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Three parts natural, seven parts man-made: Bayesian analysis of China's Great Leap Forward demographic disaster

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  • Houser, Daniel
  • Sands, Barbara
  • Xiao, Erte

Abstract

The millions of deaths that occurred during China's great famine of 1959-1961 were the result of one of the world's greatest civil demographic disasters. Two primary hypotheses have been advanced to explain the famine. One is that China experienced three consecutive years of bad weather while the other is that national policies were wrong in that they reduced and misallocated agricultural production. The relative importance of these two factors to the famine remains controversial among China scholars. This paper uses provincial-level demographic panel data and a Bayesian empirical approach in an effort to distinguish the relative importance of weather and national policy on China's great demographic disaster. Consistent with the qualitative literature in this area, we find that national policy played an overall more important role in the famine than weather. However, we provide new quantitative evidence that weather was also an important factor, particularly in those provinces that experienced excessively wet conditions.

Suggested Citation

  • Houser, Daniel & Sands, Barbara & Xiao, Erte, 2009. "Three parts natural, seven parts man-made: Bayesian analysis of China's Great Leap Forward demographic disaster," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 148-159, February.
  • Handle: RePEc:eee:jeborg:v:69:y:2009:i:2:p:148-159
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    References listed on IDEAS

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    1. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, May.
    2. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
    3. Houser, Daniel & Bechara, Antoine & Keane, Michael & McCabe, Kevin & Smith, Vernon, 2005. "Identifying individual differences: An algorithm with application to Phineas Gage," Games and Economic Behavior, Elsevier, vol. 52(2), pages 373-385, August.
    4. Houser, Daniel, 2003. "Bayesian analysis of a dynamic stochastic model of labor supply and saving," Journal of Econometrics, Elsevier, vol. 113(2), pages 289-335, April.
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    Citations

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    Cited by:

    1. Cormac Ó Gráda, 2007. "The ripple that drowns? Twentieth-century famines in China and India as economic history," Working Papers 200719, School of Economics, University College Dublin.
    2. Cormac Ó Gráda, 2007. "Making Famine History," Journal of Economic Literature, American Economic Association, vol. 45(1), pages 5-38, March.
    3. Matthieu CLEMENT (GREThA UMR CNRS 5113), 2010. "Food Availability and Food Entitlements during the Chinese Great Leap Forward Famine: A dynamic panel data analysis (In French)," Cahiers du GREThA 2010-03, Groupe de Recherche en Economie Théorique et Appliquée.
    4. Gooch, Elizabeth, 2017. "Estimating the Long-Term Impact of the Great Chinese Famine (1959–61) on Modern China," World Development, Elsevier, vol. 89(C), pages 140-151.

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