An application of dynamic specifications of factor demand equations to interfuel substitution in US industrial energy demand

• Published in: Economic modelling Vol. 16; no. 4; pp. 503 - 513
• Main Author: Urga, Giovanni
• Format: Journal Article
• Language: English
• Published: London Elsevier B.V 01.12.1999; Elsevier; Butterworths; Elsevier Science Ltd
• Series: Economic Modelling
• Subjects: Cost function; Demand functions; Dynamic cost function; Economic models; Elasticity of demand; Energy consumption; Equilibrium; Fuels; Mathematical economics; Power demand; Statistics; Studies; Supply & demand; U.S.A; United States > US; Dynamic cost function; D2; C2
• ISSN: 0264-9993; 1873-6122
• DOI: 10.1016/S0264-9993(99)00012-7

In a recent paper, Jones (1995) [A dynamic analysis of the interfuel substitution in US industrial energy demand. J. Bus. Econ. Stat. 13 (4), 459–465] presents a dynamic analysis of interfuel substitution in US industry energy demand. The author concludes that a dynamic linear logit model is `superior' to a comparable dynamic translog model. The latter in fact violates concavity conditions whilst the logit formulation does not. This paper shows first of all that the dynamic formulation of the translog used in Jones (1995) is mis-specified. In fact, a parsimonious error-correction model (ECM) `dominates' alternative dynamic formulations, amongst which the partial adjustment mechanism used by the author. The ECM is able to generate optimal estimates of long-run and short-run elasticities, and it satisfies the concavity conditions of the cost function. Further, the theoretical framework used in this paper is the one recently proposed by Urga (1996) [On the identification problem in testing dynamic specification of factor demand equations. Econ. Lett. 52, 205–210] and Allen and Urga (1998) [Derivation and estimation of interrelated factor demands from dynamic cost function. Forthcoming in Economica]. It allows one to identify all coefficients (long-run and short-run) of the dynamic formulation via the joint estimation of the `effective' (short-run) cost function and the set of factor demand equations. This strategy solves, amongst other things, the parameter identification problem within the set of demand equations themselves, an issue which was originally noted by Anderson and Blundell (1982) [Estimation and hypothesis testing in dynamic singular equation systems. Econometrica, 1559–1571], re-addressed by Friesen (1992) [Testing dynamic specification of factor demand equations for US manufacturing. Rev. Econ. Stat. LXXIV (2), 240–250] and, more recently, by Urga (1996) and Allen and Urga (1998).