Paper Balwant Tambe

8/2/2019 Paper Balwant Tambe

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Poverty in Mountain Economy

A Case of North-Eastern State-Sikkim

Balwant Singh Mehta and Sadeep Tambe1

1. Background

In developing countries high poverty incidence is one of the major challenges. In the country

like India, where around 27 per cent of the people live in poverty, the economic and social

development of poor is a central issue for policy makers2. However, the major hurdle for

eradication of poverty is to identify poor and their characteristics. There are several

approaches have been used by development researchers, government agencies and social

scientist for the identification of poor. But these methods are general and not area specific.

In mountains, people livelihood is vastly different to plains. Therefore, using common

approaches for identifying poor at both mountains and plains has always many limitations. In

India, the north-eastern part is mainly covered by mountains, where people livelihood largely

depends upon agriculture, forestry, animal husbandry, horticulture and tourism. Sikkim, is a

landlocked state in the north-eastern region of India. The total geographical area of Sikkim is

7,096 sq km, which constitutes 0.22 per cent of the total geographical area of India. The State

is divided into four districtsSouth, North, East and West. Sikkim is the part of the Inner

Himalayas Mountain Ranges, the elevation ranging from 300 to 7000 meters above sea level.

The entire state is covered with hills and forest; only the southern part of the state (in the

lower Himalayas) is populated. The green cover of the State is critical for sustaining

livelihoods in agriculture, animal husbandry, and tourism. Forest resources have catered to

the requirements of local communities and tourism. The economy of Sikkim is largely

dependent on agricultural with principal crops grown here include maize, paddy, millet,

wheat and barley. Horticultural products include orange, potatoes, apples and cardamom.

Sikkim has the largest area under cardamom production. Tea is also grown in the state. The

tourism and handicrafts are also among other industries of economic importance. It is one of

the prosperous states of India owing to its political stability and economic growth

According to the 2001 Census of India, total population of Sikkim was around 540 thousands

with 89 per cent lives in rural areas. Social group wise distribution shows that about three-

Associate Fellow, Institute for Human Development, New Delhi and Special Secretary, Rural Management

and Development Department, Government of Sikkim, Sikkim respectively2 Planning Commission, Government of India, 2008


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fourth of the population belonged to other category and 21 per cent were tribal. Overall sex

ratio was 875 female per 1000 male with little higher in rural areas with 880 female per 1000

male. The literacy rate of the state was around 60 percent with 66 per cent of male and 51 per

cent of literate female. About 47 per cent of the population was economically active with 57

per cent male and 37 per cent female. Overall majority of the workers were involved in

agriculture and related activities (Annexure 1). According to Planning Commission estimate,

about 20.1 per cent people in the state lives below the poverty line in 2004-5, which has come

down drastically from 41 per cent in 1993-94. Although the states economy broadly depends

on the agriculture but its progress remain limited due to difficult topography and other natural

barriers. Recently, Sikkim government announced to make the state poverty free mission by

2013. Therefore, identifying the poverty and poor households in the mountain economy like

Sikkim will be an uphill task for such mission.

In this paper an attempt has been done in this direction by using various approaches to

calculate poverty and identify poor. This study will help greatly to policy makers and

development agencies for better policy formulation and implementation to eradicate poverty.

2. Objective of the Study

The main objectives of the study are following:

To measure poverty and identification of the poor.

Identify the socio-economic characteristic of the poor.

Major policy recommendation for eradication of the poverty.

3. Literature Review

There are numerous studies on poverty, inequality and material poverty or well being. In

India, mainly for hill regions very few studies have been done in the past. In this section few

prominent studies done in the past on poverty in hill economy have been discussed. One

major study on poverty especially for north-eastern state Poverty Eradication in North East

India: An Approach done by National Institute of Rural Development (NIRD) to identify the

factors contributing to poverty. This study emphasized on urgent need of four fold

developments: Economic, Human Resource, Institutional and Infrastructural development.

International level, The International Centre for Integrated Mountain Development

(ICIMOD) has done a series of studies focusing on mountain economy and poverty. These

studies explain that generally poor access to education and health, low level of infrastructure,


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lack of employment opportunities in mountain areas, the complexity and fragility of

mountain conditions, and the marginalisation of mountain communities from the mainstream,

coupled with climate stresses and proneness to natural disasters, contribute to the high levels

of income and food poverty. As a result, mountain people are increasingly exposed to

growing physical, social, and economic risks and vulnerabilities (Papola, 2008).

Studies on farming in mountain regions reveals that farmers are faced with a fragile and

unstable environment. Their livelihoods therefore depend on the adoption of complex

survival strategies involving a variety of enterprises (Yadav 1992, Demaine 1998). Wide

variations in micro-climatic conditions and small land parcels that often fall on steep slopes

provide limited scope for mechanisation and agricultural specialisation. Extreme poverty and

relatively low natural capital have furthermore limited the ability of farmers to absorb risks of

crop failure. Mountain farmers use forests and natural resources to gather a host of materialsfor food, fuel, medicines, construction materials, and other equipment. Livestock provides

draught power, meat, and cash income. In order to meet household cash requirements

mountain farmers have to resort to non-farm employment, sometimes in distant cities and

countries (Yadav 1992). Mountain agriculture is, therefore, much more complex, diverse, and

risk-prone than lowland agriculture. Sectoral policies and programmes designed to serve the

lowlands, particularly in relation to field crops, have failed to address the diverse needs of

mountain farmers that arise from the complex interdependencies between mountain

agriculture and mountain livelihood systems.

Further, studies shows that the human dimension of development processes in high mountain

regions regularly escapes appropriate assessment due to a lack of applicable methods.

Comparative data are lacking, and it is difficult to substantiate the position of mountain

societies within nation-states (Kreutzmann, 2008). In India, State Human Development

Reports have been prepared by many hill regions. These reports are more like evaluation or

academic kind, containing information on human development indicators. The reports

highlighted by effective policy intervention and implementation of mountain specific skilldevelopment with education will enable the people themselves to avail of the services on

offer, either within the region or beyond. States just need to provide opportunities for this to

happen, within the boundaries of area fragility and resource conservation (National Human

Development Report, 2001).


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The Planning Commission, Government of India use National Sample Survey Data for

calculating the poverty for North-Eastern State and takes Assam poverty ratio as the

representative for all the North-Eastern States including Sikkim. But there is no sound logic

behind it (Sarma Atul, 2004).

The above brief literature review shows that in India, there is lack of studies on measuring

poverty and especially identification of poor for mountain economy. Hence, there is an urgent

need to study detail poverty analysis for hill economy.

4. Research Methodology and Framework

The poverty related information on mountain regions is very scant, therefore we largely

depends upon the primary survey based information. For collecting information both

qualitative and quantitative tools have been used. A semi structured interview schedule

including major socio-economic characteristics has been canvassed for the collection of

quantitative information. For collecting qualitative information, wealth mapping and focus

group discussion is conducted with the villagers.

Two districts, one highly developed (East) and another backward (West) district of Sikkim

have been covered under the study. Majority of people in West district have low literacy, low

work participation and highly depend upon agricultural for their livelihood as compared to

East district. Further, within the district, one block and one Gram Panchayat in each district

have been selected for detailed household census survey. In each Gram Panchayat all the

villages have been covered under the study. Thus, in some way it is representing the state

with mixed population of backward and developed areas.

Poverty is a multidimensional concept. It encompasses both the prevailing welfare levels and

capabilities (IFAD, 2001). Most often it is measured and portrayed in terms of the indicators

of current levels of welfare, disregarding the capabilities of the population to sustain and

enhance it. This approach to poverty has serious limitations in mountains areas. Level of

welfare are also mostly seen in terms of some economic indicators-income and consumption.

Non-economic aspects of welfare and poverty are not necessarily ignored but it is assumed

that those poor in income and consumption terms are poor in other aspects as well, or those

able to meet some objectively determined minimum level of consumption expenditure are

also able to enjoy other social and political aspects of a decent living. These assumptions are


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not always valid. Improved income and consumption may be accompanied by higher

dependency and lower freedom while a great sense of empowerment and mobility could be

had even at low income levels (Jodha, 1988). Yet, economic indicators of poverty,

specifically private consumption or income below an objective poverty line, have continued

to be the most commonly used measures for analysis and poverty. Another, simplest

application of the summary economic statistic in this respect has been the dollar poverty

concept used by the World Bank to consider all those as poor who have less than 1 or 1.25

US dollar per day expenditure in constant purchasing power parity. Apart from these two

approaches, recent Tendulkar Committee poverty line has also been used.

These approaches only highlight proportion of people below the poverty line but do not

reveal much about their characteristics. There have been attempt to both sharpen the concept

of poverty by going beyond a single income or expenditure indicators or headcount ratio to

assess the poverty gap and severity of poverty and to include socio-political dimensions by

the multidimensional index of poverty such as the human development index (UNDP, 2002)

for different countries and regions or by bringing in aspects like vulnerability, deprivation,

lack of freedom and empowerment and exclusion in the analysis of poverty (Heninger, 1999).

Therefore, income quintile concept (dividing households or population on the basis of per

capita income) has been further used to identify the characteristics of poor people. The ratio

method is just an extension of quintile approach, as how far is the richest from the poor or

poorest. It measures the distance or gap of the lowest quintile (poorest) over the highest

quintile (wealthiest) at a particular place. Lastly, qualitative approach of wealth ranking or

mapping has been done to identify the characteristics of the poorest, poor and others in detail

according to the villagers.

5. Findings of the Study

The result shows that 502 households with a population of 2333 have been covered under the

survey. Kaluk block (857 persons) in the East district has substantially higher population ascompared to Ragoh (1476 persons) block of West district. Nazar Bartok (799 persons) and

Middle Lingtam (270 persons) village has the highest and the lowest population respectively.


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Table 1: The population of and household of district

HH PopulationDistrict/Block/Village N % N %

Lower LingtamMiddle LingtamUpper Lingtam

676274

13.3512.3514.74

288270299

12.3411.5712.82

West (Ragoh) 203 40.44 857 36.73

Nazar BartokYangsum

164135

32.6726.89

799677

34.2529.02

East (Kaluk) 299 59.56 1476 63.27

Total 502 100.00 2333 100.00

The social group wise distribution shows that around 42 per cent of the population belongs to

schedule tribe, followed by other backward class (34.46 per cent), Schedule caste (7.97 per

cent) and other caste (15.54 per cent). Further, religion wise distribution indicates majority of

the population belong to Buddhist (48.4 per cent) followed by Hindus (39.8 per cent) and

Christian (10.8 per cent) and others.

5.1. Poverty Analysis

Overall poverty has been calculated by three major approaches by using income approach,

i.e. monthly per capital income approach (MPCI). Accordingly, using Planning Commission

and Tendulkar Committee poverty line, 24.1 per cent and 47.1 per cent people are below

poverty line respectively. The International 1.25$ (dollar) approach, 29.88 per cent people are

living below poverty line.

General16%

OBC34%

SC8%

ST42%

Religion Wise Distribution

Hinduism

40%

Christianity11%

Buddhism

48%

Others

1%

Social Group Wise Distribution


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Table 4: Measuring Poverty through various methods

PlanningCommission

TendulkarCommittee

World Bank

N % N % N %

Poverty 121 24.1 236 47.01 150 29.88

However, overall poverty, only indicate the proportion of people living below poverty line. It

does not reveal much about the characteristics of poor people. In the subsequent section

quintile approach has been used to study this phenomenon in detail.

5.1.1. Identifying Poor

There are two approaches as discussed above have used to identify poor and their

characteristics. In this sub-section, quantitative approach of income quintile has been used to

further identify the poor people.

5.1.1a: Quantitative Approach

The educational level clearly shows that educational level of the poorest household is lower

than others. Household size of poorest household is almost double of wealthy or top quintile

households. The result further corroborated by dependency ratio, as dependent among poor

households are substantially higher as compared to others. Further, land holding size also

reveal, poorest households have lowest landholding, although there is no such differencefound among other income classes. Broadly, census results show that poor households have

lower literacy, higher family size and dependency. However, land categories have significant

importance among poorest households but productive land play major role among other

income classes, not the average land size only. Per capita income of the poorest households

is seven time lower than wealthiest indicate the poverty gap or distance.

Table 6: Major Household Indicator by quintile wise

Bottom20% Q2 Q3 Q4 Top20% Total

Literacy 74.5 77.4 78.1 78.2 81.1 77.6Household Size 5.6 5.1 5.4 4.2 2.9 4.6Sex Ratio 941 1012 894 1103 849 961Dependency Ratio 96.1 74.6 62.5 52.7 40.0 66.5Land Holding 0.74 1.67 1.01 0.44 1.22 1.02Average MPCI 350 563 765 1018 2431


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The social group wise distribution indicates schedule tribes are well off compared to other

social groups. In hills, especially in Sikkim social groups or caste does not play any role in

the poverty of the households.

Table 7: Social group wise distribution

Social Group Bottom20%

Q2 Q1+Q2[poor]

Q3 Q4 Top20%

Q4+Q5[wealthy]

Total

General 21.8 25.6 47.4 14.1 20.5 17.9 38.5 15.5

OBC 21.4 17.9 39.3 22.5 19.1 19.1 38.2 34.5

Schedule Caste 20.0 22.5 42.5 20.0 32.5 5.0 37.5 8.0

Schedule Tribe 18.0 19.4 37.4 19.9 18.5 24.2 42.7 42.0

Total 19.9 20.1 40.0 19.9 20.1 19.9 40.0 100.0

Further, educational level data reveal that majority of households members of poor

households are illiterate and below secondary level qualification. The people belong to

wealthiest category have higher number of secondary and above qualified people. This

analysis clearly indicates educational level or human capital in the households play an

important role in coming out of poverty.

Table 8: Education level by quintile wise

Education Level Bottom20%

Q2 Q1+Q2[poor]

Q3 Q4 Top20%

Q4+Q5[wealthy]

Total

No education 26.00 21.99 47.99 22.83 18.18 10.99 29.18 22.44

Below secondary 24.65 23.04 47.69 22.89 18.71 10.71 29.42 64.66

Secondary and above 8.82 15.81 24.63 27.21 19.85 28.31 48.16 12.90

Total 22.91 21.87 44.78 23.43 18.74 13.05 31.78 100.00

The distribution by main occupation reveal that majority of poor households are involved in

agriculture and non-agriculture wage employment followed by small and marginal land

holders involved in self agriculture (cultivator, plantation and animal husbandry etc)

activities. Whereas, majority of wealthy households are big land holders involved in self

agriculture (large landholders, plantation, animal husbandry) and salaried employment. Other

categories like pensioner, Remittances, interest and rental income belong to wealthiest

categories in the village.


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Table 9: Main occupation by quintile groups

Main Occupation Q1 Q2 Q1+2[poor]

Q3 Q4 Q5 Q4+5[wealthy]

Total

Self employment in agriculture 19.2 21.2 40.4 19.9 21.2 18.5 39.7 30.1

Self employment in non-agriculture 14.7 26.5 41.2 14.7 29.4 14.7 44.1 6.8

Wage employment in agriculture 37.1 19.1 56.2 23.6 10.1 10.1 20.2 17.7

Wage employment in non- agriculture 21.8 25.6 47.4 21.8 22.6 8.3 30.8 26.5

Salaried 2.7 9.3 12.0 16.0 22.7 49.3 72.0 14.9

Others 10.0 10.0 20.0 15.0 15.0 50.0 65.0 4.0

Total 19.9 20.1 40.0 19.9 20.1 19.9 40.0 100.0

5.1.1b: Qualitative Approach

The qualitative tools, wealth mapping and focus group discussion have been conducted in

Lower Lingtam village to get perception of people on poverty in the village. The villagers

have been facilitated though group discussion on identifying the wealth class of people in the

village. As per the focus group discussion with the villagers, four classes have been emerged,

poorest, poor, medium and wealthiest families. Out of total 48 households in the village, 16

households (36 per cent) are classified as well-off; 10 households (22 per cent) as medium;

12 (27 per cent) households as poor and 7 households (16 per cent) are the poorest.

Focus Group Discussion of Wealth Classes in Village Lower Lingtam


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Table 10: Criteria of wealth mapping or ranking according to focus group discussion

Criteria Poorest Poor Medium Well-Off

Housing Kuccha orSemi-Pucca house

PuccaHouse

Pucca House Pucca House

Income source Casual labour Casual

labour

Salaried government

employee (temporaryor contractual), smallcontractor (4th grade)

Regular Government

Employee, Bigcontractor (1-3 grade)

Land ownership Less than half acre to 6acres

6 to 10 acres 10 acres or more

Assets - Taxi vehicle owner Private 4 wheel motorvehicle

Vulnerability Single womenheaded Household

Illness ofhousehold

head

- -

No. of Household 12HHs (27%) 7HHs

(16%)

10HHs (22%) 16 HHs (36%)

The villagers indicated that poorest and poor categories in the village are those having no

land (landless) or marginal lands, Kachha Houses/Semi Pucca houses, involved in casual

labour activities, high dependency ratio and single women headed households. However,

medium class category are mainly having pucca houses, land between 6 to 10 acres, taxi or

vehicle owner (four wheeler), shop owner and regular salaried. Finally, wealthy people in the

village are having regular government employment, land holding more than 10 acres, pucca

houses, private motor vehicle and pensioner or retired government service holders. These

results further explain the quantitative finding of the study and more specifically indicated the

category of poor people. The poor households of hill economy are involved in casual labour

activities, landless, residing in Kachha houses and female headed in the Sikkim.

6. Conclusion and Policy Recommendation

Finally, the results of both quantitative and qualitative survey indicate that identification of

poor has two major dimensions. One set of poor people those who have productive and non-

productive assets, other who have better human capital base like skills or educational level.

The above analysis shows that poor people are mainly involved in unskilled casual labour.

The identification of human capital will help policy makers to provide income generating

activities or employment (like in hotel and tourism industry like driving, hotel jobs and guide

etc.) to skilled poor by imparting training. One the other hand poor people those who have

non-productive land due to irrigation problem, thus government can provide them irrigation

facilities to make their land productive.


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Another, set of people those who are unskilled can be not be provided direct income but

through the development of local infrastructure like improvement of road, transport and

electricity, local employment opportunities in non-farm sectors will be available. In this

direction MGNAREGA is already generating lot of employment opportunities for local

unskilled labour but due to large family size 100 days of employment is not sufficient for

them.

To sum up the human capital, productive assets and infrastructure holds key role in coming

out of poverty. Therefore, following are some of the key issues need to be address to

eradicate poverty in rural areas:

Providing facilities for skills and higher education to rural poor people

Enhancing, rural non-farm employment opportunities by providing better

infrastructure like road, transport, electricity and communication facilities

Encouraging rural youth towards mountain specific non-farm activities like animal

rearing, horticulture and handicraft etc through providing training and credit facilities

So, there is an urgent need to identify poor people across their activity level, assets and

human capital base. This profile will help policy makers in formulation of better and target

specific policy for poverty eradication. If these policies are properly designed and address by

government, poverty free State is possible in long run.

Bibliography

Banskota, M. (1997) Mountain Accessibility and Rural Roads: Innovations and Experiencesfrom Nepal. In Issues in Mountain Development 97/5. Kathmandu: ICIMOD

Banskota, M. (2000) The Hindu Kush-Himalayas: Searching for Viable Socioeconomic andEnvironmental Options. In Banskota, M.; Papola, T.S.; Richter, J. (eds), Growth, PovertyAlleviation, and Sustainable

Bhatia, A. (2000) Participatory Forest Management (PFM): Rediscovery of a PromisingMechanism for Poverty Alleviation in the Mountain Areas of South Asia. In Banskota, M.;

Papola, T.S.; Richter, J. (eds).

Demaine, H (1998) A Livelihood Systems Approach to the Sustainable Development ofUpland Farming Systems. In Upland Farming Systems in the Lao PDR: Problems andOpportunities for Livestock, Chapman, EC; Bouahom, B; Hansen, PK (eds). ACIARProceedings No. 87. Canberra: Australian Centre for International Agricultural Research

Human Development Report, 2001, Government of Sikkim, Sikkim, 2008


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Jodha N S (1998), Poverty Debate in India: A Minority View in Economic and PoliticalWeekly, Special Article, 23, 1998

Quick Estimate of Poverty, 2004-05 (2008), Planning Commission Government of India,2008

Papola, T.S. (1996) Integrated Planning for Environment and Economic Development inMountain Areas. Discussion Paper Series No MEI 96/2. Kathmandu: ICIMOD

Papola, T.S. (2002) Poverty in Mountain Areas of the Hindu Kush- Himalayas: Some BasicIssues in Measurement, Diagnosis, and Alleviation, Talking Point 2/02, Kathmandu:ICIMOD

Poverty Eradication/Alleviation in North East India: An approach, National Institute of

Rural Development (NIRD), North Eastern Regional Centre, Guwahati, Assam,2008

Prakash, S. (1997) Poverty and Environment Linkages in Mountains and Uplands:Reflections on the Poverty Thesis. CREED Working paper Series No. 12. London:

International Institute of Environment and Development

Yadav, Y (1992) Farming-ForestryLivestock Linkages: A Component of MountainFarmers Strategies (Nepal). In Sustainable Mountain Agriculture: Perspectives and Issues,Vol. 1, pp. 143161, Jodha, NS; Banskota, M and Partap, T (eds). New Delhi: Oxford andIBH Publishing Co. Pvt. Ltd

Annexure 1: Demographic Indicator, Sikkim and East & West District

Source: Census of India, 2001

Sikkim East West

Total Rural Total Rural Total RuralN 540,851 480,981 245,040 192,188 123,256 121,432Population

Percentage in Rural - 88.93 - 78.43 - 98.52

Sex Ratio 875 880 844 845 929 931

SC 5.0 5.0 5.8 6.0 4.7 4.6

ST 20.6 21.2 18.5 19.1 19.3 19.5

Social Group

Others 74.4 73.8 75.7 75.0 76.0 75.9

Persons 58.9 56.8 65.1 62.3 49.2 48.9

Male 65.5 63.8 71.4 69.2 56.1 55.8

Literacy

Female 51.2 48.9 57.7 54.1 41.7 41.5

Persons 48.6 49.7 47.6 49.6 43.2 43.3

Male 57.4 57.7 58.0 58.7 52.2 52.0

WPR

Female 38.6 40.6 35.2 38.8 33.6 33.8

Cultivator 47.5 53.1 27.4 34.7 67.3 68.4

Agriculture Labour 4.3 4.7 4.5 5.7 5.4 5.5

Household Activities 1.5 1.5 1.5 1.7 2.1 2.0

Main Occupation

Others 46.7 40.7 66.6 57.9 25.2 24.1

Total 100.0 100.0 100.0 100.0 100.0 100.0

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