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Optimal Chinese Agricultural Trade Patterns under the Laws of Comparative Advantage

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  • Hayes, Dermot J.
  • Fuller, Frank H.

Abstract

Using Chinese agricultural and resources data and an adaptation of the Heckscher-Ohlin-Vanek (HOV) international trade model, this paper projects what Chinese trade, production, and consumption patterns would be if China allowed the laws of comparative advantage to direct production and trade decisions. This work is motivated by the fact that current production and consumption patterns in China are likely very different from those that would exist under complete liberalization. Any econometric-based model must use current production patterns as a base against which policy changes can be evaluated; however, the greater role of market forces following trade liberalization may render the conclusions of the econometric model invalid.

Suggested Citation

  • Hayes, Dermot J. & Fuller, Frank H., 1999. "Optimal Chinese Agricultural Trade Patterns under the Laws of Comparative Advantage," Papers 18467, Hebrew University of Jerusalem Archive.
    • Handle: RePEc:ags:hebarc:18467
    DOI: 10.22004/ag.econ.18467
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    References listed on IDEAS

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    1. Dermot J. Hayes & Alexander Kumi & S.R. Johnson, 1995. "Trade Impacts of Soviet Reform: A Heckscher-Ohlin-Vanek Approach," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 17(2), pages 131-145.
    2. Bowen, Harry P & Leamer, Edward E & Sveikauskas, Leo, 1987. "Multicountry, Multifactor Tests of the Factor Abundance Theory," American Economic Review, American Economic Association, vol. 77(5), pages 791-809, December.
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    Cited by:

    1. Cheng, Fuzhi, 2008. "China: Shadow WTO agricultural domestic support notifications," IFPRI discussion papers 793, International Food Policy Research Institute (IFPRI).
    2. Nin, Alejandro & Hertel, Thomas W. & Foster, Kenneth & Rae, Allan, 2004. "Productivity growth, catching-up and uncertainty in China's meat trade," Agricultural Economics, Blackwell, vol. 31(1), pages 1-16, July.

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