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The Growth Path of Agricultural Labor Productivity in China: A Latent Growth Curve Model at the Prefectural Level

by Peng Bin 1,2,* and Marco Vassallo 3
1
School of International Studies, University of Trento, Via Tommaso Gar 14, Trento 38122, Italy
2
College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China
3
Agricultural Research Council (CRA), Via Ardeatina 546, Rome 00178, Italy
*
Author to whom correspondence should be addressed.
An initial version of this paper is presented in the 133rd EAAE seminar “Developing Integrated and Reliable Modelling Tools for Agricultural and Environmental Policy Analysis”, 15–16 June 2013, Chania, Crete, Greece.
Academic Editor: Ralf Fendel
Economies 2016, 4(3), 13; https://doi.org/10.3390/economies4030013
Received: 22 January 2016 / Revised: 19 May 2016 / Accepted: 21 June 2016 / Published: 30 June 2016
Given the shrinking proportion of agriculture output and the growing mobility of the labor force in China, how agricultural labor productivity develops has become an increasingly attractive topic for researchers and policy makers. This study aims to depict the development trajectory of agricultural labor productivity in China after its WTO entry. Based on a balanced panel data containing 287 Chinese prefectures from 2000 to 2013, this study applies the Latent Growth Curve Model (LGCM) and finds that the agricultural labor productivity follows a piecewise growth path with two breaking points in the years of 2004 and 2009. This may stem from some exogenous stimulus, such as supporting policies launched in the breaking years. Further statistical analysis shows an expanding gap of agricultural labor productivity among different Chinese prefectures. View Full-Text
Keywords: agricultural labor productivity; growth trend; divergence; agricultural reforms agricultural labor productivity; growth trend; divergence; agricultural reforms
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Bin, P.; Vassallo, M. The Growth Path of Agricultural Labor Productivity in China: A Latent Growth Curve Model at the Prefectural Level. Economies 2016, 4, 13.

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