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IASSI-Quarterly
Year : 2023, Volume : 42, Issue : 4
First page : ( 687) Last page : ( 707)
Print ISSN : 0970-9061. Online ISSN : 0974-018X.

Livelihood Choice of Agricultural Households in India and its Determinants: An Inter-State Analysis Based on 70th Round of NSSO

Dey Sagarika1

1Assistant Professor, Department of Economics, Assam University, Silchar, Assam, Email: dey_sagarika@rediffmail.com

Online Published on 09 February, 2024.

Abstract

This paper uses unit level data available from the 70th round of NSSO to analyse the livelihood choices among agricultural households in India and to assess the factors that influence such choices. Cluster analysis is employed to demarcate the livelihood options in terms of intrahousehold allocation of labour to various activities. The findings reveal that while overall agriculture is the mainstay of the agricultural households, significant variations in livelihoods exist among different landowning classes with the landless and marginal landowners being more dependent on livelihoods involving agricultural and non-agricultural labour. As landless and marginal landowners constitute the majority of rural households in India, the need to generategainful livelihoods for these households poses the single most important development challenge. As subsequent analysis has shown, households adopting casual wage labour as a livelihood option are at a higher risk of poverty. In contrast, households that are able to adopt salaried employment or other types of non-farm-based livelihoods have a lower incidence of poverty. Education is the single most important factor determining access to these livelihoods. Significant variations are found across Indian states in terms of livelihood structures. The state level regressions showed that while some factors such as per capita ownership of land had a uniform effect in influencing livelihood choices across all states, the role of other factors such as age, caste and education vary across states.

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Keywords

Livelihoods, Cluster analysis, Multinomial logit model, Poverty.

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