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Weak Axiom of Cost Dominance: A Nonparametric Test of Cost Efficiency Without Input Quantity Data

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  • Subhash Ray

Abstract

Varian's Weak Axiom of Cost Minimization provides a nonparametric test of cost minimization, which can be applied only when both input price and quantity data are available for individual firms. In this paper we propose a Weak Axiom of Cost Dominance (WACD), which serves as the basis of an alternative test of cost-minimization applicable in situations where input quantity data are missing. Unlike a previous test developed by Diewert and Parkan, the proposed test does identify individual firms that violate the assumption of cost-minimizing behavior. It also provides an upper bound of the cost-efficiency of any observed firm. The test procedure is shown to be equivalent to applying dominance analysis using normalized input prices with reference to the Cost-indirect technology. The proposed method is applied to Nerlove's electrical utility data. The nonparametric results are also compared with parametric efficiency levels computed from a stochastic frontier cost function. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Subhash Ray, 1997. "Weak Axiom of Cost Dominance: A Nonparametric Test of Cost Efficiency Without Input Quantity Data," Journal of Productivity Analysis, Springer, vol. 8(2), pages 151-165, May.
  • Handle: RePEc:kap:jproda:v:8:y:1997:i:2:p:151-165
    DOI: 10.1023/A:1007747407212
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    References listed on IDEAS

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    1. Henry Tulkens, 1993. "On FDH efficiency analysis: Some methodological issues and applications to retail banking, courts, and urban transit," Journal of Productivity Analysis, Springer, vol. 4(1), pages 183-210, June.
    2. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    3. Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-frontier measures of efficiency, progress and regress for time series data," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 83-97, April.
    4. Hanoch, Giora & Rothschild, Michael, 1972. "Testing the Assumptions of Production Theory: A Nonparametric Approach," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 256-275, March-Apr.
    5. Varian, Hal R, 1984. "The Nonparametric Approach to Production Analysis," Econometrica, Econometric Society, vol. 52(3), pages 579-597, May.
    6. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. Toshiyuki Sueyoshi, 1999. "DEA Duality on Returns to Scale (RTS) in Production and Cost Analyses: An Occurrence of Multiple Solutions and Differences Between Production-Based and Cost-Based RTS Estimates," Management Science, INFORMS, vol. 45(11), pages 1593-1608, November.
    2. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "The measurement of returns to scale under a simultaneous occurrence of multiple solutions in a reference set and a supporting hyperplane," European Journal of Operational Research, Elsevier, vol. 181(2), pages 549-570, September.
    3. repec:wsi:wsbook:6875 is not listed on IDEAS
    4. Paul Oslington, 2012. "General Equilibrium: Theory and Evidence," The Economic Record, The Economic Society of Australia, vol. 88(282), pages 446-448, September.

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