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A World Factory in Global Production Chains: Estimating Imported Value Added in Chinese Exports


  • Koopman, Robert
  • Wang, Zhi
  • Wei, Shang-Jin


The rise of the People’s Republic of China (PRC) in world trade has brought both benefits and anxiety to other economies. For many policy questions, it is crucial to know the extent of foreign value added (FVA) in exports. We review a general formula in Koopman, Wang and Wei (2008) for computing domestic and foreign contents when processing exports are pervasive. In addition, we develop another formula for slicing up foreign content to allocate it among key individual economy’s supply chains, including sourcing from Japan and the United States. By our estimation, the share of foreign content in exports by the PRC is about 50%. There are also interesting variations across sectors. Those sectors that are likely labeled as relatively sophisticated such as electronic devices have particularly high foreign content (about 80%). By our estimation, Japan; the United States; Hong Kong, China; and the European Union are the major sources of foreign content in the PRC’s exports of computers and consumer electronics, two of its largest and fastest growing export categories.

Suggested Citation

  • Koopman, Robert & Wang, Zhi & Wei, Shang-Jin, 2009. "A World Factory in Global Production Chains: Estimating Imported Value Added in Chinese Exports," CEPR Discussion Papers 7430, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:7430

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    References listed on IDEAS

    1. Ulf Axelson & Sandeep Baliga, 2009. "Liquidity and Manipulation of Executive Compensation Schemes," Review of Financial Studies, Society for Financial Studies, vol. 22(10), pages 3907-3939, October.
    2. Bergstresser, Daniel & Philippon, Thomas, 2006. "CEO incentives and earnings management," Journal of Financial Economics, Elsevier, vol. 80(3), pages 511-529, June.
    3. Shane A. Johnson & Harley E. Ryan & Yisong S. Tian, 2009. "Managerial Incentives and Corporate Fraud: The Sources of Incentives Matter," Review of Finance, European Finance Association, vol. 13(1), pages 115-145.
    4. Maug, Ernst & Dittmann, Ingolf, 2007. "Lower salaries and no options : the optimal structure of executive pay
      [Lower salaries and no options? On the optimal structure of executive pay]
      ," Papers 07-41, Sonderforschungsbreich 504.
    5. Patrick Bolton & Jose Scheinkman & Wei Xiong, 2006. "Pay for Short-Term Performance: Executive Compensation in Speculative Markets," NBER Working Papers 12107, National Bureau of Economic Research, Inc.
    6. Simi Kedia & Thomas Philippon, 2009. "The Economics of Fraudulent Accounting," Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2169-2199, June.
    7. Holmstrom, Bengt & Tirole, Jean, 1993. "Market Liquidity and Performance Monitoring," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 678-709, August.
    8. Lin Peng & Ailsa Röell, 2008. "Executive pay and shareholder litigation," Review of Finance, European Finance Association, vol. 12(1), pages 141-184.
    9. Bizjak, John M. & Brickley, James A. & Coles, Jeffrey L., 1993. "Stock-based incentive compensation and investment behavior," Journal of Accounting and Economics, Elsevier, vol. 16(1-3), pages 349-372, April.
    10. Efraim Benmelech & Eugene Kandel & Pietro Veronesi, 2010. "Stock-Based Compensation and CEO (Dis)Incentives," The Quarterly Journal of Economics, Oxford University Press, vol. 125(4), pages 1769-1820.
    11. Goldman, Eitan & Slezak, Steve L., 2006. "An equilibrium model of incentive contracts in the presence of information manipulation," Journal of Financial Economics, Elsevier, vol. 80(3), pages 603-626, June.
    12. Ingolf Dittmann & Ernst Maug, 2007. "Lower Salaries and No Options? On the Optimal Structure of Executive Pay," Journal of Finance, American Finance Association, vol. 62(1), pages 303-343, February.
    13. Jensen, Michael C & Murphy, Kevin J, 1990. "Performance Pay and Top-Management Incentives," Journal of Political Economy, University of Chicago Press, vol. 98(2), pages 225-264, April.
    14. Alex Edmans & Xavier Gabaix & Augustin Landier, 2009. "A Multiplicative Model of Optimal CEO Incentives in Market Equilibrium," Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 4881-4917, December.
    15. Narayanan, M P, 1985. "Observability and the Payback Criterion," The Journal of Business, University of Chicago Press, vol. 58(3), pages 309-323, July.
    16. Lin Peng & Ailsa Roell, 2008. "Manipulation and Equity-Based Compensation," American Economic Review, American Economic Association, vol. 98(2), pages 285-290, May.
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    Cited by:

    1. Shahid Yusuf, 2012. "From Technological Catch-up to Innovation : The Future of China’s GDP Growth," World Bank Other Operational Studies 12781, The World Bank.
    2. Robert Koopman & William Powers & Zhi Wang & Shang-Jin Wei, 2010. "Give Credit Where Credit Is Due: Tracing Value Added in Global Production Chains," NBER Working Papers 16426, National Bureau of Economic Research, Inc.

    More about this item


    domestic content; foreign value added; processing trade;

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • F1 - International Economics - - Trade

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