Sources of Total-Factor Productivity and Efficiency Changes in China’s Agriculture

Jianxu Liu, Changrui Dong, Shutong Liu, Sanzidur Rahman () and Songsak Sriboonchitta
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Jianxu Liu: School of Economics, Shandong University of Finance and Economics, Shandong Province, Jinan 250014, China
Changrui Dong: School of Economics, Shandong University of Finance and Economics, Shandong Province, Jinan 250014, China
Shutong Liu: School of Economics, Shandong University of Finance and Economics, Shandong Province, Jinan 250014, China
Songsak Sriboonchitta: Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand

Agriculture, 2020, vol. 10, issue 7, 1-18

Abstract: The core of agricultural development depends on agricultural production efficiency improvement, and total-factor productivity growth is its significant embodiment. Hence, it is essential to address the question of “how to improve China’s agricultural productivity and efficiency in order to achieve growth and sustainability of agriculture in the future”. This paper estimates indices of China’s agricultural technical efficiency (TE) scores, total-factor productivity (TFP), and its two components, technological change/progress (TC) and technical efficiency change (EC), using provincial-level panel data of 30 provinces from 2002 to 2017 by applying a stochastic frontier approach (SFA). The paper also identifies determinants of TE, TC, and TFP using selected indicators from four hierarchical levels of the economy, i.e., farm level, production environment level, provincial level, and the state level, by applying a system-GMM method. Results reveal that agricultural labor, machinery, agricultural plastic film, and pesticides are the significant drivers of agricultural productivity, with no significant role of land area under cultivation. Constant returns to scale exist in China’s agriculture. The agricultural technical efficiency level fluctuated between 80% and 91% with a stable trend and a slight decline in later years, while TFP improved consistently over time, mainly driven by technological progress. Among the determinants, government investment in agricultural development projects significantly drives TC and TE, while the experienced labor force significantly increases TE. The disaster rate significantly reduces TE but promotes TC and TFP. The literacy rate significantly improves TC and TFP. However, government expenditures in “agriculture, forestry, and water” significantly reduce TE, TC, and TFP. Policy recommendations include (1) increased levels of mechanization and agriculture film use while avoiding an increase in pesticide use, (2) a continued increase in government expenditure in agricultural development projects, R&D to improve technological progress, and diffusion of modern agricultural technologies, and (3) investment in education targeted at the farming population in order to continue the growth in the productivity and sustainability of China’s agriculture.

Keywords: China’s agriculture; technical change; agricultural productivity; production efficiency; stochastic frontier approach (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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