Can IP tribunals increase firm patent applications?—Empirical evidence from China

IF 5.2 1区经济学 Q1 ECONOMICS

中国经济评论 Pub Date : 2024-07-10 DOI:10.1016/j.chieco.2024.102240

Yufei Zhang , Li Wang , Tengjiao He

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Abstract

This paper aims to examine whether property rights protection can enhance firm innovation. To address the endogeneity problem and establish a causal relationship, we adopt the establishment of Intellectual Property Tribunals (IP Tribunals) in China as a natural experiment and employ the Difference-in-Differences (DiD) approach for estimation. By measuring firm innovation via patents and invention patent applications, we find that establishing IP Tribunals can significantly boost firm innovation. Furthermore, we investigate the heterogeneity of our baseline results and discover that privately-owned firms, smaller-sized firms, non-high-tech firms, and firms located in less marketized areas experience a larger improvement in innovation. This finding suggests that this institutional improvement provides greater protection to disadvantaged firms. Breaking regional protectionism and relaxing firm financing constraints are two possible mechanisms through which IP Tribunals can enhance firm innovation. Our results provide new evidence on how institutional change affects economic growth in China.

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知识产权法庭能否增加企业的专利申请？

本文旨在研究产权保护能否促进企业创新。为解决内生性问题并建立因果关系，我们以中国建立知识产权法庭（IP Tribunals）为自然实验，并采用差分法（DiD）进行估计。通过专利和发明专利申请来衡量企业创新，我们发现知识产权法庭的设立能够显著促进企业创新。此外，我们还对基线结果的异质性进行了研究，发现私有企业、规模较小的企业、非高科技企业以及位于市场化程度较低地区的企业在创新方面的进步更大。这一结果表明，制度改进为弱势企业提供了更大的保护。打破地区保护主义和放宽企业融资限制是知识产权法庭促进企业创新的两种可能机制。我们的研究结果为制度变迁如何影响中国经济增长提供了新的证据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.