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The impact of environmental regulations and government subsidies and their policy mix on clean technology innovation

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Abstract

Existing frontier studies have predominantly focused on the incentivizing role of a single policy instrument, such as environmental regulations or government subsidies, in driving clean technology innovation. However, they have generally neglected to consider the impact of policy mix instruments on fostering clean technology innovation. This paper presents a mathematical deduction of the impact of environmental regulations, government subsidies, and their combined policy mix on clean technology innovation. Additionally, an empirical study is conducted using panel data from listed enterprises in China's clean energy industry spanning the period from 2008 to 2021. The findings reveal an inverted U-shaped relationship between both environmental regulations and government subsidies and the incentives for clean technology innovation, that is, they are characterized by promotion followed by suppression. Further analysis shows that a combination of environmental regulations and government subsidies positively promotes clean technology innovation. The results of the heterogeneity analysis indicate that environmental regulations and government subsidies have higher clean technology innovation performance for SOEs (state-owned enterprises), and the incentive effects of their policy mix are more significant. Moreover, in the eastern region, equal levels of government subsidies or environmental regulations yield higher incentives compared to the central and western regions, and the incentive effects of their policy mixes are more significant too. The findings of this paper will help policymakers flexibly design and implement incentive policies for clean technology innovation.

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Data availability

The datasets analyzed during the current study are available in databases such as Stata Intellectual Property Office, CSMAR, and WIND.

Notes

  1. The case of substitution σ > 1 (in fact the elasticity of substitution is much greater than 1) seems to be the more empirically relevant benchmark, as we expect clean technologies to substitute for non-clean but technologies.

  2. Labor market clearing requires that the demand for labor is less than the total supply of labor, normalized to 1, \({L}_{ct}+{L}_{dt}=1\).

  3. This assumption imposes a reasonable condition that innovative activities initially take place in the non-cleaning sector.

  4. Marketization and government efficiency are classified based on whether they are above or below the national average. To overcome endogeneity, the grouping of marketization and government efficiency has been done using historical information, grouped by 2008 data.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China for financial support through Grant No: 72164007 and No: 71463010, and research participants for their suggestions for the design of this study.

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  1. Cai Xiang, Ge Dongming, Zhao Xiaohui & Wang Yihui

    Present address: School of Business, Guilin University of Electronic Technology, Guilin, 541004, China

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    Dan Wang

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Table 11 Renewable energy IPC classification number
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Cai, X., Dan, W., Ge, D. et al. The impact of environmental regulations and government subsidies and their policy mix on clean technology innovation. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-03953-z

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