Evidence map›Paper›PMID 36498441›Full record

ArticleInternational journal of environmental research and public health2022

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

Yan Wang, Lingling Zuo, Shujing Qian

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yan WangSchool of Business, Ningbo University, Ningbo 315211, China.
Lingling ZuoSchool of Business, Ningbo University, Ningbo 315211, China.
Shujing QianSchool of Business, Ningbo University, Ningbo 315211, China.

Funding

Fundamental Research Funds for the Provincial Universities of Zhejiang SJWY2021009Humanities and Social Science Fund of Ministry of Education of China 16YJC790103National Social Science Fund of China 22CTQ028
6 · The paper itself

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.

Indexed as

AgricultureIndustryChinaEconomic DevelopmentEfficiencyUrbanizationagriculturegreen-biased technical changeMalmquist–Luenberger indexSBM model

Identifiers

PMID36498441
PMCPMC9735650

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