Full Sample Maximum Likelihood Estimation of Dynamic Demand Models

Philippe Deschamps

No 1995049, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: The maximum likelihood estimation of dynamic demand models has usually been based on the likelihood function conditional on the first observations of the dependent variables. However, this neglects information which may be necessary for identifying the long-run structure. We formulate the unconditional likelihood of a general dynamic demand model involving arbitrary lag orders, express its analytical derivatives in a relatively simple form, and propose a reparameterization which is always welldefined. The methodology is illustrated with a small empirical application, using the levels version of the CBS model proposed by Barten (1989) and annual British data on four commodities.

Keywords: Unconditional likelihood function; Dynamic demand models; Matrix differential calculus; Error-correction models (search for similar items in EconPapers)
JEL-codes: C13 C32 C63 (search for similar items in EconPapers)
Date: 1995-08-01
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:1995049

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