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An Individual Choice Model of Energy Mix

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  • Bousquet, Alain
  • Ivaldi, Marc

Abstract

Usually firms operate with a restricted number of energy sources. In the dairy industry, most firms have multi-energy systems allowing them to shift from one energy source to another at almost no cost. Zero expenditures are observed because firms minimize costs and non-negativity constraints on the demand functions are binding. Estimation of demand systems when the probability of observing zero expenditures is not nil has already received attention from econometricians. However, most surveys generally report prices only for the subset of goods actually purchased. The econometrician faces a problem of missing price observations when zero expenditures occur. The originality of our approach is to propose a combined and coherent treatment of both the zero expenditures and missing data. Price equations are added to the demand system and the cost-minimizing mix of energy inputs leads to a simultaneous equation/limited dependent variable model. A general framework is provided in which it is possible to formulate parameter restrictions which guarantee consistency of the cost minimizing model and its relationship to a generalized tobit model with errors in variables. An application to a sample drawn from a survey on firms of the French dairy industry shows the strength of a model which decomposes the choice of energy mix in two parts: a qualitative preference and a quantitative decision. A micro-simulation model gives evidence of the practical use of this study. Nonetheless some theoretical points remain unsolved and should motivate further research.

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Bibliographic Info

Paper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 4.

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Date of creation: 1991
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Publication status: Published in Resource and Energy Economics, n°20, 1998, p.�263-286.
Handle: RePEc:ide:wpaper:1184

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References

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  1. Bryan W. Brown & Mary Beth Walker, 1992. "Stochastic specification in random production models of cost minimizing firms," Working Paper 92-6, Federal Reserve Bank of Atlanta.
  2. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-70, February.
  3. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 21(3), pages 263-285, April.
  4. W. Erwin Diewert & T.J. Wales, 1989. "Flexible Functional Forms and Global Curvature Conditions," NBER Technical Working Papers 0040, National Bureau of Economic Research, Inc.
  5. Gourieroux, C & Laffont, J J & Monfort, A, 1980. "Coherency Conditions in Simultaneous Linear Equation Models with Endogenous Switching Regimes," Econometrica, Econometric Society, vol. 48(3), pages 675-95, April.
  6. Lee, Lung-Fei & Pitt, Mark M., 1987. "Microeconometric models of rationing, imperfect markets, and non-negativity constraints," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 89-110.
  7. Lee, Lung-Fei & Pitt, Mark M, 1986. "Microeconometric Demand Systems with Binding Nonnegativity Constraints: The Dual Approach," Econometrica, Econometric Society, vol. 54(5), pages 1237-42, September.
  8. Wales, T J & Woodland, A D, 1980. "Sample Selectivity and the Estimation of Labor Supply Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(2), pages 437-68, June.
  9. Van Soest, Arthur & Kooreman, Peter, 1990. "Coherency of the indirect translog demand system with binding nonnegativity constraints," Journal of Econometrics, Elsevier, vol. 44(3), pages 391-400, June.
  10. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
  11. Nelson, Forrest D., 1977. "Censored regression models with unobserved, stochastic censoring thresholds," Journal of Econometrics, Elsevier, vol. 6(3), pages 309-327, November.
  12. Bloemen, H.G. & Kapteyn, A.J., 1993. "The joint estimation of a non-linear labour supply function and a wage equation using simulated response probabilites," Open Access publications from Tilburg University urn:nbn:nl:ui:12-364724, Tilburg University.
  13. Newey, Whitney K., 1987. "Efficient estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 36(3), pages 231-250, November.
  14. Flinn, C. & Heckman, J., 1982. "New methods for analyzing structural models of labor force dynamics," Journal of Econometrics, Elsevier, vol. 18(1), pages 115-168, January.
  15. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  16. Florens, Jean-Pierre & Ivaldi, Marc & Larribeau, Sophie, 1996. "Sobolev Estimation of Approximate Regressions," Econometric Theory, Cambridge University Press, vol. 12(05), pages 753-772, December.
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Citations

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Cited by:
  1. Lundmark, Robert, 2008. "Empirical specification of cost reductions associated with accumulated knowledge in the Swedish kraft paper industry," Forest Policy and Economics, Elsevier, vol. 10(7-8), pages 460-466, October.
  2. Tauchmann, H., 2006. "Firing the furnace? An econometric analysis of utilities' fuel choice," Energy Policy, Elsevier, vol. 34(18), pages 3898-3909, December.
  3. Bousquet, Alain & Ladoux, Norbert, 2006. "Flexible versus designated technologies and interfuel substitution," Energy Economics, Elsevier, vol. 28(4), pages 426-443, July.
  4. Alain Bousquet & Raja Chakir & Norbert Ladoux, 2002. "Modeling Corner Solutions with Panel Data: Application to Industrial Energy Demand in France," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C3-2, International Conferences on Panel Data.
  5. Raja Chakir & Alban Thomas, 2003. "Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand," Revue d'économie politique, Dalloz, vol. 0(6), pages 773-799.
  6. Lundmark, Robert & Söderholm, Patrik & Lundmark, Robert, 2003. "Structural changes in Swedish wastepaper demand: a variable cost function approach," Journal of Forest Economics, Elsevier, vol. 9(1), pages 41-63.
  7. Bousquet, Alain & Chakir, Raja & Ladoux, Norbert, 2003. "Modeling Corner Solutions with Panel Data: Application to the Industrial Energy Demand in France," IDEI Working Papers 230, Institut d'Économie Industrielle (IDEI), Toulouse.
  8. Lundmark, Robert, 2005. "A comparison of approaches towards measuring technical change: the case of Swedish newsprint production," Forest Policy and Economics, Elsevier, vol. 7(4), pages 563-577, May.
  9. Arnberg, Soren & Bjorner, Thomas Bue, 2007. "Substitution between energy, capital and labour within industrial companies: A micro panel data analysis," Resource and Energy Economics, Elsevier, vol. 29(2), pages 122-136, May.
  10. MAHENC Philippe, 2008. "Optimal environmental taxation when green alternative is available," LERNA Working Papers 08.04.248, LERNA, University of Toulouse.
  11. Lundmark, Robert & Soderholm, Patrik, 2004. "Estimating and decomposing the rate of technical change in the Swedish pulp and paper industry: A general index approach," International Journal of Production Economics, Elsevier, vol. 91(1), pages 17-35, September.
  12. Roberto Gómez-Calvet & David Conesa & Ana Rosa Gómez-Calvet & Emili Tortosa-Ausina, 2013. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Working Papers 2013/17, Economics Department, Universitat Jaume I, Castellón (Spain).
  13. Dong, Diansheng & Kaiser, Harry M. & Myrland, Oystein, 2003. "Estimation Of Censored La/Aids Model With Endogenous Unit Values," Research Bulletins 122119, Cornell University, Department of Applied Economics and Management.

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