Incitations ŕ développer les EnR et l'énergie solaire : une approche par la cointégration en panel
Mots-clés :
EnR, production d’électricité, solaire, économétrie des panels, non stationnarité, cointégrationRésumé
Les menaces que font peser le réchauff ement climatique sur l'environnement ont incité les pouvoirs publics des pays européens à accélérer leur transition énergétique et à augmenter leur production d'électricité à partir d'énergies renouvelables (EnR). Le déploiement des énergies renouvelables en Europe est cependant hétérogène selon les pays et il semble répondre à un certain nombre de déterminants macroéconomiques identifi és dans la littérature (émissions de CO2, revenu national, consommation et dépendance énergétique, dynamique du prix du pétrole). Dans cet article, nous montrons que le recours aux estimateurs à eff ets fi xes permet de retrouver les eff ets empiriques des déterminants usuels de la production d'électricité à partir des EnR pris dans leur globalité. Néanmoins, les analyses de la littérature semblent avoir négligé la présence de non stationnarité et de cointégration dans la relation entre la production d'EnR et ses déterminants. L'utilisation d'estimateurs adaptés à la cointégration (DOLS, FMOLS) relativise la portée des résultats habituellement identifi és dans la littérature. En conduisant la même analyse pour le cas particulier de l'énergie solaire, nous montrons que ce type particulier d'énergie, comme le laissait entrevoir une maigre littérature, ne réagit pas aussi fortement aux principaux déterminants macroéconomiques que les EnR dans leur globalité. Les estimations en panel par eff ets fi xes et par le biais des estimateurs de panel adaptés à la présence de cointégration conduisent à cette même conclusion que seul le niveau de dépendance énergétique est réellement important dans la décision de produire de l'énergie solaire.
Références
Aguirre, M., Ibikunle, G., 2014, Determinants of Renewable Energy Growth: a Global Sample Analysis, Energy Policy, vol. 69: 374–384.
View in Google Scholar
Carley, S., 2009, State Renewable Energy Electricity Policies: an Empirical Evaluation of Effectiveness, Energy Policy, vol. 37, pp. 3071–3081.
View in Google Scholar
Carrion-i-Silvestre, J.L., Barrio-Castro, T.D., Lopez-Bazo, E., 2005, Breaking the Panels: an Application to the GDP Per Capita, Econometrics Journal, vol. 8, pp. 159–75.
View in Google Scholar
Eberhardt, M., 2012, Estimating Panel Time-series Models with Heterogeneous Slopes, The Stata Journal, vol. 12(1), pp. 61–71.
View in Google Scholar
Eberhardt, M., Presbitero, A.F., 2015, Public Debt and Growth: Heterogeneity and Non-li- nearity, Journal of International Economics, vol. 97 (1), pp. 45–58.
View in Google Scholar
Engle, R.F., Granger, C.W. J., 1987, Co-Integration and Error Correction: Representation, Estimation, and Testing, Econometrica, vol. 55(2), pp. 251–276.
View in Google Scholar
Gan, L., Eskeland, G., Kolshus, H., 2007, Green Electricity Market Development : Lessons from Europe and the US, Energy Policy. vol. 35, pp. 144–155.
View in Google Scholar
Harmelink, M., Voogt, M., Cremer, C., 2006, Analysing the Effectiveness of Renewable Energy Supporting Policies in the European Union, Energy Policy, vol. 34, no. 3, pp. 343–3351.
View in Google Scholar
Hlouskova, J., Wagner, M., 2006, The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study, Econometric Reviews, vol. 25 (1), pp. 85–116.
View in Google Scholar
Im, K.S., Pesaran, M.H., Shin, Y., 2003, Testing for Unit Roots in Heterogenous Panels, Journal of Econometrics, vol. 115 (1), pp. 53–74.
View in Google Scholar
Johnstone N., Hascic I., Popp D., 2010, Renewable Energy Policies and Technological Innovation : Evidence Based on Patents Counts, Environmental and Resource Economics. vol. 45, pp. 133–155.
View in Google Scholar
Kao, C., Chiang, M.H., 2000, On the Estimation and Inference of a Cointegrated Regression in Panel Data, Advances in Econometrics, vol. 15, pp. 179–222.
View in Google Scholar
Levin, A., Lin, C.F., Chu, C., 2002, Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties, Journal of Econometrics, vol. 108, pp. 1–25.
View in Google Scholar
Maddala, G.S., Wu, S., 1999, A comparative Study of Unit Root Tests with Panel Data and a new Simple Test, Oxford Bulletin of Economics and Statistics, vol. 61, pp. 631–652.
View in Google Scholar
Marques A.C., Fuinhas J.A., Manso J.R., 2010, Motivations Driving Renewable Energy in European Countries : a Panel Data Approach, Energy Policy, vol. 38, pp. 6877–6885.
View in Google Scholar
Marques A.C., Fuinhas J.A., 2011, Drivers Promoting Renewable Energy: a Dynamic Panel Approach, Renewable and Sustainable Energy Reviews, vol. 15(3), pp. 1601–1608 Marques A.C. Fuinhas J.A., 2012, Are Public Policies Towards Renewables Successful? Evidence from European Countries, Renewable Energy, vol. 44, pp. 109–118.
View in Google Scholar
Menz F., Vachon, S., 2006, The Effectiveness of Different Policy Regimes for Promoting Wind Power: Experiences from the States, Energy Policy, vol. 34, pp. 1786–1796.
View in Google Scholar
Moscone, F., Tosetti, E., 2009, A Review And Comparison of Tests of Cross-Section Independence in Panels, Journal of Economic Surveys, vol. 23(3): 528–561.
View in Google Scholar
Omri, A., Nguyen, D.K., 2014, On the Determinants of Renewable Energy Consumption: International Evidence, Energy, vol. 72, pp. 554–560.
View in Google Scholar
Orsal, D.K., 2008, Comparisons of Panel Cointegration Tests, Economics Bulletin, vol. 3(6), pp. 1–20.
View in Google Scholar
Pedroni, P., 1999, Critical Values for Cointegration Tests in Heterogenous Panels with Multiple Regressors, Oxford Bulleting of Economics and Statistics, vol. 61, pp. 631–652.
View in Google Scholar
Pedroni, P., 2000, Fully Modified ols for Heterogeneous Cointegrated Panels, Advances in Econometrics, vol. 15, pp. 93–130.
View in Google Scholar
Pedroni, P., 2004, Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the Ppp Hypothesis, Econometric Theory, vol. 20(3), pp. 597–625.
View in Google Scholar
Pesaran, M.H., 2004, General Diagnostic Tests for Cross Section Dependence in Panels, University of Cambridge, Faculty of Economics, Cambridge Working Papers in Economics no. 0435.
View in Google Scholar
Pesaran, M.H., 2006, Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure, Econometrica, vol. 74, pp. 967–1012.
View in Google Scholar
Pesaran, M.H, 2007, A Simple Panel Unit Root Test in the Presence of Cross-section De- pendence, Journal of Applied Econometrics, vol. 22(2), pp. 265–312.
View in Google Scholar
Pesaran, M.H, Smith, V.L., Takashi, Y., 2013, Panel Unit Root Tests in the Presence of a Multifactor Error Structure, Journal of Econometrics, vol. 175(2), pp. 94–115.
View in Google Scholar
Polzin, F., Migendt, M., Täube, F.A., von Flotow, P., 2015, Public Policy Influence on Renewable Energy Investments, A panel data study across OECD countries. Energy Policy, vol. 80, pp. 98–111.
View in Google Scholar
Popp, D., Hascic, I., Medhi, N., 2011, Technology and the Diffusion of Renewable Energy, Energy Economics, vol. 33 (4), pp. 648–662.
View in Google Scholar
Ringel, M., 2006, Fostering the Use of Renewable Energies in the European Union: The Race between Feed-in Tariffs and Green Certificates, Renewable Energy, vol. 31, pp. 11–17.
View in Google Scholar
Romano A.A., Scandurra G., Carfora A., Fodor M., 2017, Renewable Investments: The impact of Green Policies in Developing and Developed Countries, Renewable and Sustainable Energy Reviews, vol. 68, pp. 738–747.
View in Google Scholar
Valdès Lucas J.N., Escribano Francés G., Gonzalez San Martin E., 2016, Energy Security and Renewable Energy Deployment in the EU: Liaisons Dangereuses or Virtuous Circle?, Renewable and Sustainable Energy Reviews, vol. 62, pp. 1032–1046.
View in Google Scholar
Van Ruijven B., Van Vuuren D., 2009, Oil and Natural Gas Prices and Greenhouse Gas Emissions Mitigation, Energy Policy, vol. 37, pp. 4797–4808.
View in Google Scholar
Van Rooijen S., Van Wees M., 2006, Green Electricity Policies in the Netherlands: an Analysis of Policy Decisions, Energy Policy, vol. 34, pp. 60–71.
View in Google Scholar
Westerlund, J., 2007, Testing for Error Correction in Panel Data, Oxford Bulletin of Economics and Statistics, vol. 68, pp. 101–132.
View in Google Scholar
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