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How does the selection of National Development Zones affect urban green innovation?

Citation

Yu, Xiaolin; Wan, Kai (2022), How does the selection of National Development Zones affect urban green innovation?, Dryad, Dataset, https://doi.org/10.5061/dryad.8gtht76rp

Abstract

The launch of the selection process for National Development Zones (NDZs) marked a fundamental change in the construction of development zones, making it an essential position for local authorities to implement high-quality development. Based on the data of prefecture-level cities in China from 2000 to 2018, this paper examines the impact and mechanism of selecting NDZs on urban green innovation through a double-difference spatial durbin model using the selection of NDZs as a “quasi-natural experiment”. The study finds that the selection of NDZs can promote green innovation in cities and has a significant window-radiating effect. The heterogeneity test results show that the implementation of the selection policy for development zones in non-old industrial cities, large and medium-sized cities, cities with easy access to transportation, and cities with high market orientation are more likely to promote urban green innovation. At the same time, the higher the level of government governance and the better the level of economic development of the development zones, the more it helps to realize the effects of the selection policy. The results of the mechanism test show that the selection of NDZs has a positive impact on urban green innovation through environmental regulation effects, resource allocation effects, and policy amplification effects. Data on development zones are sourced from the China Directory of Development Zones Audit and Announcement (2006) and the China Directory of Development Zones Audit and Announcement (2018 Edition)(http://www.gov.cn/xinwen/2018-03/03/content_5270330.htm); data on patents are sourced from the China Intellectual Property Office (https://www.cnipa.gov.cn/); Other city-level data from China City Statistical Yearbook, China Regional Economic Statistical Yearbook, China Statistical Yearbook (https://data.cnki.net/Yearbook/Navi?type=type&code=A). Our data is collated from the above sources using Python software. 

Funding

Ministry of Education of China, Award: 20YJA790055