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Regular and Estimable Inverse Demand Systems: A Distance Function Approach

  • Gary K.K. Wong
  • Keith R. McLaren

    ()

To be useful for realistic policy simulation in an environment of rapid structural change, inverse demand systems must remain regular over substantial variations in quantities. The distance function is a convenient vehicle for generating such systems. While it directly yields Hicksian inverse demand functions, those functions will not usually have an explicit representation in terms of the observable variables. Note however that this problem need not hinder estimation and could be solved by using the numerical inversion estimation approach. This paper develops the formal theory for using distance functions in this context, and demonstrates the operational feasibility of the method.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2002/wp6-02.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 6/02.

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Length: 32 pages
Date of creation: Jul 2002
Date of revision:
Handle: RePEc:msh:ebswps:2002-6
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  1. Cooper, Russel J. & McLaren, Keith R. & Wong, Gary K. K., 2001. "On the empirical exploitation of consumers' profit functions in static analyses," Economics Letters, Elsevier, vol. 72(2), pages 181-187, August.
  2. Pollak, R.A. & Wales, T.J., 1990. "The Likelihood Dominance Criterion: A New Approach To Model Selection," Working Papers 90-10, University of Washington, Department of Economics.
  3. Barten, A. P. & Bettendorf, L. J., 1989. "Price formation of fish : An application of an inverse demand system," European Economic Review, Elsevier, vol. 33(8), pages 1509-1525, October.
  4. Blackorby, C. & Davidson, R. & Schworm, W., 1990. "Implicit Separability: Characterisation And Implications For Consumer Demands," G.R.E.Q.A.M. 90a16, Universite Aix-Marseille III.
  5. James Eales & Catherine Durham & Cathy R. Wessells, 1997. "Generalized Models of Japanese Demand for Fish," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1153-1163.
  6. Holt, Matthew T., 2002. "Inverse demand systems and choice of functional form," European Economic Review, Elsevier, vol. 46(1), pages 117-142, January.
  7. Beach, Charles M & MacKinnon, James G, 1979. "Maximum Likelihood Estimation of Singular Equation Systems with Autoregressive Disturbances," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(2), pages 459-64, June.
  8. Richard Blundell & Robin, J M, 1995. "Latent separability: grouping goods without weak separability," IFS Working Papers W95/09, Institute for Fiscal Studies.
  9. Perroni, C. & Rutherford, T., 1991. "Regular Flexibility of Nested CES Functions," Working Papers 91145, Wilfrid Laurier University, Department of Economics.
  10. Robert H. Beach & Matthew T. Holt, 2001. "Incorporating Quadratic Scale Curves in Inverse Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 230-245.
  11. Eales, James S. & Unnevehr, Laurian J., 1994. "The inverse almost ideal demand system," European Economic Review, Elsevier, vol. 38(1), pages 101-115, January.
  12. Selvanathan, Saroja, 1991. "The Reliability of ML Estimators of Systems of Demand Equations: Evidence from OECD Countries," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 346-53, May.
  13. Richard C. Bishop & Matthew T. Holt, 2002. "A semiflexible normalized quadratic inverse demand system: an application to the price formation of fish," Empirical Economics, Springer, vol. 27(1), pages 23-47.
  14. Brown, Mark G & Lee, Jonq-Ying & Seale, James L, Jr, 1995. "A Family of Inverse Demand Systems and Choice of Functional Form," Empirical Economics, Springer, vol. 20(3), pages 519-30.
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