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Cross‐Border Data Flow and Knowledge Diffusion: Evidence From China

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Review of International Economics

Published online on

Abstract

["Review of International Economics, EarlyView. ", "\nABSTRACT\nCross‐border data flows constitute a core mechanism for international knowledge spillovers in the digital era, while stringent data protection regulations, notably the European Union's GDPR, may impede knowledge diffusion for innovation. Since existing research has not systematically established the causal relationship and mechanisms between cross‐border data flows and knowledge diffusion, this paper takes the 2018 GDPR implementation as a policy shock, integrates data from the Chinese patent database, Google Patents citation data, and Orbis enterprise database from 2010 to 2020 to construct a firm‐country‐year panel, and uses a DID approach to identify the causal effects of data protection regulation on international knowledge spillovers on both extensive and intensive margins. We find GDPR significantly impedes cross‐border knowledge flows: on the extensive margin, Chinese firms' probability of citing EU patents fell by 0.015 (LPM) post‐implementation; on the intensive margin, citation intensity between enterprise‐country pairs declined by 23% (PPML). Further analysis shows GDPR hinders knowledge spillovers by raising firms' knowledge acquisition and utilization costs, via reduced information accessibility, disrupted commercial cooperation, tacit knowledge diffusion barriers, and compliance‐related resource crowding‐out and procedural frictions. In addition, alternative information channels like international trade can effectively mitigate GDPR's negative impact. This study enriches the theoretical framework of data protection policies' economic effects while providing empirical evidence for balancing privacy protection and knowledge sharing in global data governance.\n"]