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Off-farm employment experience triggers heterogeneity of exiting part-time farming in rural China

Yunli Bai, Weidong Wang, Linxiu Zhang

Part-time farming is a stable long-run occupation in rural labor market of China from 2008 to 2015. Off-farm employment experience generally has positive effects on long-term part-time farming and the probability of exiting part-time farming. It significantly promotes female to exit part-time farming.

Journal Title: China Agricultural Economic Review

Volume/Issue/Page: CAER-04-2020-0069

Published Time: February 2022

Abstract

Purpose – The purpose of this paper is to examine the occupational specialization in rural labor market by analyzing the nature of part-time farming in rural China and estimating the impact of off-farm experience on the individual’s persistence and exit of part-time farming as well as its heterogeneity.

Design/methodology/approach – Using the panel data collected in 100 villages and 2,000 households across five provinces in 2008, 2012 and 2016, this study provides insights on the nature of part-time farming in rural labor market and find the impact and mechanism of off-farm employment experience on exiting part-time farming by adopting event history analysis.

Findings – Part-time farming is a stable long-run occupation in rural labor market of China from 2008 to 2015. Off-farm employment experience generally has positive effects on long-term part-time farming and the probability of exiting part-time farming. It significantly promotes female to exit part-time farming.

Originality/value – Based on the two-sector model, this study builds a conceptual framework of off-farm experience and occupational specialization and sets a theoretical basis of hazard model when using event history analysis. This study contributes to identify the impact of off-farm experience on persistence and exiting

part-time farming in recent years. The empirical findings support the policy of promoting off-farm employment to improve occupational specialization. 

Corresponding author: Yunli Bai, baiyl.11b@igsnrr.ac.cn

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