Simulated maximum likelihood estimation of demand systems with corner solutions and panel data application to industrial energy demand

Estimation par maximum de vraisemblance simulé de systèmes de demande avec solutions en coin et données de panel application à la demande d’énergie industrielle

Raja Chakir () and Alban Thomas
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Raja Chakir: GREMAQ - Groupe de recherche en économie mathématique et quantitative - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique
Alban Thomas: LEERNA - Laboratoire d'Economie de l'Environnement et des Ressources Naturelles - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INRA - Institut National de la Recherche Agronomique

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Abstract: his paper proposes a convenient method for evaluating energy price elasticities, when firms may switch between energy regimes. The methodology involves estimation of an energy demand system that explicitly deals with the zero expenditures problem, while allowing for unobserved heterogeneity. We apply a Simulated Maximum Likelihood technique for estimating a simultaneous equation energy demand system in the French pulp and paper sector, over the period 1983-1996. Endogenous regime transitions are accounted for when computing energy price elasticities. Our estimates are used to predict the outcome of an environmental policy aimed at reducing CO 2 emissions in the paper and pulp industry.

Keywords: Simulated maximum likelihood; Non-negativity constraint; Energy demand estimation; Contraintes de positivité; Estimation de la demande d'énergie; Maximum de vraisemblance simulé (search for similar items in EconPapers)
Date: 2003-12-01
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Published in Revue d'économie politique, 2003, Vol. 113 (6), pp.773-799. ⟨10.3917/redp.136.0773⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05136019

DOI: 10.3917/redp.136.0773

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