数字经济如何提升全要素碳效率——基于市场扭曲视角研究

doi:10.12118/j.issn.1000-6060.2025.557

Abstract

Abstract:

This study analyzes the mechanism through which the digital economy enhances total factor carbon efficiency from the perspective of market distortions, constructing causal mediation, dynamic spatial panel Durbin, threshold effect, and a quantile regression models using panel data from 282 prefecture-level cities in China from 2011 to 2021. Five relevant results emerge. (1) The digital economy significantly enhances carbon efficiency, and this conclusion remains robust following incomplete exogeneity instrumental variable tests, difference-in-differences estimation endogeneity tests, and multiple robustness tests. (2) Mechanism analysis validates reduced distortions in the product market as a primary pathway through which the digital economy enhances carbon efficiency. Subsequent sensitivity analysis confirms the robustness of this mediating effect. (3) Regarding the spatial spillover effects of the transmission mechanism, the digital economy significantly enhances total factor carbon efficiency in neighboring cities and alleviates product market distortions in these regions. (4) Concerning the heterogeneity of transmission mechanisms, the digital economy’s impact on improving carbon efficiency becomes more pronounced as a region’s carbon efficiency increases. Furthermore, as the degree of product market distortion rises, the digital economy’s effect on mitigating this distortion follows an inverted U-shaped pattern, initially intensifying before gradually weakening. (5) The digital economy’s impact on carbon efficiency exhibits an N-shaped double-threshold effect of first enhancing, then inhibiting, and subsequently promoting efficiency. This comprehensive mechanism analysis provides a novel perspective for systematically understanding the digital economy’s influence on enhancing carbon efficiency and reveals valuable pathways and policy insights for advancing carbon peak and neutrality goals.

Key words: digital economy, total factor carbon efficiency, market distortions, spillover effect, causal mediation effect, difference-in-differences model

YANG Qing, ZHANG Jinru, HAO Jiayi, ZOU Shaohui, ZHANG Lei. How does the digital economy enhance total factor carbon efficiency: A study from the perspective of market distortions[J].Arid Land Geography, 2026, 49(9): 1977-1994.

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变量	全要素碳效率
变量	（1）	（2）	（3）	（4）	（5）
dige	0.011^***（0.002）	0.047^***（0.002）	0.005^***（0.002）	0.025^***（0.002）	0.006^***（0.002）
常数项	0.583^***（0.002）	0.685^***（0.004）	0.782^**（0.013）	0.631^***（0.008）	0.813^***（0.025）
R²	0.015	0.364	0.838	0.532	0.842
调整后R²	0.015	0.362	0.821	0.530	0.826
控制变量	否	否	否	是	是
地区效应	否	否	是	否	是
时间效应	否	是	是	是	是

平均效应	置信区间	中介变量：产品市场扭曲
平均因果中介效应	[0.001, 0.003]	0.002
平均直接效应	[0.042, 0.049]	0.045
平均处理效应	[0.044, 0.050]	0.047

变量	SDM			SAR
变量	W1	W2	W3	W1	W2	W3
dige	0.024^***（0.002）	0.020^***（0.002）	0.024^***（0.002）	0.025^***（0.002）	0.023^***（0.002）	0.025^***（0.002）
W*dige	0.015^**（0.006）	0.020^***（0.006）	0.016^**（0.007）	-	-	-
直接效应	0.024^***（0.002）	0.022^***（0.002）	0.024^***（0.002）	0.025^***（0.002）	0.024^***（0.002）	0.025^***（0.002）
间接效应	0.023^***（0.008）	0.036^***（0.008）	0.024^***（0.008）	0.005^***（0.001）	0.009^***（0.001）	0.005^***（0.001）
总效应	0.047^***（0.008）	0.058^***（0.008）	0.048^***（0.008）	0.030^***（0.003）	0.033^***（0.003）	0.030^***（0.003）
rho	0.182^***（0.034）	0.300^***（0.030）	0.183^***（0.034）	0.161^***（0.030）	0.286^***（0.027）	0.161^***（0.030）
R²	0.551	0.570	0.551	0.544	0.545	0.544
控制变量	是	是	是	是	是	是
地区效应	否	否	否	否	否	否
时间效应	是	是	是	是	是	是

变量	SDM			SAR
变量	W1	W2	W3	W1	W2	W3
dige	-0.719^***（0.079）	-0.698^***（0.086）	-0.719^***（0.080）	-1.087^***（0.068）	-1.020^***（0.067）	-1.087^***（0.068）
W*dige	-1.669^***（0.194）	-1.105^***（0.183）	-1.673^***（0.195）	-	-	-
直接效应	-0.733^***（0.081）	-0.735^***（0.085）	-0.732^***（0.081）	-1.088^***（0.070）	-1.028^***（0.069）	-1.088^***（0.070）
间接效应	-1.837^***（0.191）	-1.517^***（0.198）	-1.842^***（0.192）	-0.198^***（0.046）	-0.331^***（0.050）	-0.120^***（0.046）
总效应	-2.570^***（0.160）	-2.252^***（0.163）	-2.574^***（0.161）	-1.287^***（0.085）	-1.359^***（0.094）	-1.287^***（0.085）
rho	0.065^*（0.035）	0.193^***（0.032）	0.065^*（0.035）	0.158^***（0.033）	0.252^***（0.031）	0.158^***（0.033）
R²	0.207	0.198	0.207	0.180	0.183	0.180
控制变量	否	否	否	否	否	否
地区效应	否	否	否	否	否	否
时间效应	是	是	是	是	是	是

变量	10%分位点	30%分位点	50%分位点	70%分位点	90%分位点	东部	中部	西部
dige	0.010^*** （0.003）	0.014^*** （0.002）	0.015^*** （0.003）	0.023^*** （0.004）	0.031^*** （0.005）	0.015^*** （0.004）	0.005^* （0.003）	0.001 （0.004）
常数项	0.586^*** （0.006）	0.606^*** （0.009）	0.614^*** （0.008）	0.625^*** （0.009）	0.630^*** （0.017）	0.828^*** （0.049）	0.650^*** （0.024）	0.646^*** （0.032）
R²	0.241	0.294	0.332	0.371	0.447	0.858	0.823	0.742
控制变量	是	是	是	是	是	是	是	是
地区效应	否	否	否	否	否	是	是	是
时间效应	是	是	是	是	是	是	是	是

How does the digital economy enhance total factor carbon efficiency: A study from the perspective of market distortions

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变量	10%分位点	30%分位点	50%分位点	70%分位点	90%分位点
dige	-0.247^**（0.116）	-0.345^***（0.081）	-0.377^***（0.080）	-0.323^***（0.093）	-0.192（0.177）
常数项	9.224^***（0.403）	9.825^***（0.402）	10.726^***（0.387）	12.959^***（0.413）	17.174^***（1.005）
控制变量	是	是	是	是	是
R²	0.170	0.159	0.145	0.143	0.151
地区效应	否	否	否	否	否
时间效应	是	是	是	是	是

项目	dige≤-1.094	-1.094<dige≤1.976	dige>1.976
dige	0.010^***（0.004）	-0.005^**（0.003）	0.009^***（0.002）
常数项	0.656^***（0.013）
控制变量	是
R²	0.561
时间效应	是
个体效应	否

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