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Finite sample inference methods for dynamic energy demand models


  • Jean-Thomas Bernard

    (Holder of the Chair on the Economics of Electric Energy; Groupe de recherche en économie de l'énergie, de l'environnement et des ressources naturelles [GREEN], Université Laval. Mailing address: Pavillon J.-A.-De Sève, Ste-Foy, Québec, Canada, G1K 7P4)

  • Nadhem Idoudi

    (Conseiller Coûts et caractéristiques de la consommation, Direction des Affaires réglementaires et tarifaires, Hydro-Québec Distribution, and Groupe de recherche en économie de l'énergie, de l'environnement et des ressources naturelles [GREEN], Université Laval. Mailing address: 75, boul. René-Lévesque ouest, 2e étage, Montréal, (Québec) H2Z 1A4)

  • Lynda Khalaf

    (Holder of the Canada Research Chair in Environment; Centre interuniversitaire de recherche en économie quantitative (CIREQ) and Economics Department, Carleton University, Loeb Building 1125 Colonel By Drive, Ottawa, Ont., Canada K1S 5B6)

  • Clément Yélou

    (Département d'économique, Groupe de recherché en économie de l'énergie, de l'environement et des ressources naturelles [GREEN], and Centre de recherche en économie agroalimentaire (CRÉA), Université Laval. Jean-Talon Building, B-5, Statistics Canada, 170 Tunney's Pasture Driveway, Ottawa ON K1A 0T6)


This paper considers finite sample motivated inference methods in dynamic energy demand models, in which case commonly used econometric methods remain asymptotic. We focus on structural stability, and on exact confidence set estimation of elasticities. We account for intractable and nuisance parameter dependant distributions through Monte Carlo test procedures. For long-run elasticities which depend on parameter ratios, we assess available asymptotic and exact methods with Fieller based alternatives. Fieller based and exact methods invert approximate and exact relevant test criteria (respectively) and may lead to unbounded set estimates. Our empirical results underscore the importance of using identification-robust inference methods. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Jean-Thomas Bernard & Nadhem Idoudi & Lynda Khalaf & Clément Yélou, 2007. "Finite sample inference methods for dynamic energy demand models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1211-1226.
  • Handle: RePEc:jae:japmet:v:22:y:2007:i:7:p:1211-1226
    DOI: 10.1002/jae.996

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    References listed on IDEAS

    1. Kiviet, Jan F. & Dufour, Jean-Marie, 1997. "Exact tests in single equation autoregressive distributed lag models," Journal of Econometrics, Elsevier, vol. 80(2), pages 325-353, October.
    2. Jean-Marie Dufour, 2003. "Identification, weak instruments, and statistical inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 36(4), pages 767-808, November.
    3. McAvinchey, Ian D. & Yannopoulos, Andreas, 2003. "Stationarity, structural change and specification in a demand system: the case of energy," Energy Economics, Elsevier, vol. 25(1), pages 65-92, January.
    4. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    5. Dunstan, Roger H. & Schmidt, Ronald H., 1988. "Structural changes in residential energy demand," Energy Economics, Elsevier, vol. 10(3), pages 206-212, July.
    6. Savin, N.E., 1984. "Multiple hypothesis testing," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 14, pages 827-879 Elsevier.
    7. James M. Griffin & Craig T. Schulman, 2005. "Price Asymmetry in Energy Demand Models: A Proxy for Energy-Saving Technical Change?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-22.
    8. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    9. Dufour, Jean-Marie & Kiviet, Jan F., 1996. "Exact tests for structural change in first-order dynamic models," Journal of Econometrics, Elsevier, vol. 70(1), pages 39-68, January.
    10. Dufour, Jean-Marie, 1989. "Nonlinear Hypotheses, Inequality Restrictions, and Non-nested Hypotheses: Exact Simultaneous Tests in Linear Regressions," Econometrica, Econometric Society, vol. 57(2), pages 335-355, March.
    11. Dermot Gately & Hiliard G. Huntington, 2002. "The Asymmetric Effects of Changes in Price and Income on Energy and Oil Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 19-55.
    12. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    13. Jean-Marie Dufour & Jan F. Kiviet, 1998. "Exact Inference Methods for First-Order Autoregressive Distributed Lag Models," Econometrica, Econometric Society, vol. 66(1), pages 79-104, January.
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    Cited by:

    1. Bernard, Jean-Thomas & Idoudi, Nadhem & Khalaf, Lynda & Yelou, Clement, 2007. "Finite sample multivariate structural change tests with application to energy demand models," Journal of Econometrics, Elsevier, vol. 141(2), pages 1219-1244, December.
    2. Christian Murray & Juan Urquiza, 2017. "Do Estimated Taylor Rules Suffer from Weak Identification?," Working Papers 2017-274-09, Department of Economics, University of Houston.
    3. J.G. Hirschberg & J. N. Lye, 2007. "Providing Intuition to the Fieller Method with Two Geometric Representations using STATA and Eviews," Department of Economics - Working Papers Series 992, The University of Melbourne.
    4. Jean-Thomas Bernard & Michael Gavin & Lynda Khalaf & Marcel Voia, 2011. "The Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification," Cahiers de recherche CREATE 2011-4, CREATE.
    5. Jean-Thomas Bernard & Michael Gavin & Lynda Khalaf & Marcel Voia, 2015. "Environmental Kuznets Curve: Tipping Points, Uncertainty and Weak Identification," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(2), pages 285-315, February.
    6. Hirschberg, J.G. & Lye, J.N. & Slottje, D.J., 2008. "Inferential methods for elasticity estimates," Journal of Econometrics, Elsevier, vol. 147(2), pages 299-315, December.
    7. Jean-Thomas Bernard & Ba Chu & Lynda Khalaf & Marcel-Cristian Voia, 2017. "Non-standard Confidence Sets for Ratios and Tipping Points with Applications to Dynamic Panel Data," Carleton Economic Papers 17-05, Carleton University, Department of Economics.
    8. J. G. Hirschberg, J. N. Lye & D. J. Slottje, 2008. "Confidence Intervals for Estimates of Elasticities," Department of Economics - Working Papers Series 1053, The University of Melbourne.
    9. Gatta, Valerio & Marcucci, Edoardo & Scaccia, Luisa, 2015. "On finite sample performance of confidence intervals methods for willingness to pay measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 169-192.
    10. Hirschberg, J.G. & Lye, J.N., 2010. "Two geometric representations of confidence intervals for ratios of linear combinations of regression parameters: An application to the NAIRU," Economics Letters, Elsevier, vol. 108(1), pages 73-76, July.

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