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The threshold effect of environmental regulation in the nexus between green finance and total factor carbon productivity: evidence from a dynamic panel threshold model

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Abstract

This paper investigates whether the effect of regional green finance (GF) on total factor carbon productivity (TFCP) differs by the level of environmental regulation intensity. Using data of 30 provinces in China from 2008 to 2020, we measure green finance based on the entropy weight method. Then, we employ the Super-slacks-based measure (SBM) model that incorporates undesirable outputs to calculate TFCP. Further, based on a dynamic panel threshold model, we empirically investigate the relationship between GF and TFCP. The main conclusions are as follows: (1) a nonlinear relationship exists between GF and TFCP in China. Moreover, we are the first to take market-based environmental regulation (MER) and command-and-control environmental regulation (CER) as threshold variables. With MER and CER as threshold variables, there was a double-threshold effect between both GF and TFCP. Hence, when GF has a negative impact on TFCP, the government should consider reasonably adjusting environmental regulations to reap the full benefits of GF in terms of TFCP growth. (2) The heterogeneity analysis states that the nonlinear effect of GF on TFCP in different regions is still significant under the thresholds of MER and CER. Therefore, the government should implement flexible environmental regulation policies to make GF promote TFCP according to region’s characteristics. This study provides a new perspective on the relationship between green finance and total factor carbon productivity.

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Data availability

The datasets used and/or analyzed in this study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors are very grateful to the editors and anonymous reviewers for their insightful comments that helped us sufficiently improve the quality of this paper.

Funding

This work was financially supported by the following foundations: Hebei Provincial Department of Education Humanities and Social Science Research Major Project (ZD202004); Natural Science Foundation of Hebei Province (G2021202001); Hebei Province Innovation Capacity Enhancement Program Project Soft Science Research Special (225576190D); and Major Project of Hebei Social Science Foundation (HB19ZD03).

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Contributions

Zibiao Li designed the study and revised the original manuscript. Siwei Wang proposed the conception of the study and wrote the manuscript. Xue Lu performed the numerical analysis. Xin Li and Han Li provided experimental data used in validating the model.

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Correspondence to Siwei Wang.

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All the co-authors agreed to publish the manuscript.

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The authors declare no competing interests.

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Appendix

Appendix

Tables 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 and 11

Table 1 Variable names and calculation methods
Table 2 Regional green finance evaluation index system
Table 3 Control variables
Table 4 Descriptive statistics
Table 5 Estimation results of the linear model
Table 6 Significance test and threshold estimation of each threshold variable
Table 7 Dynamic panel threshold model regression results
Table 8 Endogeneity test of each explanatory variable
Table 9 Results of robustness tests for removal of municipalities
Table 10 Results of sub-regional threshold test
Table 11 Test results of sub-regional environmental regulation threshold estimation

Figures 1, 2, 3, 4, 5, 6, 7 and 8

Fig. 1
figure 1

Average green finance level in 30 Chinese provinces from 2008 to 2020

Fig. 2
figure 2

Green finance in 30 provinces in China in 2008

Fig. 3
figure 3

Green finance in 30 provinces in China in 2012

Fig. 4
figure 4

Green finance in 30 provinces in China in 2016

Fig. 5
figure 5

Green finance in 30 provinces in China in 2020

Fig. 6
figure 6

Total factor carbon productivity trends for 30 Chinese provinces

Fig. 7
figure 7

Truthfulness test of market-based environmental regulation thresholds

Fig. 8
figure 8

Truthfulness test of command-and-control environmental regulation thresholds

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Li, Z., Lu, X., Wang, S. et al. The threshold effect of environmental regulation in the nexus between green finance and total factor carbon productivity: evidence from a dynamic panel threshold model. Environ Sci Pollut Res 30, 42223–42245 (2023). https://doi.org/10.1007/s11356-023-25214-2

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  • DOI: https://doi.org/10.1007/s11356-023-25214-2

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