jaggery made from sugarcane)

was a good source of income, but he could not sustain it for long as the colour

of this sweet was dark in colour and unappealing. The same product coming

from Lanka, Khirani, and Barkula was not dark and, thus, had taken over the

market.

In weaving, too, women are facing a similar situation. Getanjali Bora, an

experienced weaver of Ganakpara, stated that at ‘One time we could not meet

the demand of the Mahajan. But now, they do not like us with cloth in hand.

They do not want to buy, but we give them the weave forcibly’. She adds that

‘in the present days, polyester has taken the market and thus people do not

prefer the eri (a kind of silk), which used to be in high demand at one point in

time’.

All the artisans feel that change has pushed them into a worse condition.

They do not have anything in life now, except poverty. Child labour and

sickness is common for them, and strong social taboos in the artisan vil-

lages has led them to poverty, pulling their children into the same trap.

On the basis of analysis on perception of ‘change’, Table 3 sums up the

problems and options of rural livelihood. It is evident from Table 3 that mi-

gration is a common option for the people in rural areas. The rural–urban

linkage, thus, plays an important role in the livelihood in rural areas. The

migrants mostly start as casual labourers and then get into regular work.

Very few of them start something of their own due to the limited capital

available. Selling assets as an option and, as shown in the table is highly

detrimental for livelihood as assets are also not only a source of earning,

IJSW, 71(3), 387–415, July 2010


but are also an agent for ‘adequate and decent living’. Losing assets not

only makes livelihood insecure, but also leads to the loss of social status.

TABLE 3

Problems and Options of Rural Livelihoods

Occupation Problems Options

Cultivator • Increasing cost of

production

• Unfavourable weather

• Selling assets/ Migration

• Diversification

Agricultural labour • Seasonality

• Unfavourable weather

• Migration

Casual labour • Low wage

• Limited scope to work

• Migration

Artisans • Competition/Child labour

• Illness/ Social taboos

• Casual labour

Self employed • Competition

• Less skill

• Migration/selling assets

• Diversification

On comparing the average monthly remittances sent by the different

household types, we find that the self employed sends the highest amount

(Rupees 3,000), followed by the regular worker (Rupees 2,200), and the

casual labourer (Rupees 1,728.57). Among the three categories, the casual

labourer sends the highest percentage (70%) of remittances, followed by

the regular worker (62%) and self employed (15%). Migration and remit-

tances from migrants have become the major means by which the rural

poor gain access to higher economic opportunities. Yet, even though mi-

gration might assist in maintaining and even improving household in-

comes, the rural–urban flow of migrants do not necessarily create the basis

for long-term rural or urban development. Remittances do not find their

way into investments in infrastructure, market or other forms of economic

overheads needed for rural development (UNDP, 2000).

The Sikni factory is run almost completely by migrant workers of both sexes.

The factory has been in the village from the last 10 years and every year

workers come from nearby villages. There are 150 households who had settled

here temporarily on 1.5 bighas of land. They stay in this place from November

to May every year. All the workers are illiterate and the work is divided among

the men and women in the following manner: work which requires more

physical labour is obviously done by male members like putting the betel nuts

in the sun to dry, transporting them from one place to another, packing,

colouring, and so on. The female migrant workers clean and cut the betel nuts.

IJSW, 71(3), 387–415, July 2010


For cleaning, women earn Rupees 25 per bag and male members earn Ru-

pees 1,500 per month. There is no fixed time for women to do the cleaning

work. The more they can do, the more they earn. As this is a seasonal crop,

many of the women work overnight as earnings are limited for a few months

of the year. The women also have to manage the household work and

childcare responsibilities. Male workers work from 7 a.m. to 7 p.m. Almost all

these workers do not have homestead land and a few of them have half a kata

(1 bigha = 5 katas) or less than that. Female workers also earn from the outer

covering of the betel nut in the off season at Rupees 15 per bag or by stitching

katha (layers of cloth pieces stitched together, mainly used for children).

Chemicals used in the factory are disposed carelessly and stomach dis-

orders and fever are common among the workers. Physically, the wives are

assaulted regularly and they take it very easily as part of life. It is common

for the wife to run away from her ‘Daurain dain’ or husband to escape from

his beatings.

A quick study of the living conditions reveal lack of electricity, one tube

well and one kachaa toilet. The workers consider these facilities to be more

than what is available in their own homes. They feel that, over time, their

condition has improved as they own livestock like goat and poultry, which

helps in sustaining them during periods when they have no work. Since

they do not have a ration card—which could help them access the public

distribution system—the workers have to buy goods at the market price.

They do not buy fuel as they use the betel nut covering, which they get dur-

ing the season period.

Table 4 indicates the problem and option of livelihoods in urban areas.

The casual labourers and regular workers of urban areas are in a more vul-

nerable state as they do not have any option to come out of the problem of

living without basic amenities.

TABLE 4

Problems and Options of Urban Livelihoods

Occupation Problems Options

Self employed Competition, Illness Diversification

Casual labour/Regular worker Absence of basic amenities None

Income is one of the key factors for a sustainable livelihood. To under-

stand the difference in income, a comparative study of average monthly in-

come by occupation is presented in Table 5.

IJSW, 71(3), 387–415, July 2010


IJSW, 71(3), 387–415, July 2010

By comparing Table 5 and Table 6, gender discrimination in wage and

other earnings is clearly evident. Due to the many household constraints

and sickness, women cannot regularly go out to work. They also have to

take a break to nurse their children during work. This reduces their average

monthly earnings.

In rural areas, the women mostly work as weavers, agricultural labour, sell

liquor, and factory workers. Women find less opportunity for diversification

in villages. While men migrate and take up new employment opportunities,

women in rural areas find themselves at a relatively disadvantageous position.

Agricultural labour remains an easy option before them. Due to the large num-

bers of female agricultural labourers in 2004–2005, the percentage of female

agricultural labour in India was 72.8%, while the corresponding figure for

males was much lower at 48.9% (Sengupta, 2007).

In urban areas, more women are stepping out of their homes to add to

their limited household income. This enables them to meet the educational

and other expenditure of children.

Anjali Debi is a 36-year old woman who works in a printing press at Guwahati

and earns Rupees 35 daily (not regularly, but only when there are orders in the

press). She starts every day with the uncertainty of whether there will be work for

her or not. Her husband had a shop, which burnt down in a fire. Since her husband

suffers from high blood pressure, he cannot work in any other place. Somehow,

Anjali Debi helped him to start a shop near the railway gate. Her daughter is in

college and she wants her to study further. She says ‘I know my daughter will get

a job with her education. At least she will be able to live and will come out of any

problem in the near future.’ Every day is a struggle for the family.

Afia is a 20-year old girl from the agricultural labour dominated village of

Paschim Salapar and has nine brothers and sisters. Her father earns a livelihood

from farming, fishery and livestock. The father had a sewing machine and

encouraged Afia to take up tailoring as he wanted her to be self reliant. She has

done a certificate course in tailoring by staying at her uncle’s place in Nagaon

town. During Id or other such other festivals, she earns around Rupees 500, which

helps her to cover her expenditure on cosmetics. She has freedom to spend what

she earns on herself. Her cousin, Aktara is an embroiderer and earns Rupees

100–200 per month. Since not much significance is given to embroidery in the

region, Aktara does not get too many orders. In spite of having a certificate, Afia

has not been able to qualify for a loan, as she and her parents lack contact with

political power and the middlemen who manage the loan. Two girls from Afia’s

village, and who cannot stitch, have got loans for buying a sewing machine. Afia

wants to work more and earn for the future for which she needs to buy a new

machine as the current one is old and needs constant repairing.

To overcome various problems and challenges in livelihoods, diversifica-

tion in strategies are recommended for sustainable living. Diversification re-

duces dependence on one source of livelihood and reduces vulnerability to

IJSW, 71(3), 387–415, July 2010


specific stresses and shocks. Both rural and urban poor households can di-

versify their sources of income and carry out a portfolio of activities—

formal waged employment, informal trading, service activities, and so on,

with different family members engaging in them. But in this context it is to

be noted that engaging in too many activities can mean that households are

not able to invest sufficient time or resources in any one activity to make it

profitable. Thus, with proper balancing and study of market activities, diver-

sifications are to be taken up.

Injam Ali (42) is a father of four children. He owns 10 bighas of land on which

his preferred means of living was from summer paddy. But with increasing

expenditure, he is trying various alternatives. Two years back he made money

by selling jute at a higher price. With minimum capital of Rupees 20,000 he

purchased 90 mon (1 mon = 50 kg) of jute at Rupees 220/mon and after two

months he sold it at Rupees 440/mon. With this money, he reinvested in

poultry, which did not give a satisfactory return due to disease among the

chicken. He then entered into betel nut business and recovered the loss.

Recently, he has discovered that cultivation of bananas would be profitable and

has since then decided to cultivate banana on his land. He states, ‘the moment

business of particular thing is started—jute, betel nut—profit starts to flow. But

this continues only for a very short time, as the number of people doing the

same business increases leading to decline in profit margins. Constant

vigilance in the market and continuous change in alternative product for

business is essential for living in this area’. The living condition of Ali is better

than that of other villagers. He owns a pucca house with good water and

electricity facilities. Thus, Ali has turned an unfavourable situation to his

favour by keeping himself open to change and constantly diversifying his

source of income.

DISCUSSION

It is clear that, presently, cultivation is not a preferred livelihood strategy.

The self employed in the village are found to be in a better state and from the

secondary data we find they are in the highest percentage in rural Assam. It is

also seen that the successful self employed or cultivators are those who have

followed diversification in livelihood strategy. Constant vigilance of the

market and change accordingly is the prerequisite for sustaining any liveli-

hood strategy. Influence of competition is very strongly understood in rural

and urban livelihoods. With improved transport and communication, mobil-

ity has also increased and touched every activity of livelihood. In both rural

and urban areas, except casual labour of urban areas, very few from the rest

of the occupations could add asset holding significantly as done by the ear-

lier generation. Addition is done more in durables through various means

(selling livestock, loan from friends, father’s savings) for social status. The

artisans seem to be most hit among all the occupations by the wave of

IJSW, 71(3), 387–415, July 2010


changes as poverty along with child labour is common in such villages. The

skill, which could have been an asset for them, is of less use now as easily

available, substitute products have come into the market.

Age is found to be another determining factor influencing livelihood ac-

tivity. Senior workers pull on with the previous system as they can neither

migrate nor can try new things. Thus, they cannot add new assets but remain

as they were. The middle aged group, by trying diversification in cultivation

or business or any other thing, could add to their assets and improve rhwie

living condition. In all the study villages of both districts, the younger gener-

ation is in the most depressing conditions. Most of them do not want to get

into cultivation as it demands hard physical labour and poor cash returns. In-

stead, they hope to get white collar jobs in towns or cities after completing

their education. The data on urban area shows that when youngsters mi-

grated to Guwahati they hoped for such jobs, but ended up working as casual

labourers, where they live in a poor state. It was interesting to know that they

were happy as they were getting cash in addition to a taste of city life. Those

who stay back in the village lead a more frustrating life as there is nothing

except cultivation. Alcoholism is a major problem of this group in cultiva-

tor-dominated villages of Nagaon district.

The status of women is seen to differ in the village on the basis of reli-

gious background. Women in Muslim-dominated villages rarely perform

any other activity other than household work. The girl child is educated to

get a good husband. But now some young girls are trying to earn by various

means. Weaving is common practice in Assamese villages. But here too we

see the influence of competition from substitute products, which limit their

income. Even then women now feel that their status has improved as they

alone handle the cash and have a strong support of organisation. Compared

to the earlier generation, they find themselves to be in a better state. It is to

be noted that as far as violence against women is concerned, wife beating is

common in most of the villages. No gender discrimination was observed in

the field of education.

The data on secondary and primary livelihood activities makes it clear

that in both rural and urban areas, self employment is gradually increasing.

Poverty in rural livelihoods is very prominent and is forcing agricultural la-

bour to take up other occupations, leading to a decline in its percentage.

The PCA has also scored rural households low for poor housing conditions

and on parameters like literacy and access to credit. Influence of

liberalisation can be very clearly understood from the analysis—

IJSW, 71(3), 387–415, July 2010


availability of variety, easy accessibility and wide price ranges of product

has brought significant change in rural livelihood activities.

Figure 2 clearly indicates that diversification and credit support is essen-

tial for sustainable livelihood. The response to subsistence earning has two

diverse paths: (i) continuation of the strategy of the earlier period, which

leads to unsustainable livelihood with less resilience to shocks and

stresses; and (ii) diversification with credit support. Constant vigilance on

the market structure and adopting change in a positive manner leads to

higher security and sustainability of livelihood. To sustain livelihood, it

compelled the household by type and gender to be vigilant and diversify

their activities. The working population of all the types accepted that liveli-

hood is not as easy as it was during their previous generation.

The major reasons are unsuitable weather for cultivation, fluctuation of

prices, competition from better/substitute/cheap products and, lastly, the

reluctant attitude of the young generation towards undertaking livelihood

activities of rural areas. The interdependence of livelihood in rural and

urban areas is gaining importance and linkage is influencing the livelihood

of rural and urban areas both in positive and negative ways.

CONCLUSION

The above discussion draws out the following points of livelihood strate-

gies in Assam:

• Unfavourable weather, increasing expenditure structure, and reduced

size of cultivable land is making the livelihood of cultivators stressful.

Lack of mechanisation is mainly responsible for such a backdrop.

• Unemployment problem is frustrating the younger generation which,

to some extent, is responsible in increasing the problem of alcoholism.

• The younger generation want to try something other than cultivation.

• Agricultural and casual labourers are in the most stressful situation

with minimum asset holding and reduced work options. They get

compelled to out migrate in this situation.

• Enough scope is noted in the development of self-help groups of women

as they have a strong urge to do something in an organised manner.

• Artisans are in the worst state with poor sanitation, child labour, and

indebtedness common among their households.

• Organisational weakness and weak market structure has led to the

active participation of middlemen, which works as a depressing

factor in reinvestment and diversification.

IJSW, 71(3), 387–415, July 2010


IJSW, 71(3), 387–415, July 2010


In such a background, an integrated participatory process, with central,

state, and local government agencies sharing the responsibilities with local

residents and their representatives are required for long-term, need-based

development programme.

REFERENCES

Assam: Directorate of :

Economics and Statistics

2001

Statistical Handbook of Assam, Guwahati.

Assam: Directorate of :

Agriculture

no date

Available online at www.assamagribusiness.nic.in/statistical/

20Handbook/climate.pdf. Accessed on June 4, 2009.

Department for :

International

Development

2000a

Sustainable Livelihoods Guidance Sheet. Available online at

www.livelihood.org/info/info_guidancesheets.htm (Retrieved

October 12, 2004).

2000b : Sustainable Livelihoods and Poverty Elimination, Sustainable

Livelihood Guidance Sheet. Available online at www.liveli

hood.org/info/info_guidancesheets.htm. Accessed on October

12, 2004.

Fan, S., Fang, C. and :

Zhang, X.

2007

Master Plan for Guwahati Metropolitan 2025 (Revised Draft,)

New Delhi: Consulting Engineering Services (I) Private Limited.

India: Department of :

Statistics

1993–1994

Sources of Household Income in India 1993–1994, 50th Round,

Report No. 413, Fifth Quinquennial Survey, New Delhi.

1994–1995 : Household Consumer Expenditure and Employment Situation in

India 1994–1995, 51st Round, Revised Report No. 436(51/1.0/1)

, New Delhi.

1995–1996 : Household Consumer Expenditure and Employment Situation

in India 1995–1996, 52nd Round, Report No. 440(52/1.0/1),

New Delhi.

1997 : Household Consumer Expenditure and Employment Situation in

India 1997, 53rd Round, Report No. 442(53/1.0/1), New Delhi.

1999–2000a : Sources of Household Income in India 1999–2000, 55th Round,

Report No. 463 (55/1.0/5), New Delhi.

1999–2000b : Employment and Unemployment in India 1999–2000, Key

Results, 55th Round, Report No. 455(55/10/1), New Delhi.

2000–2001 : Household Consumer Expenditure and Employment Situation

in India 2000–2001, 56th Round Revised Report No. 476

(56/1.0/1) New Delhi.

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2001–2002 : Household Consumer Expenditure and Employment-

Unemployment Situation 2001–2002, 57th Round, Report No.

481 (57/1.0/1), New Delhi.

2004–2005a : Employment and Unemployment Situation in India 2004–2005

(Part I), 61st Round, Report No. 515(61/10/1) New Delhi.

2004–2005b : Employment and Unemployment Situation in India 2004-2005

(Part II), 61st Round, Report No. 515 (61/10/1), New Delhi.

Lucas, R. and Stark, O. :

1996

Involving Women in Sustainable Development: Livelihoods

and Conservation. In D.C. Pirages (Ed.), Building Sustainable

Societies: A Blue Print for a Post Industrial World, New York:

M.E. Sharpe Publications, 207–218.

Quisumbing, A.R., :

Brown, L.R.,

Feldstein, H.S.,

Haddad, L. and Pena, C.

1995

Women: The Key to Food Security, Food Policy. Available

online at www.siteresources.worldbank.org [Retrieved March

18, 2009].

Sengupta, A.K. :

1986

Women's Work, Class and the Urban Household: A Study of

Shimla, North India, London: Tavistock Publications.

2007 : Report on Condition of Work and Promotion of Livelihoods in

Unorganised Sector. Available on www.nceuis.nic.in/condition_

of_workers_Sep_2007.pdf. [Retrieved April 12, 2009]

United Nations :

Development

Programme

2000

Rural–Urban Linkages: An Emerging Policy Priority. Available

online at www.undp.org. Accesses on September 2, 2005.

IJSW, 71(3), 387–415, July 2010


APPENDIX 1Values of indicators for Principal Component Analysis

Pa

chim

Sa

lpa

ra

Ch

ako

riG

ao

n

Ku

chG

ao

n

Bh

aka

tga

on

Ka

lap

an

i

Ga

na

kpa

ra

Dh

op

gu

ri

Na

ga

on

To

wn

Gu

wa

ha

tiT

ow

n

Flood 100.00 20.00 35.00 23.00 100.00 100.00 13.00 5.00 0.00

Option 67.00 2.00 9.50 0.00 6.00 14.50 78.00 0.00 0.00

Casual 57.50 7.60 27.50 30.00 65.00 60.00 45.00 20.00 33.00

Violence 75.00 43.00 12.00 2.00 15.00 68.00 79.50 12.50 77.50

Homestead 1.65 2.64 1.75 1.40 1.53 1.31 1.85 0.75 0.34

Literacy 72.34 95.19 77.00 75.96 44.94 79.89 79.60 54.78 70.50

Dropout 57.50 32.50 29.68 40.63 16.22 72.50 53.85 12.22 14.00

Health Exp. 817.50 612.50 445.00 720.00 0.00 412.50 362.50 2200.50 3100.00

Credit 7.14 53.85 9.52 0.00 0.00 15.38 27.78 7.22 6.82

Non-Primary 25.00 53.08 26.38 44.00 5.66 20.22 18.98 75.00 31.80

WPR 53.07 57.44 58.53 42.60 62.35 77.53 55.95 53.01 56.98

Income 37838.75 57702.50 27672.75 59881.00 24373.00 23529.50 58161.00 52228.50 43553.83

No Health 32.50 55.00 32.50 10.00 15.00 10.00 25.00 2.50 0.00

Female Lit. 72.56 94.79 80.66 33.33 52.08 77.42 75.23 63.21 77.93

Non-Kutcha 27.50 77.50 15.00 40.00 10.00 47.50 55.00 47.50 35.83

Electricity 37.50 70.00 35.00 35.00 0.00 7.50 0.00 77.50 83.33

DW 15.00 45.00 0.00 5.00 0.00 32.50 25.00 57.50 40.00

Sanitation 0.00 50.00 10.00 15.00 0.00 5.00 10.00 65.00 18.33

IJSW, 71(3), 387–415, July 2010


IJSW, 71(3), 387–415, July 2010


AP

PE

ND

IX2

Co

rrel

ati

on

Ma

trix

of

the

Sel

ecte

dV

ari

ab

les

Co

rrel

ati

on

Flo

od

Op

tio

nC

asu

al

Vio

-le

nce

Ho

me-

stea

dL

ite-

racy

Dro

p-

ou

tH

ealt

hE

xp.

Cre

dit

No

n-

Pri

ma

ryW

PR

Inco

me

No

Hea

lth

Fem

ale

Lit

.N

on

-K

utc

ha

Ele

c-tr

icit

yD

WS

an

i-ta

tio

n

Flo

od

1.0

00

.22

3.8

15

.11

6.1

82

-.2

44

.47

9-.

56

9-.

26

4-.

62

2.5

29

-.7

41

.08

6-.

09

8-.

44

8-.

61

3-.

45

8-.

63

1

Op

tio

n.2

23

1.0

00

.43

9.6

21

.28

1.1

72

.59

3-.

30

9.1

33

-.4

04

-.0

39

.10

0.2

77

.17

9.0

36

-.4

67

-.1

59

-.4

24

Cas

ual

.81

5.4

39

1.0

00

.33

2-.

14

6-.

42

0.4

44

-.3

77

8-.

47

7-.

80

7.4

58

-.6

42

-.2

80

-.2

55

-.5

44

-.7

49

-.4

72

-.8

07

Vio

len

ce.1

16

.62

1.3

32

1.0

00

-.0

51

.36

5.5

00

.18

4.3

10

-.3

46

.35

6-.

01

5.0

74

.55

6.2

91

-.0

62

.31

0-.

29

1

Ho

mes

tead

.18

2.2

61

-.1

46

-.0

51

1.0

00

.55

1.3

55

-.7

66

.69

4-.

13

0.0

17

.14

3.9

25

.32

5.3

37

-.3

20

-.2

46

-.0

34

Lit

erac

y-.

24

4.1

72

-.4

20

.36

5.5

51

1.0

00

.52

5-.

16

1.7

29

.11

5.0

33

.36

0.8

09

.55

4.6

57

.12

1.1

67

.07

3

Dro

po

ut

.47

9.5

93

.44

4.5

00

.35

5.5

25

1.0

00

-.5

11

.19

5-.

36

5.3

51

-.1

13

.23

2.1

43

.22

9-.

55

9-.

15

5-.

47

7

Hea

lth

Ex

p.

-.5

69

-.3

09

-.3

78

.18

4-.

76

6-.

16

1-.

51

11

.00

0-.

19

2.5

09

-.2

36

.26

0-.

52

7.0

89

.10

6.8

10

.62

0.4

58

Cre

dit

-.2

64

.13

3-.

47

7.3

10

.69

4.7

29

.19

5-.

19

21

.00

0.2

19

.16

1.4

04

.73

8.7

15

.81

4.1

59

.45

2.4

09

Non-P

rim

ary

-.6

22

-.4

04

-.8

07

-.3

46

-.1

30

.11

5-.

36

5.5

09

.21

91

.00

0-.

44

5.6

19

-.0

36

.01

0.5

34

.77

0.6

76

.92

8

WP

R.5

29

-.0

39

.45

8.3

56

.01

7.0

33

.35

1-.

23

6.1

61

-.4

45

1.0

00

-.7

09

-.0

30

.46

7-.

01

5-.

37

0.1

23

-.2

55

Inco

me

-.7

41

.10

0-.

64

2-.

01

5.1

43

.36

0-.

11

3.2

60

.40

4.6

19

-.7

09

1.0

00

.13

3-.

10

2.6

85

.40

5.4

06

.56

1

No

Hea

lth

.08

6.2

77

-.2

80

.07

4.9

25

.60

9.2

32

-.5

27

.73

8-.

03

6-.

03

0.1

33

1.0

00

.55

2.3

23

-.0

41

-.1

20

.05

4

Fem

ale

Lit

.-.

09

8.1

79

-.2

55

.55

6.3

25

.55

4.1

43

.08

9.7

15

.01

0.4

67

-.1

02

.55

21

.00

0.4

08

.26

0.4

45

.19

6

No

n-K

utc

ha

-.4

48

.03

6-.

54

4.2

91

.33

7.6

57

.22

9.1

06

.81

4.5

34

-.0

15

.68

5.3

23

.40

81

.00

0.3

21

.71

8.6

08

Ele

ctri

city

-.6

13

-.4

67

-.7

49

-.0

62

-.3

20

.12

1-.

55

9.8

10

.15

9.7

70

-.3

70

.40

5-.

04

1.2

60

.32

11

.00

0.6

38

.72

6

DW

-.4

58

-.1

59

-.4

72

.31

0-.

24

6.1

67

-.1

55

.62

0.4

52

.67

6.1

23

.40

6-.

12

0.4

45

.71

8.6

38

1.0

00

.77

9

San

itat

ion

-.6

31

-.4

24

-.8

07

-.2

91

-.0

34

.07

3-.

47

7.4

58

.40

9.9

28

-.2

55

.56

1.0

54

.19

6.6

08

.72

6.7

79

1.0

00

IJSW, 71(3), 387–415, July 2010


Sig

.(I

tail

ed)

Flo

od

Op

tio

nC

asu

al

Vio

-le

nce

Ho

me-

stea

dL

ite-

racy

Dro

p-

ou

tH

ealt

hE

xp.

Cre

dit

No

n-

Pri

ma

ryW

PR

Inco

me

No

Hea

lth

Fem

ale

Lit

.N

on

-K

utc

ha

Ele

c-tr

icit

yD

WS

an

i-ta

tio

n

Flo

od

.28

2.0

04

.38

4.3

20

.26

4.0

96

.05

5.2

46

.03

7.0

72

.01

1.4

13

.40

1.1

13

.03

9.1

08

.03

4

Op

tio

n.2

82

.11

9.0

37

.23

2.3

29

.04

6.2

09

.36

6.1

40

.46

1.3

99

.23

5.3

23

.46

4.1

02

.34

1.1

28

Cas

ual

.00

4.1

19

.19

1.3

54

.13

0.1

16

.15

8.0

97

.00

4.1

08

.03

1.2

33

.25

4.0

65

.01

0.1

00

.00

4

Vio

len

ce.3

84

.03

7.1

91

.44

8.1

67

.08

5.3

17

.20

9.1

81

.17

3.4

85

.42

5.0

60

.22

4.4

37

.20

9.2

24

Ho

mes

tead

.32

0.2

32

.35

4.4

48

.06

2.1

75

.00

8.0

19

.38

9.4

83

.35

7.0

00

.19

7.1

88

.20

0.2

62

.46

5

Lit

erac

y.2

64

.32

9.1

30

.16

7.0

62

.07

4.3

40

.01

3.3

84

.46

6.1

71

.04

1.0

61

.02

7.3

78

.33

3.4

26

Dro

po

ut

.09

6.0

46

.11

6.0

85

.17

5.0

74

.08

0.3

07

.16

7.1

77

.38

6.2

74

.35

7.2

77

.05

9.3

45

.09

7

Hea

lth

Ex

p.

.05

5.2

09

.15

8.3

17

.00

8.3

40

.08

0.3

10

.08

1.2

71

.24

9.0

72

.41

0.3

93

.00

4.3

8..1

08

Cre

dit

.24

6.3

66

.09

7.2

09

.01

9.0

13

.30

7.3

10

.28

6.3

39

.14

0.0

12

.01

5.0

04

.34

2.1

11

.13

7

Non-P

rim

ary

.03

7.1

40

.00

4.1

81

.36

9.3

84

.16

7.0

81

.28

6.1

15

.03

8.4

63

.48

9.6

9.0

08

.23

.00

0

WP

R.0

72

.46

1.1

08

.17

3.4

83

.46

6.1

77

.27

1.3

39

.11

5.0

16

.47

0.1

03

.48

5.1

63

.37

6.2

54

Inco

me

.01

1.3

99

.03

1.4

85

.35

7.1

71

.38

6.2

48

.14

0.0

38

.01

6.3

67

.39

7.2

1.1

40

.13

9..0

58

No

Hea

lth

.41

3.2

35

.23

3.4

25

.00

0.0

41

.27

4.0

72

.01

2.4

63

.47

0.3

67

.06

2.1

98

.45

8.3

79

.44

6

Fem

ale

Lit

..4

01

.32

3.2

54

.06

0.1

97

.06

1.3

57

.41

0.0

15

.48

9.1

03

.39

7.0

62

.13

8.2

50

.11

5.3

07

No

n-K

utc

ha

.11

3.4

64

.06

5.2

24

.18

8.0

27

.27

7.3

93

.00

4.0

69

.48

5.0

21

.19

8.1

38

.20

0.0

15

.04

1

Ele

ctri

city

.03

9.1

02

.01

0.4

37

.20

0.3

78

.59

.00

4.3

42

.00

8.1

63

.14

0.4

58

.25

0.2

00

.03

2.0

13

DW

.10

8.3

41

.10

0.2

09

.26

2.3

33

.34

5.0

38

.11

1.0

23

.37

6.1

39

.37

9.1

15

.01

5.0

32

.00

7

San

itat

ion

.34

3.1

28

.00

4.2

24

.46

5.4

26

.09

7.1

08

.13

7.0

00

.25

4.0

58

.44

6.3

07

.04

1.0

13

.00

7

APPENDIX 3Values of the Indicators for Principal Component Analysis

Pa

chim

Sa

lpa

ra

Ch

ako

riG

ao

n

Ku

chG

ao

n

Bh

aka

tga

on

Ka

lap

an

i

Ga

na

kpa

ra

Dh

op

gu

ri

Na

ga

on

To

wn

Gu

wa

ha

tiT

ow

n

Flood 100.00 20.00 35.00 23.00 100.00 100.00 13.00 5.00 0.00

Option 67.00 2.00 9.50 0.00 6.00 14.50 78.00 0.00 0.00

Casual 57.50 7.60 27.50 30.00 65.00 60.00 45.00 20.00 33.00

Violence 75.00 43.00 12.00 2.00 15.00 68.00 79.50 12.50 77.50

Homestead 1.65 2.64 1.75 1.40 1.53 1.31 1.85 0.75 0.34

Literacy 72.34 95.19 77.00 75.96 44.94 79.89 79.60 54.78 70.50

Dropout 57.50 32.50 29.68 40.63 16.22 72.50 53.85 12.22 14.00

Health Exp. 817.50 612.50 445.00 720.00 0.00 412.50 362.50 2200.50 3100.00

Credit 7.14 53.85 9.52 0.00 0.00 15.38 27.78 7.22 6.82

Non Primary 25.00 53.08 26.38 44.00 5.66 20.22 18.98 75.00 31.80

WPR 53.07 57.44 58.53 42.60 62.35 77.53 55.95 53.01 56.98

Income 37838.75 57702.50 27672.75 59881.00 24373.00 23529.50 58161.00 52228.50 43553.83

No health 32.50 55.00 32.50 10.00 15.00 10.00 25.00 2.50 0.00

Female Lit. 72.56 94.79 80.66 33.33 52.08 77.42 75.23 63.21 77.93

Non-kutcha 27.50 77.50 15.00 40.00 10.00 47.50 55.00 47.50 35.83

Electricity 37.50 70.00 35.00 35.00 0.00 7.50 0.00 77.50 83.33

DW 15.00 45.00 0.00 5.00 0.00 32.50 25.00 57.50 40.00

Sanitation 0.00 50.00 10.00 15.00 0.00 5.00 10.00 65.00 18.33

IJSW, 71(3), 387–415, July 2010


IJSW, 71(3), 387–415, July 2010


AP

PE

ND

IX4

Res

ult

sof

the

Pri

nci

pal

Com

pon

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An

aly

sis:

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Init

ial

Eig

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alu

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qu

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dL

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din

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tati

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ms

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ad

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tal

Per

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tag

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Per

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ota

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of

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cen

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Per

cen

tag

e

Flo

od

6.6

62

37

.01

13

7.0

11

6.6

62

37

.01

13

7.0

11

6.1

77

34

.31

63

4.3

16

Op

tio

n4

.77

22

6.5

13

63

.52

44

.77

22

6.5

13

63

.52

44

.27

32

3.7

39

58

.05

4

Cau

sal

2.4

33

13

.51

47

7.0

38

2.4

33

13

.51

47

7.0

38

2.7

24

15

.13

37

3.1

87

Vio

len

ce1

.69

29

.40

38

6.4

40

1.6

92

9.4

03

86

.44

02

.38

61

3.2

53

86

.44

0

Ho

mes

tead

1.0

02

5.5

65

92

.00

6-

--

--

-

Lit

erac

y.6

76

3.7

55

95

.76

1-

--

--

-

Dro

po

ut

.49

92

.77

29

8.5

33

--

--

--

Hea

lth

Ex

p.

.26

41

.46

71

00

.00

0-

--

--

-

Cre

dit

9.3

8E

-01

65

.21

E-0

15

10

0.0

00

--

--

--

No

n-P

rim

ary

4.0

3E

-01

62

.24

E-0

15

10

0.0

00

--

--

--

WP

R2

.17

E-0

16

1.2

0E

-01

51

00

.00

0-

--

--

-

Inco

me

1.2

3E

-01

66

.81

E-0

16

10

0.0

00

--

--

--

No

Hea

lth

7.0

5E

-01

73

.92

E-0

16

10

0.0

00

--

--

--

Fem

ale

Lit

.-1

.38

E-0

16

-7.6

6E

-01

61

00

.00

0-

--

--

-

No

n-k

utc

ha

-1.5

6E

-01

6-8

.68

E-0

16

10

0.0

00

--

--

--

Ele

ctri

city

-2.6

0E

-01

6-1

.44

E-0

15

10

0.0

00

--

--

--

DW

-4.0

8E

-01

6-2

.27

E-0

15

10

0.0

00

--

--

--

San

itat

ion

-6.9

2E

-01

6-3

.84

E-0

15

10

0.0

00

--

--

--

No

te:

Ex

trac

tio

nM

eth

od

:P

rin

cip

alC

om

po

nen

tA

nal

ysi

s.

APPENDIX 5Initial Component Matrix

Component Matrix (a)

Component

1 2 3 4

Flood -.825 .120 .078 -.253

Option -.370 .494 .127 .625

Casual -.916 -.071 .278 .135

Violence -.123 .488 .744 .364

Homestead -.065 .806 -.545 -.172

Literacy .304 .796 -.018 .097

Dropout -.447 .634 .163 .314

Health Exp. .601 -.507 .537 .147

Credit .459 .841 .000 -.173

Non-Primary .892 -.164 -.105 -.021

WPR -.417 .280 .580 -.561

Income .725 .155 -.280 .574

No health .084 .804 -.399 -.221

Female Literacy .254 .657 .464 -.358

Non-kutcha .672 .586 .127 .131

Electricity .846 -.239 .182 -.116

DW .747 .095 .563 -.054

Sanitation .910 -.063 -.030 -.208

Note: Extraction Method: Principal Component Analysis; 4 components extracted.

IJSW, 71(3), 387–415, July 2010


Rotated Component Matrix (b)

Compnent

1 2 3 4

Flood -.744 -.015 .054 .457

Option -.356 .165 .773 -.192

Casual -.772 -.368 .346 .299

Violence .095 .012 .909 .323

Homestead -.271 .949 -.030 -.076

Literacy .240 .727 .386 -.028

Dropout -.409 .331 .665 .094

Health Exp. .761 -.587 .073 .003

Credit .402 .847 .217 .144

Non-Primary .812 .062 -.281 -.303

WPR -.185 .061 .150 .918

Income .556 .244 .188 -.744

No health -.080 .925 -.003 .013

Female Literacy .380 .505 .299 .591

Non-kutcha .642 .543 .338 -.087

Electricity .872 -.106 -.211 -.053

DW .888 -.006 .218 .223

Sanitation .858 .166 -.317 -.110

Note: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser

Normalization.Rotation converged in 8 iterations.

IJSW, 71(3), 387–415, July 2010


a comparative study of livelihood strategies in rural and...

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