Centralized procurement authority and corporate innovation

IF 5.5 1区经济学 Q1 ECONOMICS

中国经济评论 Pub Date : 2025-09-09 DOI:10.1016/j.chieco.2025.102544

Xiao Jia , Xiaoxi Li , Boluo Liu , Nan Shao

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引用次数: 0

Abstract

Leveraging the establishment of the National Healthcare Security Administration (NHSA) in China as an external policy change, we demonstrate that the government's centralized control over drug procurement platform and insurance coverage catalog significantly enhances the innovation activities of pharmaceutical companies. By manually adjusting for expenditures of passing consistency evaluation, we accurately measure effective research and development inputs. Further tests reveal two key mechanisms driving our result: first, NHSA policies negatively impact firms' financial performance and stock returns, leading affected firms to invest more in innovation; second, increased competition further incentivizes innovation, especially among firms that lose more market shares. Importantly, companies with stronger internal resources are more successful in translating these pressures into effective innovation. Our results show that the NHSA not only redefines competitive dynamics but also acts as a powerful catalyst for pharmaceutical innovation, contributing to the understanding of the policy implications of centralized public procurement.

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集中采购权与企业创新

我们利用中国国家医疗保障局的成立作为外部政策变化，证明政府对药品采购平台和保险覆盖目录的集中控制显著增强了制药公司的创新活动。通过手动调整通过一致性评估的支出，我们准确地衡量有效的研发投入。进一步的检验揭示了驱动我们的结果的两个关键机制：第一，国家保障金政策对企业的财务绩效和股票收益产生负向影响，导致受影响的企业更多地投资于创新；其次，竞争的加剧进一步激励了创新，尤其是那些失去更多市场份额的公司。重要的是，拥有更强大内部资源的公司更能成功地将这些压力转化为有效的创新。我们的研究结果表明，NHSA不仅重新定义了竞争动态，而且还作为制药创新的强大催化剂，有助于理解集中公共采购的政策含义。

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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.