Abstract

Agricultural mechanization is an important factor to improve the green total factor productivity of the planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Based on the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of the output-oriented distance function to measure the green total factor productivity of China’s planting industry based on net carbon sinks, and empirically studies the impact of agricultural mechanization on the green total factor productivity in China’s planting industry. The main findings of this paper are as follows: (1) Agricultural mechanization can promote the planting green total factor productivity significantly, and this basic conclusion is still robust after using instrumental variables and sub sample regression. (2) The path of agricultural mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover, while the mechanisms of operation scale expansion, factor allocation optimization and technical efficiency change are not significant. (3) With the improvement in the mechanization level, the promotion effect of mechanization on planting GTFP will become clearer. Given these findings, the paper adds considerable value to the empirical literature and provides various policy and practical implications.

Highlights

  • The impact of mechanization on green total factor productivity (GTFP) depends on three aspects: the emissions increase effect caused by energy consumption, the emissions reduction effect caused by the optimization of agriculture chemical inputs and the sinks increase effect caused by the increase in yield

  • The mechanism path is mainly reflected in technology progress and spatial spillover, while the path of operation scale expansion, factor allocation optimization and technical efficiency change is not verified

  • Mechanization improves the efficiency of traditional energy utilization, changes the traditional factor input structure, and optimizes the energy consumption structure by increasing the utilization of renewable energy, and promoting planting GTFP

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. How of 20 ever, only considering carbon emissions overemphasizes the negative side of planting production and ignores the positive yield and carbon sink in the process of crop growth. The second method is to adopt net carbon sinks [4] based on the dual attributes of agriand ignores the positive yield and carbon sink in the process of crop growth. As agriculture has the dual attributes of carbon sinks and carbon sinks [4] (shown in Figure 1), it is a better option to use net carbon sinks as the carbon source, and China’s agriculture shows clear characteristics of net carbon sinks [4]. Based on the above analysis, this paper (shown in Figure 1), it is a better option to use net carbon sinks as the indicator to measure considers net carbon sinks as environmental factors to obtain the GTFP from the perspeccarbon emissions intensity.

Planting
Planting GTFP
Decomposition of Planting GTFP
Planting GTFP Is Influenced by Mechanization through Technology Progress
Planting GTFP Is Influenced by Mechanization through Changing Operation Scale
Planting GTFP Is Influenced by Mechanization through Spatial Spillover Effect
Method
Recursive Model for Mediating Effect Test
Spatial Econometric Model
Dependent Variable
Independent Variable
Instrument Variable
Intermediary Variables
Control Variables
Data Description
Results
The Basic Regression Results
Mechanism Test
Heterogeneity Analysis
Discussion
Findings
The Impact Mechanism of Mechanization on GTFP
Conclusions
Full Text
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