Green-Biased Technical Change and Its Influencing Factors of Agriculture Industry: Empirical Evidence at the Provincial Level in China

Yan Wang (), Lingling Zuo and Shujing Qian
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Yan Wang: School of Business, Ningbo University, Ningbo 315211, China
Lingling Zuo: School of Business, Ningbo University, Ningbo 315211, China
Shujing Qian: School of Business, Ningbo University, Ningbo 315211, China

IJERPH, 2022, vol. 19, issue 23, 1-24

Abstract: The continued expansion of agriculture must contend with the dual pressures of changing factor endowment structure and constrained resources and environments. The main purpose of this paper is to provide feasible ideas for high-quality agricultural development in the transition period through the research on the green-biased technical change in Chinese agriculture. This paper selects China’s provincial panel data of the agriculture industry from 1997 to 2017, combining the DEA-SBM model and Malmquist–Luenberger index decomposition method to calculate the green-biased technical change (BTC) index; second, the influence mechanism of BTC is empirically investigated by using the panel data regression analysis approach. The results show that: (1) in China’s agriculture industry, BTC is the driving force behind long-term and steady improvement of technological advancement. Specifically, input-biased technical change (IBTC) has a substantial enhancing effect on agricultural green total factor productivity (GTFP), whereas output-biased technical change (OBTC) has a certain inhibiting effect. (2) On the whole, the tendency of capital substituting for labor and land is very evident, whereas the biased advantage of desirable output is not particularly prominent. (3) The BTC index in Chinese agriculture varies regionally. The eastern region has the highest IBTC index but the lowest OBTC index. (4) The degree of marketization, urbanization, capital deepening, financial support for agriculture, and other factors have a promoting effect on IBTC, whereas most of them have a restraining effect on OBTC. There is evident regional heterogeneity in the effect of environmental regulation intensity on BTC. The following are the primary contributions of this paper: based on national conditions in China, this paper empirically explores the changes and internal rules of green-biased technical change in China’s agriculture industry from various regional viewpoints. It provides an empirical foundation for the regional diversification of agricultural green transformation.

Keywords: agriculture; green-biased technical change; SBM model; Malmquist–Luenberger index (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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