The effects of low-carbon pilot policy on technological innovation: Evidence from prefecture-level data in China

Chen Zhu and Chien-Chiang Lee ()

Technological Forecasting and Social Change, 2022, vol. 183, issue C

Abstract: Using a balance panel dataset of 278 Chinese cities, this study is the first to employ a spatial difference-in-differences (SDID) approach to investigate both the direct and indirect effects of low-carbon pilot policy on technological innovation. A series of robustness tests including the parallel trend test, placebo test and using SDID with propensity score matching to alleviate spatial sample selection bias are performed. Furthermore, mechanism and heterogeneity analyses are conducted by using mediation effect and moderation effect models, respectively. The results show that implementing low-carbon pilot policy have a significant promotion effect on technological innovation both in pilot cities and neighbouring cities, resulting from enhancing green total factor productivity, optimizing the industrial structure, alleviating financing constraints, and enhancing economic density. Moreover, the technological innovation increasing effect is more significant in cities with higher CO2 emissions, more cultural diversity, higher political hierarchy, lower terrain relief and more integrated market. However, low-carbon pilot policy which implementing in cities with higher CO2 emissions would not help to promoting technological innovation in neighbouring cities. In addition, low-carbon pilot policy increase technological innovation within 700 km of the coastline, whereas the beyond 800 km, the reduction effect is dominant.

Keywords: Low-carbon pilot; Innovation; Spatial difference-in-differences model; Spatial spillover effect; China (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (64)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:183:y:2022:i:c:s0040162522004760

DOI: 10.1016/j.techfore.2022.121955

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