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The effect of innovation-driven development on pollution reduction: Empirical evidence from a quasi-natural experiment in China

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  • Gao, Kang
  • Yuan, Yijun

Abstract

Under the dual pressures of slowing economic growth and increasing environmental pollution in China, there is no doubt that relying on innovation to promote pollution reduction is the key to achieving compatible development between economic growth and environmental quality. Since previous studies have mostly explored the relationship between the two from the perspective of technological innovation, the endogeneity problem makes the research results lack credibility. This study attempts to fill this gap. Constructing a quasi-natural experiment based on the national innovative city policy, this study explores the impact and mechanism of innovation-driven development on pollution reduction using propensity score matching(PSM) and difference-in-differences(DID) models. The results demonstrate that the construction of national innovative cities has a positive effect on the reduction of pollution emissions intensity, which is mainly achieved through the improvement of urban innovation level and industrial R&D personnel concentration but has not effectively promoted pollution reduction through the advanced industrial structure. Additionally, national innovative city policy exhibits heterogeneous effects on pollution reduction. Specifically, the pollution reduction effect of big cities is weaker than that of small and medium-sized cities. The greater the manufacturing scale and the degree of financial support for science and technology, the stronger the pollution reduction effects. The pollution reduction effect shows a non-linear mechanism as pollution emissions intensity increases, and the overall trend is upward. Accordingly, corresponding policy recommendations are put forward based on the current weakness.

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  • Gao, Kang & Yuan, Yijun, 2021. "The effect of innovation-driven development on pollution reduction: Empirical evidence from a quasi-natural experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:tefoso:v:172:y:2021:i:c:s0040162521004790
    DOI: 10.1016/j.techfore.2021.121047
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