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Exploring Alternatives For Estimating Systems Of Equations With Multiple Censored Variables: Farm Output Supply And Input Demand

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  • Arias, Carlos
  • Perali, Carlo Federico

Abstract

This paper explores two alternatives for estimating systems of equations with multiple censored variables: Maximum Simulated Likelihood and a two-step technique that seems to be well suited for large samples. The empirical part of the paper estimates a system of cost, cost shares and revenue shares equations of Italian farms using both approaches.

Suggested Citation

  • Arias, Carlos & Perali, Carlo Federico, 1999. "Exploring Alternatives For Estimating Systems Of Equations With Multiple Censored Variables: Farm Output Supply And Input Demand," 1999 Annual meeting, August 8-11, Nashville, TN 21591, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea99:21591
    DOI: 10.22004/ag.econ.21591
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    References listed on IDEAS

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    1. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
    2. Phaneuf, Daniel J., 1999. "A Dual Approach to Modeling Corner Solutions in Recreation Demand," Journal of Environmental Economics and Management, Elsevier, vol. 37(1), pages 85-105, January.
    3. Stern, Steven, 1992. "A Method for Smoothing Simulated Moments of Discrete Probabilities in Multinomial Probit Models," Econometrica, Econometric Society, vol. 60(4), pages 943-952, July.
    4. Antonella Caiumi & Federico Perali, 1997. "Female Labor Force Participation: A Comparison between Urban and Rural Families," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 595-601.
    5. Arthur Lewbel, 1985. "A Unified Approach to Incorporating Demographic or Other Effects into Demand Systems," Review of Economic Studies, Oxford University Press, vol. 52(1), pages 1-18.
    6. Blundell, Richard & Pashardes, Panos & Weber, Guglielmo, 1993. "What Do We Learn About Consumer Demand Patterns from Micro Data?," American Economic Review, American Economic Association, vol. 83(3), pages 570-597, June.
    7. Browning, Martin & Meghir, Costas, 1991. "The Effects of Male and Female Labor Supply on Commodity Demands," Econometrica, Econometric Society, vol. 59(4), pages 925-951, July.
    8. Huffman, Wallace E., 1988. "An Econometric Methodology for Multiple-Output Agricultural Technology: An Application of Endogenous Switching Models," Staff General Research Papers Archive 11003, Iowa State University, Department of Economics.
    9. Lee, Lung-Fei & Pitt, Mark M, 1986. "Microeconometric Demand Systems with Binding Nonnegativity Constraints: The Dual Approach," Econometrica, Econometric Society, vol. 54(5), pages 1237-1242, September.
    10. Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996. "Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
    11. Lee, Lung-Fei & Pitt, Mark M., 1984. "Microeconometric Models of Consumer and Producer Demand with Limited Dependent Variables," Bulletins 7495, University of Minnesota, Economic Development Center.
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    Cited by:

    1. Sckokai, Paolo, 2001. "The Common Agricultural Policy In Econometric Models," Working Papers 14800, National Institute of Agricultural Economics, Italy - INEA, Osservatorio Sulle Politiche Agricole dell'UE.

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