Migration, local off-farm employment, and agricultural production efficiency: evidence from China
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This paper studies the effect of local off-farm employment and migration on the technical efficiency of rural households’ crop production using a five-year panel dataset from more than 2000 households in five Chinese provinces. While there is not much debate about the positive contribution of migration and local off-farm employment to China’s economy, there is increasing concern about the potential negative effects of moving labor away from agriculture on China’s future food security. This is a critical issue as maintaining self-sufficiency in grain production will be critical for China to feed its huge population in the future. Several papers have studied the impact of migration on production and have yielded ambiguous results. But the impact of migration on technical efficiency is rarely studied. Methodologically, we incorporate the correlated random-effects approach into the inefficiency analysis of the standard stochastic production frontier model to control for unobservable factors that are correlated with migration and off-farm employment decisions and technical efficiency. The most consistent result that emerged from our econometric analysis is that neither migration nor local off-farm employment has a negative effect on the technical efficiency of grain production, which does not support the widespread notion that vast-scale labor migration could negatively affect China’s future food security.
KeywordsMigration Local off-farm Agriculture Efficiency China
JEL ClassificationD24 O12 O13
The authors would like to acknowledge the support from NSFC71361140370, the CGIAR Research Program on Policies, Institutions and Markets led by IFPRI, and the National Social Science Fund of China (Grant No. 13CGL085). Financial supports from Michigan State University’s Competitive Discretionary Fund Program (09-CDFP-1965), the Office of the Provost and AgbioResearch are also greatly appreciated. The authors are also grateful to Peter Schmidt and Zhengfei Guan for valuable input on the paper’s econometric method. All errors remain the responsibility of the authors.
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