Do Green Production Technologies Improve Household Income? Evidence from Rice Farmers in China

Foyuan Kuang, Jiatong Li (), Jianjun Jin and Xin Qiu
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Foyuan Kuang: School of Economics, Nanjing University of Finance and Economics, Nanjing 210023, China
Jiatong Li: State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China
Jianjun Jin: State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China
Xin Qiu: State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China

Land, 2023, vol. 12, issue 10, 1-15

Abstract: Revealing the behavioral decision-making mechanism and behavioral effects of farmers adopting green production technologies will help motivate farmers to actively adopt green production technologies, thereby promoting the development of green agriculture. A stratified random sampling technique was used to select 607 Chinese rice farmers, while the endogenous switching regression model was used to analyze the influencing factors and behavioral effects of farmers adopting green production technologies. The results show that the adoption of green production technologies by farmers can significantly increase household income. Among the green production technologies, soil testing and formula fertilization technology has the greatest impact on farmers’ income, followed by straw returning technology and planting green manure. The main influencing factors of farmers adopting green production technologies are education level, cultivated land area, cultivated land fragmentation, soil fertility, and the distance between home and agricultural technology stations. The results of this study provide an empirical basis for relevant government departments to carry out agricultural technology extension work and formulate relevant policies.

Keywords: green production technologies; household income; rice farmers; the endogenous switching regression model; China (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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