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Using Panel Data to Estimate Risk Effects in Seemingly Unrelated Production Functions

Author

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  • Wan, Guang H
  • Griffiths, William E
  • Anderson, Jock R

Abstract

In this paper, production functions in the form of seemingly unrelated regressions (SUR) with errors that are heteroscedastic and that contain cross-section and time components are proposed. These functions are distinguished from others in that they allow the risks (indicated by variances) of outputs to change in any direction in response to input changes. The SUR are then applied in the analysis of cross-section time-series data for rice, wheat, and maize production in China.

Suggested Citation

  • Wan, Guang H & Griffiths, William E & Anderson, Jock R, 1992. "Using Panel Data to Estimate Risk Effects in Seemingly Unrelated Production Functions," Empirical Economics, Springer, vol. 17(1), pages 35-49.
    • Handle: RePEc:spr:empeco:v:17:y:1992:i:1:p:35-49
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    Cited by:

    1. Do, Huu-Luat & Dang Thuy, Truong, 2022. "Productivity response and production risk: A study of mangrove forest effects in aquaculture in the Mekong River Delta," Ecological Economics, Elsevier, vol. 194(C).
    2. 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.
    3. Alain Carpentier & Robert D. Weaver, 1995. "The contribution of pesticides to agricultural production : a reconsideration [Le rôle des pesticides dans la production agricole : nouvelle approche]," Post-Print hal-02850939, HAL.
    4. Nolan, Elizabeth & Santos, Paulo, 2012. "Insurance premiums and GM traits," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125942, International Association of Agricultural Economists.
    5. Tai-Hsin Huang & Tong-Liang Kao, 2006. "Joint estimation of technical efficiency and production risk for multi-output banks under a panel data cost frontier model," Journal of Productivity Analysis, Springer, vol. 26(1), pages 87-102, August.
    6. Alain Carpentier & Robert D. Weaver, 1996. "Assessment of producers' attitude toward risk and information using panel data : the example of pesticide use in the French crop sector," Post-Print hal-01931607, HAL.
    7. Ragnar Tveteras & Ola Flaten & Gudbrand Lien, 2011. "Production risk in multi-output industries: estimates from Norwegian dairy farms," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4403-4414.
    8. Bin Zhou & Qinfeng Xu & Jinhong You, 2011. "Efficient estimation for error component seemingly unrelated nonparametric regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 121-138, January.
    9. Ragnar Tveteros, 1999. "Production Risk and Productivity Growth: Some Findings for Norwegian Salmon Aquaculture," Journal of Productivity Analysis, Springer, vol. 12(2), pages 161-179, September.
    10. Jinhong You & Alan Wan & Shu Liu & Yong Zhou, 2015. "A varying-coefficient approach to estimating multi-level clustered data models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 417-440, June.
    11. Badi Baltagi & Alain Pirotte, 2011. "Seemingly unrelated regressions with spatial error components," Empirical Economics, Springer, vol. 40(1), pages 5-49, February.
    12. Ragner Tveterås & G. H. Wan, 2000. "Flexible panel data models for risky production technologies with an application to salmon aquaculture," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 367-389.
    13. Tai-Hsin Huang, 2004. "Empirical estimation of production risk using a cost function with panel data," Applied Economics Letters, Taylor & Francis Journals, vol. 11(5), pages 297-301.
    14. Erik Biørn & Kjersti-Gro Lindquist & Terje Skjerpen, 2002. "Heterogeneity in Returns to Scale: A Random Coefficient Analysis with Unbalanced Panel Data," Journal of Productivity Analysis, Springer, vol. 18(1), pages 39-57, July.
    15. Tomson Ogwang, 2022. "The regression approach to the measurement and decomposition of the multidimensional Watts poverty index," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 951-973, December.

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