Determinants of various modes of rural non-farm sector (RNFS) employment in SAT (semi-arid tropics) and Eastern regions of India: an empirical analysis

The objective of the present study is to identify the major motivating factors and thereby tracing out the existence of any entry barrier for several categories of rural non-farm sector (RNFS) employment in India. We conduct our analysis using household-level data from semi-arid tropics (SAT) and Eastern regions of India for the period 2010–2014. We disaggregate the RNFS activities into various categories—wage employment, self-employment, and others—and use a multinomial logit model as the baseline model to determine the factors driving participation in the various types of non-farm employment. Furthermore, Heckman Selection Model to account for selection bias in our sample and a multinomial fractional logit model to account for the intensity of RNFS income are used. The empirical results, based on a multinomial logit model, reveal that education in general and technical education, in particular, access to credit and endowment of social capital, are the major determinants of RNFS employment in India. However, these determinants are not same across the various RNFS sub-sectors. It is found that while education affects participation in wage employment and self-employment, technical education affects participation in wage employment and others only. Also, social capital determines employment in self-employment and wage employment, but does not determine employment under the ‘others’ category. Other factors that determine RNFS diversification are land and non-land assets, age, and gender of the household head, household size and distance from market. Policy implications of our empirical results are also discussed.