Farm Exit among Smallhoder Farmers of Nepal: A Bayesian Logistic Regression Models Approach
Keshav P Pokhrel1, Taysseer Sharaf1, Prem Bhandari2
1Department of Mathematics and Statistics, University of Michigan-Dearborn.
Abstract:
To leave or not to leave farming? This is a dilemma facing a large number of farm households in a rural agrarian setting of Nepal where nearly two-thirds of the population is small holder farmers. Using the uniquely detailed retrospective panel data collected in 2015 from farming households, we examine the influence of the access to cultivated land holding and land tenure on subsequent farm exit. We address the statistical modeling issue of complete separation by developing a robust Bayesian predictive model to predict the probability of farm exit. We use the Bayesian framework with weakly informative prior to carry out the logistic regression model and compare it with other available binary response models. Our results show that the size of cultivated land has a strong negative influence on farm exit, net of all other controls. Moreover, farmers who rented farmland from others or who rented farmland to others were significantly more likely to exit farming. We estimate that a farm household required at least 5 Katha of land (one sixth of a hectare) per year to stay in farming.
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