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Migration, local off-farm employment, and agricultural production efficiency: evidence from China

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Abstract

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.

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Notes

  1. NBSC: National Bureau of Statistics of the People’s Republic of China.

  2. High yields do not necessarily imply high efficiency, as “high-input” farmers can generate high yields but not efficiently utilize their inputs (Mochebelele and Winter-Nelson 2000).

  3. Local off-farm employment refers to any local wage-earning or self-employment activities inside own county. Migration is defined as any economic activities outside of own county.

  4. The assumption of the truncated normal distribution of technical inefficiency term \(u_{it}\) has been the dominant assumption in the SFP literature. However, there are attempts to generalize the model to alternative distributions of \(u_{it}\), such as the exponential and gamma distribution (van den Broeck et al. 1994, Tsionas 2002, Huang 2004). To allow different distributions of \(u_{it}\), the Bayesian method is generally needed. In that strand of the literature, simultaneous analysis of inefficiency has not been investigated. In this paper, we use classical MLE to estimate the model and restrict \(u_{it}\) to have a truncated normal distribution. A few existing studies comparing the effects of different distribution assumptions on efficiencies have also shown that the distribution assumption is largely immaterial (Greene 1990; Kumbhakar and Lovell 2000).

  5. The only difference between column 1 and column 2 is that the land size dummy and the interaction terms between land size dummy and the non-farm employment variables (i.e., migration and local off-farm employment) are included in the latter but not the former.

  6. We thank an anonymous associate editor for this constructive suggestion.

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Acknowledgments

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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Authors and Affiliations

  1. School of Economics, Huazhong University of Science and Technology, Wuhan, China

    Jin Yang

  2. Department of Economics, Department of Agricultural, Food and Resource Economics, Michigan State University, East Lansing, MI, USA

    Hui Wang

  3. Department of Agricultural, Food and Resource Economics, Michigan State University, East Lansing, MI, USA

    Songqing Jin

  4. School of Economics, Central University of Finance and Economics, Beijing, China

    Songqing Jin

  5. International Food Policy Research Institute, Beijing Office, Beijing, China

    Kevin Chen

  6. University of Washington, Seattle, WA, USA

    Jeffrey Riedinger

  7. Research Center for Rural Economy, Ministry of Agriculture, Beijing, China

    Chao Peng

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  1. Jin Yang
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  3. Songqing Jin
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Correspondence to Songqing Jin.

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Yang, J., Wang, H., Jin, S. et al. Migration, local off-farm employment, and agricultural production efficiency: evidence from China. J Prod Anal 45, 247–259 (2016). https://doi.org/10.1007/s11123-015-0464-9

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