Estimation of agricultural carbon abatement costs using a marginal-productivity-based production-input model: evidence from Fujian Province, China
7 affiliations
- 1College of Business, Quanzhou Normal University, Quanzhou, Fujian, China
- 2The Private Economic Development Research Institute of Characteristic New Think Tank for Universities in Fujian Province, Quanzhou, Fujian, China
- 3Quanzhou Rural Eevitalization Group, Quanzhou, Fujian, China
- 4Anxi College of Tea Science, Fujian Agriculture and Forestry University, Quanzhou, Fujian, China
- 5College of Resource and Environment Sciences, Quanzhou Normal University, Quanzhou, Fujian, China
- 6Laboratory of Regional Development Analysis and Simulation, College of Resource and Environment Sciences, Quanzhou Normal University, Quanzhou, Fujian, China
- 7College of Management and Economics, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China
Abstract
The shadow price of agricultural carbon emissions serves as a key indicator for quantifying the cost of carbon reduction in agriculture and for reflecting the associated opportunity costs. It has substantial theoretical and practical relevance for the green development and low-carbon transformation of agriculture under the dual-carbon goals. It holds significant theoretical and practical value for advancing green development and low-carbon transformation in agriculture under the dual-carbon goals. Drawing on marginal productivity theory, this study classifies agricultural carbon emissions as a production factor, builds a translog production function model, and employs ridge regression to address multicollinearity. Using panel data from nine prefecture-level cities in Fujian Province (2010–2023), we measure the shadow prices of agricultural carbon emissions across cities and conduct robustness tests via stochastic frontier analysis (SFA), exploring spatiotemporal evolutionary patterns and the drivers of regional disparities. The key findings are as follows: (1) Fujian’s agricultural carbon emission shadow prices show an overall sustained upward trend, with the economic opportunity cost of per-unit carbon reduction rising consistently across cities. (2) Significant regional disparities exist—the average shadow prices in eastern and northern Fujian remain among the highest in the province, while southern Fujian remains at a lower level, forming a “southeastern coastal–northwestern inland” dual spatial pattern. (3) The shadow price of agricultural carbon emissions varies significantly across regions, with Zhangzhou, Fuzhou, and Nanping having the highest emission reduction costs and Xiamen having the lowest. By quantifying the spatiotemporal characteristics of the costs of agricultural carbon emission reduction in Fujian, this study provides an economic basis for formulating differentiated carbon reduction policies while identifying limitations such as the restricted scope of carbon source accounting and clarifying directions for future research.
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BibTeX
@article{ye2026estimation,
title = {{Estimation of agricultural carbon abatement costs using a marginal-productivity-based production-input model: evidence from Fujian Province, China}},
author = {Jie Ye and Jie Ye and Renshan Xie and Qiao Quan and Feng Xie and Huangwei Li and Ketao Lin and Ketao Lin and Jianzhou Yang},
journal = {Frontiers in Sustainable Food Systems},
year = {2026},
month = oct,
doi = {10.3389/fsufs.2026.1953158},
url = {https://doi.org/10.3389/fsufs.2026.1953158},
note = {CC BY},
}
RIS
TY - JOUR
TI - Estimation of agricultural carbon abatement costs using a marginal-productivity-based production-input model: evidence from Fujian Province, China
AU - Jie Ye
AU - Jie Ye
AU - Renshan Xie
AU - Qiao Quan
AU - Feng Xie
AU - Huangwei Li
AU - Ketao Lin
AU - Ketao Lin
AU - Jianzhou Yang
PY - 2026
DA - 2026/10/25
JO - Frontiers in Sustainable Food Systems
DO - 10.3389/fsufs.2026.1953158
UR - https://doi.org/10.3389/fsufs.2026.1953158
AB - The shadow price of agricultural carbon emissions serves as a key indicator for quantifying the cost of carbon reduction in agriculture and for reflecting the associated opportunity costs. It has substantial theoretical and practical relevance for the green development and low-carbon transformation of agriculture under the dual-carbon goals. It holds significant theoretical and practical value for advancing green development and low-carbon transformation in agriculture under the dual-carbon goals. Drawing on marginal productivity theory, this study classifies agricultural carbon emissions as a production factor, builds a translog production function model, and employs ridge regression to address multicollinearity. Using panel data from nine prefecture-level cities in Fujian Province (2010–2023), we measure the shadow prices of agricultural carbon emissions across cities and conduct robustness tests via stochastic frontier analysis (SFA), exploring spatiotemporal evolutionary patterns and the drivers of regional disparities. The key findings are as follows: (1) Fujian’s agricultural carbon emission shadow prices show an overall sustained upward trend, with the economic opportunity cost of per-unit carbon reduction rising consistently across cities. (2) Significant regional disparities exist—the average shadow prices in eastern and northern Fujian remain among the highest in the province, while southern Fujian remains at a lower level, forming a “southeastern coastal–northwestern inland” dual spatial pattern. (3) The shadow price of agricultural carbon emissions varies significantly across regions, with Zhangzhou, Fuzhou, and Nanping having the highest emission reduction costs and Xiamen having the lowest. By quantifying the spatiotemporal characteristics of the costs of agricultural carbon emission reduction in Fujian, this study provides an economic basis for formulating differentiated carbon reduction policies while identifying limitations such as the restricted scope of carbon source accounting and clarifying directions for future research.
SN - 2571-581X
ER -