Can data elements enhance urban innovation? Evidence from China

IF 5.2 1区经济学 Q1 ECONOMICS

中国经济评论 Pub Date : 2024-11-17 DOI:10.1016/j.chieco.2024.102307

Changbiao Zhong , Chao Zhang

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Abstract

Empowering urban innovation is particularly crucial in the new development paradigm. The capacity of data elements to drive urban innovation is a significant issue that warrants exploration. Based on the panel data of Chinese cities from 2011 to 2021, we empirically estimate the effect of data elements on urban innovation using a two-way fixed-effects panel model and analyze the influencing mechanism using a mediated-effects model. The study finds that data elements significantly enhance urban innovation capacity, and this conclusion remains valid after a series of rigorous tests for robustness. The results of the mechanism analysis indicate that data elements can boost urban innovation capacity by promoting the integration of manufacturing and service industries, increasing urban entrepreneurial activity, and enhancing urban digital finance. Heterogeneity analysis reveals that data elements have a more significant impact on enhancing the innovation capacity of cities in eastern China, high-level cities, and cities with high levels of science and education. The findings of this study provide valuable guidance for formulating policies aimed at promoting the data elements market and enhancing urban innovation vitality.

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数据要素能否促进城市创新？来自中国的证据

在新的发展模式中，增强城市创新能力尤为重要。数据要素推动城市创新的能力是一个值得探讨的重要问题。基于 2011-2021 年中国城市面板数据，我们采用双向固定效应面板模型实证估计了数据要素对城市创新的影响，并采用中介效应模型分析了影响机制。研究发现，数据要素能显著提升城市创新能力，这一结论在经过一系列严格的稳健性检验后仍然有效。机制分析的结果表明，数据要素可以通过促进制造业与服务业的融合、提高城市创业活动以及加强城市数字金融来提升城市创新能力。异质性分析表明，数据要素对提升中国东部城市、高水平城市和高科教水平城市的创新能力具有更显著的影响。本研究的结论为制定促进数据要素市场发展、增强城市创新活力的政策提供了有价值的指导。

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来源期刊

中国经济评论 ECONOMICS-

CiteScore

10.60

自引率

4.40%

发文量

380

期刊介绍： The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.