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Quid Pro Quo, Knowledge Spillover and Industrial Upgrading

Author

Listed:
  • Jie Bai

    (Center for International Development at Harvard University)

  • Panle Barwick
  • Shengmao Cao
  • Shanjun Li

Abstract

Are quid pro quo (technology for market access) policies effective in facilitating knowledge spillover to developing countries? We study this question in the context of the Chinese automobile industry where foreign firms are required to set up joint ventures with domestic firms in return for market access. Using a unique dataset of detailed quality measures along multiple dimensions of vehicle performance, we document empirical patterns consistent with knowledge spillovers through both ownership affiliation and geographical proximity: joint ventures and Chinese domestic firms with ownership or location linkage tend to specialize in similar quality dimensions. The identification primarily relies on within-product variation across quality dimensions and the results are robust to a variety of specifications. The pattern is not driven by endogenous joint-venture network formation, overlapping customer base, or learning by doing considerations. Leveraging additional micro datasets on part suppliers and worker flow, we document that supplier network and labor mobility are important channels in mediating knowledge spillovers. However, these channels are not tied to ownership affiliations. Finally, we calibrate a simple learning model and conduct policy counterfactuals to examine the role of quid pro quo. Our findings show that ownership affiliation facilitates learning but quality improvement is primarily driven by the other mechanisms.

Suggested Citation

  • Jie Bai & Panle Barwick & Shengmao Cao & Shanjun Li, 2019. "Quid Pro Quo, Knowledge Spillover and Industrial Upgrading," CID Working Papers 368, Center for International Development at Harvard University.
  • Handle: RePEc:cid:wpfacu:368
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    File URL: https://growthlab.cid.harvard.edu/files/growthlab/files/2019-11-cid-wp-368-quid-pro-quo.pdf
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    References listed on IDEAS

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    3. Youming Liu & Shanjun Li & Caixia Shen, 2020. "The Dynamic Efficiency in Resource Allocation: Evidence from Vehicle License Lotteries in Beijing," NBER Working Papers 26904, National Bureau of Economic Research, Inc.

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    Knowledge spillover;

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