Sabuj Kumar Mandal

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.

Amidst the laggardness of the farm sector, a major shift away from the farm sector to the rural non-farm sector (RNFS) has been observed in India, in the recent decades. However, the diversification into the RNFS, especially for the small and the marginal farmers, may be restricted due to the presence of various entry barriers like, lack of education in general and technical education in particular, credit constraint and a lower endowment of social capital. In this context, the study develops a simple theoretical model to incorporate the labour allocation decisions of the rural farm households, focussing on the potential entry barriers in the RNFS. The theoretically determined entry barriers along with other covariates are then used to empirically estimate the intensity of RNFS participation. We employ household level panel data on Indian states belonging to Semi-arid tropics (SAT) and Eastern regions, for the years 2010–14. A fractional response model is used to empirically analyse the determinants underlying RNFS diversification. The empirical results of the study confirm the presence of entry barriers in the form of lack of education and technical education, and access to credit and social capital. Other variables that are found to have a significant impact on diversification are land asset, family size, gender of the household head, age of the household head and farm income. Since, access to education, skill, credit and social capital are vital factors determining RNFS diversification, specific policies are required to be implemented for increasing access to these assets so as to increase RNFS employment in India.