Keshav Pokhrel photo

Farm Exit Among Smallholder Farmers of Nepal: A Bayesian Logistic Regression Models Approach

Publication Abstract

Pokhrel, Keshav, Taysseer Sharaf, Prem B. Bhandari, and Dirgha J. Ghimire. Forthcoming. "Farm Exit Among Smallholder Farmers of Nepal: A Bayesian Logistic Regression Models Approach." Agricultural Research.

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 smallholder 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.

10.1007/s40003-020-00465-4

Browse | Search | Next

PSC In The News

RSS Feed icon

Mehta makes it clear why young people are leading the rise of COVID cases in Michigan: Socializing

More News

Highlights

Frey's Social Science Data Analysis Network, SSDAN wins 2020 MERLOT Sociology Classics Award

Doing COVID-19 research? These data tools can help!

More Highlights


Connect with PSC follow PSC on Twitter Like PSC on Facebook