Special Thesis & Basic Research

Calculation of Green Production Efficiency and Analysis of Influencing Factors of Double Cropping Rice in Southern China under the “Dual Carbon” Goals

Expand
  • Institute of Agricultural Economics & Information, Jiangxi Academy of Agricultural Sciences, Nanchang 330200, China
First author contact:

1st author: 737612165@qq.com

Received date: 2025-12-28

  Online published: 2026-07-14

Abstract

The southern rice region is a dominant area for double-cropping rice production in China, and the improvement of its green production efficiency has attracted widespread attention. Based on provincial panel data from 2003 to 2023, this study constructs an input-output indicator system that incorporates undesirable outputs. The DEA-SBM model is employed to measure the green total factor productivity (GTFP) of double-cropping rice in the region, and a multiple linear regression model is used to empirically analyze the influencing factors of GTFP, with robustness tests conducted. The results show that: (1) During the study period, the traditional total factor productivity (TFP) index was generally higher than the GTFP index. The annual average value of GTFP index was 1.010 4, indicating a gradual improvement in the GTFP of double-cropping rice in the southern rice region of China. (2) There were significant differences in the driving factors of GTFP growth among the ten provinces (autonomous regions) in the southern rice region of China. Specifically, GTFP growth in Zhejiang, Anhui, Fujian, and Hubei was driven by both green technological change (GTC) and green technical efficiency(GEC); Hunan, Guangxi, and Hainan relied mainly on GTC; while Guangdong, Jiangxi, and Yunnan were primarily driven by improvements in GEC. From the perspective of regional grain production and consumption characteristics, GTFP growth in major grain-producing areas followed a dual-driver pattern, major grain-consuming areas were driven by GTC, and grain-balanced areas depended on GEC. (3) Decomposition analysis of GTFP shows that under the “dual carbon” goals, the growth of GTFP in the southern rice region’s double-cropping rice sector was mainly attributed to GTC. (4) Agricultural economic development level, industrial structure index, and planting benefit level had significant positive effects on GTFP, whereas technological progress level and environmental regulation intensity exerted significant negative impacts.

Cite this article

YUAN Tingting, YU Yanfeng . Calculation of Green Production Efficiency and Analysis of Influencing Factors of Double Cropping Rice in Southern China under the “Dual Carbon” Goals[J]. China Rice, 2026 , 32(4) : 17 -24 . DOI: 10.3969/j.issn.1006-8082.2026.04.004

References

[1] 吕添贵, 梁慧, 陈安莹, 等. 长江中游粮食主产区农田生态系统碳源汇时空演化特征及碳平衡分区[J]. 水土保持研究, 2025, 32(6):337-347.
[2] 周应恒, 杨宗之. 生态价值视角下中国省域粮食绿色全要素生产率时空特征分析[J]. 中国生态农业学报(中英文), 2021, 29(10):1786-1 799.
[3] 田红宇, 刘魏. 环境约束、粮食绿色生产效率及其协调性研究 ——基于非期望产出模型[J]. 三峡大学学报(人文社会科学版), 2019, 41(5):76-82.
[4] 许朗, 罗东玲, 刘爱军. 中国粮食主产省(区)农业生态效率评价与比较——基于DEA和Malmquist指数方法[J]. 湖南农业大学学报(社会科学版), 2014, 15(4):76-82.
[5] 马林静, 王雅鹏, 田云. 中国粮食全要素生产率及影响因素的区域分异研究[J]. 农业现代化研究, 2014, 35(4):385-391.
[6] BALL V E, BUREAU J C, UTAULT J P, et al. Levels of farm sector productivity: An international comparison[J]. Journal of Productivity Analysis, 2001, 15(1): 5-29.
[7] 王淑红, 杨志海. 农业劳动力老龄化对粮食绿色全要素生产率变动的影响研究[J]. 农业现代化研究, 2020, 41(3):396-406.
[8] 张泽文, 张德硕, 崔茂森. 农机社会化服务对粮食绿色生产效率的影响分析[J]. 中国农机化学报, 2023, 44(8):221-230.
[9] 张标, 黄天辰. “双碳”目标下粮食主产区农业绿色生产效率研究——以安徽省为例[J]. 北方农业学报, 2023, 51(1):118-127.
[10] 曾福生, 高鸣. 我国粮食生产效率核算及其影响因素分析——基于SBM-Tobit模型二步法的实证研究[J]. 农业技术经济, 2012(7):63-70.
[11] FARRELL M J. The measurement of productive efficiency[J]. Journal of the Royal Statistical Society Series A (General), 1957, 120(3): 253-290.
[12] CHARNES A, COOPER W W, RHODES E. Measuring the efficiency of decision making units[J]. European Journal of Operational Research, 1978, 2(6): 429-444.
[13] CHANDA A, DALFAARD C J. Dual economies and international total factor productivity differences: Channelling the impact from institutions, trade, and geography[J]. Economica, 2008, 75(300): 629-661.
[14] APPLETON S, BALIHUTA A. Education and agricultural productivity: Evidence from Uganda[J]. Journal of International Development, 1996, 8(3): 415-444.
[15] GOLLIN D, LAGAKOS D, WAUGH M E. Agricultural productivity differences across countries[J]. The American Economic Review, 2014, 104(5): 165-170.
[16] 高维龙. 中国粮食产业高质量发展驱动机制研究[D]. 长春: 吉林大学, 2021.
[17] 阮华. 土地流转对粮食绿色生产技术效率的影响[D]. 南昌: 江西财经大学, 2021.
[18] 梅子. 化肥使用与粮食生产关联分析——以重庆市农业绿色生产为例[J]. 中国统计, 2019(12):65-67.
[19] 陈惠哲, 朱德峰, 杨仕华, 等. 我国南方稻区水稻产量差异及增产潜力[J]. 中国稻米, 2004, 10(4):9-10.
[20] 李斌, 祁源, 李倩. 财政分权、FDI与绿色全要素生产率——基于面板数据动态GMM方法的实证检验[J]. 国际贸易问题, 2016(7):119-129.
[21] 张利国, 鲍丙飞. 我国粮食主产区粮食全要素生产率时空演变及驱动因素[J]. 经济地理, 2016, 36(3): 147-152.
[22] 吴贤荣, 张俊飚, 田云, 等. 中国省域农业碳排放: 测算、效率变动及影响因素研究——基于DEA-Malmquist指数分解方法与Tobit模型运用[J]. 资源科学, 2014, 36(1):129-138.
[23] 闵锐, 李谷成. 转型期湖北省粮食绿色全要素生产率增长与分解——基于全国宏观横向比较的维度[J]. 湖北大学学报(哲学社会科学版), 2014, 41(1):137-141.
[24] 李波, 张俊飚, 李海鹏. 中国农业碳排放时空特征及影响因素分解[J]. 中国人口·资源与环境, 2011, 21(8):80-86.
[25] 黄伟华, 祁春节, 方国柱, 等. 农业环境规制促进了小麦绿色全要素生产率的提升吗?[J]. 长江流域资源与环境, 2021, 30(2):459-471.
Outlines

/

Copyright © Editorial office of China Rice
Tel: 0571-63370271, 63370368 E-mail: zgdm@163.com
Supported by Beijing Magtech Co., Ltd.