首页|基于随机生产函数的农业气候风险管理效果评估方法与应用

基于随机生产函数的农业气候风险管理效果评估方法与应用

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[目的]全球气候变暖背景下,科学评估气候风险管理效果以增强适应气候变化能力至关重要。基于随机生产函数的计量经济分析框架被广泛应用于气候风险管理效果评估,但是较多文献对随机生产函数存在错误理解。本文旨在弥补已有文献不足,梳理随机生产函数在农业风险评估方面的应用情况,进一步为应对气候变化的资源管理优化提供合理建议。[方法]针对现有应用随机生产函数评估气候风险的多篇文献中存在的逻辑不自洽问题,提出转变随机生产函数的应用思路、优化气候变化风险管理效果评估的方法,并利用2001-2020年中国335个城市的面板数据,采用最大似然估计方法实证检验随机生产函数在评估农业适应气候变化措施效果方面的适用性。[结果]①增加作物播种面积、有效灌溉面积比例、单位面积化肥投入量以及单位面积农业用电量等常规要素投入均能提高作物单产。②扩大作物播种面积不仅有助于提高作物单产,同时还能显著降低作物的生产风险。增加有效灌溉面积比例、单位面积化肥投入量和单位面积农业用电量在提高单产的同时会加剧生产风险。③各类常规要素投入对作物生产的影响随气候条件而变化,也间接反映了在不同气候条件下,各类常规要素资源管理对抵御农业气候风险的能力存在差异。[结论]①气候变化本身就是农业生产风险的重要来源,把气候变化作为解释变量估计气候变化对风险影响的传统生产函数模型存在不足,该估计结果可能并不具有实质性经济涵义。②有必要将随机生产函数应用到识别气候变化与要素投入组合的影响,从而评估不同要素投入的抵御气候变化风险效果,进而为应对气候变化的资源管理优化提供合理建议。
Stochastic production function-based assessment of the performance of climate risk management in agriculture:Methods and applications
[Objective]As global warming progresses,it is of utmost importance to scientifically evaluate the effectiveness of climate risk management to enhance the capacity to adapt to climate change.The econometric analysis framework based on the stochastic production function has been widely utilized in the assessment of climate risk management effectiveness.Nevertheless,a significant number of studies misinterpret the stochastic production function.This study aims to address the shortcomings of existing literatures,review the application of the stochastic production function in agricultural risk assessment,and further provide rational suggestions for optimizing resource management in response to climate change.[Methods]In light of the logical inconsistencies in the existing literatures that apply the stochastic production function to assess climate risks,this study proposes a shift in the application approach of the stochastic production function to optimize the method for evaluating the effectiveness of climate change risk management.Using the panel data of 335 cities in China from 2001 to 2020,employing the maximum likelihood estimation method to empirically test the applicability of the stochastic production function in evaluating the effectiveness of agricultural measures in adapting to climate change.[Results](1)Increasing the sown area of crops,improving the proportion of effectively irrigated area,boosting the amount of fertilizer input per unit area,and raising the amount of agricultural electricity consumption per unit area can increase crop yield.(2)Expanding the sown area of crops can not only increase crop yield but also significantly reduce the production risks of crops.Improving the proportion of effectively irrigated area,boosting the amount of fertilizer input per unit area,and increasing the electricity consumption for agriculture per unit area,will expand the production risks while increasing crop yield.(3)The impact of conventional inputs on crop production varied with climate conditions,indirectly reflecting that under different climate conditions,various conventional resource management approaches have varying abilities to mitigate climate risks.[Conclusion](1)Climate change itself is an important source of risk in agricultural production.Using a traditional production function to estimate the impact of climate change on risk with climate change as an explanatory variable is wrong,and the resulting estimates may lack substantive economic implications.(2)It is necessary to apply the stochastic production function to identify the effects of climate change and resource input combinations,thereby evaluating the effectiveness of different resource inputs in mitigating climate change risks,and providing reasonable suggestions for optimizing resource management to address climate change.

climate change risksresource management measuresstochastic production functionperformance of adaptationagricultural production

汪阳洁、毛小燕、汪进贤、强宏杰

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中南大学商学院,长沙 410083

气候变化风险 资源管理措施 随机生产函数 适应效果 农业生产

2024

资源科学
中国科学院地理科学与资源研究所 中国自然资源学会

资源科学

CSTPCDCSSCICHSSCD北大核心
影响因子:2.408
ISSN:1007-7588
年,卷(期):2024.46(12)