Les déterminants de la demande agrégée d'électricité en France
Mots-clés :
demande d’électricité, cointégration, modèle autorégressif à retards échelonnésRésumé
Cet article a pour objectif premier d'étudier la demande globale d'électricité à court et à long terme pour la France sur la période 1990-T1 à2015-T3. Il met en oeuvre la méthodologie économétrique connue sous le nom « du général au spécifique » pour estimer un modèle autorégressif à retards échelonnés (ARDL). Ce dernier conduit à une équation finale composée d'une relation de cointégration entre les quatre variables retenues (consommation d'électricité, prix de l'électricité, prix du gaz et PIB réel) et d'un mécanisme à correction d'erreur. À court terme, les déterminants de la demande d'électricité sont principalement constitués par l'occurrence de récessions économiques et par les variations de température.
Références
Amarawickrama, H.A. et Hunt, L.C. (2008), Electricity demand for Sri Lanka : A time series analysis. Energy, 33, 724-739.
View in Google Scholar
Asafu-Adjaye, J. (2000). The relationship between energy consumption, energy prices and economic growth : Time series evidence from Asian developing countries. Energy Economics, 22, 615-625.
View in Google Scholar
Bentzen, J. et Engsted, T. (2001). A revival of the autoregressive distributed lag model in estimating energy demand relationship. Energy, 26, 45-55.
View in Google Scholar
Bernstein, R. et Madlener, R. (2015). Short- and long-run electricity demand elasticities at the subsectoral level : A cointegration analysis for German manufacturing industries . Energy Economics, 48, 178-187.
View in Google Scholar
Bismans, F. (2014), Datation et prévision du cycle économique. Studia Oeconomica Posnaniensia, 2, 186-202.
View in Google Scholar
Bismans, F. (2016). Afterword. Dans : F. Bismans et al. (dir.), Business cycles in the run of history, Heidelberg – New York – Dordrecht – London : Springer.
View in Google Scholar
Bismans, F. et Majetti, R. (2013). Forecasting recessions using financial variables : The French case. Empirical Economics, 44, 419-433.
View in Google Scholar
Brown, R.L., Durbin, J. et Evans, J.M. (1975), Techniques for testing the constancy of regression relationship over time. Journal of the Royal Statistical Society, Series B, 37, 149-192. Clerc, M. et Marcus, V. (2009). Élasticités-prix des consommations énergétiques des ménages. Documents de travail, G2009/08, INSEE.
View in Google Scholar
Dickey, D.R. et Fuller, W.A. (1979). Distributions of the estimators for autoregressive times series with a unit root. Journal of the American Statistical Association, 74, 427-431.
View in Google Scholar
Elliott, G., Rothenberg, T.J. et Stock, J.H. (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64, 813-836.
View in Google Scholar
Engle, R.F. et Granger, C.W.J. (1987). Co-integration and error correction : Representation, estimation, and testing. Econometrica, 55, 251-276.
View in Google Scholar
Fatai, K., Oxley, L. et Scrimgeour, F.G. (2003). Modeling and forecasting the demand for electricity in New Zealand : A comparison of alternatives approaches. Energy Journal, 24, 75-102.
View in Google Scholar
Granger, C.W.J. et Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2, 111-120.
View in Google Scholar
Hannesson, R. (2009). Energy and GDP growth. International Journal of Energy Sector Management, 3, 157-170.
View in Google Scholar
Hansen, B.E. et Phillips, P.C.B. (1990). Estimation and inference in models of cointegration : A simulation studies. Advances in Econometrics, 8, 225-248.
View in Google Scholar
Hansen, J.-P. et Percebois, J. (2010). Énergie. Économie et politiques. Bruxelles : De Boeck Université.
View in Google Scholar
Hendry, D.F. (2000). Econometrics. Alchemy or science ? Oxford : Oxford University Press. Hendry, D.F. et Doornik, J.A. (2014). Empirical model discovery and theory evaluation. Automatic selection methods in econometrics. Cambridge – London, Massachusetts : Institute of Technology Press.
View in Google Scholar
Hendry, D.F. et Wallis, K.F. (dir.). (1984). Econometrics and quantitative economics. Oxford : Basil Blackwell.
View in Google Scholar
Huang, B.N., Hwang, M.J. et Yang, C.W. (2008), Causal relationship between energy consumption and GDP growth revisited : A dynamic panel data approach. Ecological economics, 67, 41-54.
View in Google Scholar
Jamil, F. et Ahmad, E. (2011). Income and price elasticities of electricity : Aggregate and sector-wise analysis. Energy Policy, 39, 5519-5527.
View in Google Scholar
Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dyna- mics and Control, 12, 231-254.
View in Google Scholar
Johansen, S. (1995). Likelihood-based inference in cointegrated vector autoregressive models. Oxford : Oxford University Press.
View in Google Scholar
Jumbe, C. B. (2004). Cointegration and causality between electricity consumption and GDP : Empirical evidence from Malawi. Energy Economics, 26, 61-68.
View in Google Scholar
Keynes, J.M. (1939). Préface pour l’édition française. Dans : J.M. Keynes. Théorie générale de l’emploi, de l’intérêt et de la monnaie, Paris : Payot, 1969.
View in Google Scholar
Kraft, J. et Kraft, A. (1978). On the relationship between energy and GNP. Journal of Energy Development, 3, 401-403.
View in Google Scholar
Kydland, F. et Prescott, E. (1991). The econometrics of the general equilibrium approach to the business cycle, Scandinavian Journal of Economics, 93, pp. 161-178.
View in Google Scholar
Lee, C.C. (2005). Energy consumption and GDP in developing countries : A cointegrated panel analysis. Energy Economics, 27, 415-427.
View in Google Scholar
Lee, C.C. (2006). The causality relationship between energy consumption and GDP in G-11 countries revisited. Energy Policy, 34, 1086-1093.
View in Google Scholar
Lim, K.-M., Lim, S.-E. et Yoo, S.-H. (2014). Short- and long-run elasticities of electricity demand in the Korean service sector. Energy Policy, 67, 517-521.
View in Google Scholar
Mehrara, M. (2007). Energy Consumption and Economic Growth : The case of oil exporting countries. Energy Policy, 35, 2939-2945.
View in Google Scholar
Narayan, P. K. et Smyth, R. (2008). Energy consumption and real GDP in G7 countries : New evidence from panel cointegration with structural breaks. Energy Economics, 30, 2331-2341.
View in Google Scholar
Nguyen-Van, P. (2010). Energy consumption and income : A semiparametric panel data analysis. Energy Economics, 32, 557-563.
View in Google Scholar
Okajima, S. et Okajima, H. (2013). Estimation of Japanese price elasticity of residential electricity demand. Energy Economics, 40, 433-440.
View in Google Scholar
Patterson, K. (2010). A primer for unit root testing. Basingstoke – New York : Palgrave Macmillan.
View in Google Scholar
Payne, J.E. (2010). Survey of the international evidence on the causal relationship between energy consumption and growth. Journal of Economic Studies, 37, 53-95.
View in Google Scholar
Penot-Antonion, L. et Têtu, Ph. (2010). Modélisation économétrique des consommations de chauffage des logements en France, Études & Documents, 21, Commissariat Général au Développement Durable.
View in Google Scholar
Perron, P. (1989). The great crash, the oil price shock and the unit root hypothesis. Econometrica, 57, 1361-1401.
View in Google Scholar
Perron, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics, 8, 153-162.
View in Google Scholar
Perron, P. (2007). Dealing with structural breaks. Dans: T.E. Mills et K. Patterson (dir.), Palgrave Handbook of Econometrics. Basingstoke – New York : Palgrave-Macmillan, 1.
View in Google Scholar
Pesaran, H. et Shin, Y. (1999). An autoregressive distributed-lag modelling approach to cointegration analysis. Dans : S. Strom (dir.), Econometrics and economic theory in the 20th century : The Ragnar Frisch centennial symposium. Cambridge : Cambridge University Press, 371-413.
View in Google Scholar
Pesaran, H., Shin, Y. et Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16, 289-326.
View in Google Scholar
Phillips, P.C.B. (1986). Understanding spurious regressions in econometrics. Journal of Econometrics, 33, 311-340.
View in Google Scholar
Phillips, P.C.B. (1995). Fully modified least squares and vector autoregressions. Econometrica, 63, 1023-1078.
View in Google Scholar
Polemis, M.L. (2007). Modeling industrial energy demand in Greece using cointegration techniques. Energy Policy, 35, 4039-4050.
View in Google Scholar
Rapanos, V.T. et Polemis, M.L. (2006). The structure of residential energy demand in Greece. Energy Policy, 34, 3137-3143.
View in Google Scholar
Renou-Maissant, P. (2002). Analyse des comportements de substitutions énergétiques dans le secteur industriel des sept grands pays de l’OCDE. Revue Économique, 53, 983-1011.
View in Google Scholar
Soytas, U. et Sari, R. (2003). Energy consumption and GDP : Causality relationship in G-7 countries and emerging markets. Energy Economics, 25, 33-37.
View in Google Scholar
Stiglitz, J.E. (2011). Rethinking macroeconomics : What failed, and how to repair it. Journal of the European Economic Association, 9, 591-645.
View in Google Scholar
Stock, J. et Watson, M.W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica, 61, 783-820.
View in Google Scholar
Tsani, S.Z. (2010). Energy consumption and economic growth : A causality analysis for Greece. Energy Economics, 32, 582-590.
View in Google Scholar
Villa, P. (1998). Évolution sur longue période de l’intensité énergétique. Document de Travail, 98-08, CEPII.
View in Google Scholar
Xiao, N., Zarnikau, J. et Damien, P. (2007). Testing functional forms in energy demand : An application of the Bayesian approach to US electricity demand. Energy Economics, 29, 158-166.
View in Google Scholar
Zarnikau, J. (2003). Functional forms in energy demand modelling. Energy Economics, 25, 603-613.
View in Google Scholar
Zivot, E. et Andrews, D.W.K. (1992). Further evidence on the great crash, the oil price shock and the unit root hypothesis. Journal of Business and Economic Statistics, 10, 251-270.
View in Google Scholar
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