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Estimating Risk Effects In Chinese Foodgrain Production

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  • G. H. Wan
  • J. R. Anderson

Abstract

Given the importance of Chinese foodgrain production both in China and in the world food market, it is useful to explore the sources of the increased variabilities of China's foodgrain production (Stone and Zhong, 1989). A production function with composite error structure and a heteroscedastic disturbance is applied to cross‐section and time‐series data from China. The function provides information on the contributions of inputs to production variance and therefore on risk. It is found that production variance is positively related to sown area, chemical fertiliser and irrigation, and is negatively related to electricity use. However, most of the estimates determining the marginal risk effects lack statistical significance. This suggests that the measured controllable factors do not contribute very significantly to Chinese foodgrain production variability.

Suggested Citation

  • G. H. Wan & J. R. Anderson, 1990. "Estimating Risk Effects In Chinese Foodgrain Production," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(1), pages 85-93, January.
    • Handle: RePEc:bla:jageco:v:41:y:1990:i:1:p:85-93
    DOI: 10.1111/j.1477-9552.1990.tb00621.x
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    References listed on IDEAS

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    1. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    2. Anthony M. Tang, 1982. "China as a Factor in the World Food Situation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 64(2), pages 323-331.
    3. Peter B. R. Hazell, 1984. "Sources of Increased Instability in Indian and U.S. Cereal Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(3), pages 302-311.
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    Cited by:

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    2. Cornelis Gardebroek & María Daniela Chavez & Alfons Oude Lansink, 2010. "Analysing Production Technology and Risk in Organic and Conventional Dutch Arable Farming using Panel Data," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 60-75, February.
    3. Asche, Frank & Tveteras, Ragnar, 1999. "Modeling Production Risk With A Two-Step Procedure," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(2), pages 1-16, December.
    4. Alain Carpentier & . European Association of Environmental And Resource Economists, 1994. "Some issues on pesticide ban : the example of the French crop sector," Post-Print hal-01947506, HAL.
    5. Carter, Colin A. & Li, Xianghong, 1999. "Economic Reform And The Changing Pattern Of China'S Agricultural Trade," Working Papers 11957, University of California, Davis, Department of Agricultural and Resource Economics.
    6. Alexandre Gohin & Herve Guyomard & Fabrice Levert & . Ministère de L'Aménagement Du Territoire Et de L'Environnement, Direction Générale de L'Administration Et Du Développement, Paris (fra) & Francois, 2000. "Economic impacts of reducing agricultural use of mineral fertilizer in France : a general equilibrium analysis [Impacts économiques d'une réduction des utilisations agricoles des engrais minéraux e," Post-Print hal-02840460, HAL.
    7. Carter, Colin A. & Zhang, Bin, 1998. "The Weather Factor and Variability in China's Grain Supply," Journal of Comparative Economics, Elsevier, vol. 26(3), pages 529-543, September.
    8. Ligeon, Carel & Jolly, Curtis M. & Bencheva, Nelly & Delikostadinov, Stanko & Puppala, Naveen, 2009. "Production risks in Bulgarian peanut production," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 9(1), pages 1-8.
    9. Lien, Gudbrand & Kumbhakar, Subal C. & Mishra, Ashok K. & Hardaker, J. Brian, 2022. "Does risk management affect productivity of organic rice farmers in India? Evidence from a semiparametric production model," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1392-1402.

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