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Time‐varying intercepts and equilibrium analysis: an extension of the dynamic almost ideal demand model
Author(s) -
Deschamps Philippe J.
Publication year - 2002
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.674
Subject(s) - unobservable , markov chain monte carlo , econometrics , state space , autoregressive model , bayesian probability , markov chain , cointegration , extension (predicate logic) , almost ideal demand system , monte carlo method , computer science , lag , economics , mathematics , statistics , demand management , programming language , computer network , macroeconomics
Demographic effects and user costs in demand systems have usually been modelled explicitly. A more robust approach is a state space formulation of the demand system, where time‐varying intercepts account for the effects of unobservable variables. The author embeds such a system in a vector autoregressive distributed lag model, with a Bayesian hierarchical prior. The model is estimated by a Markov chain Monte Carlo method on samples involving quarterly US and UK data. In the US case, the results are compared with a previously published cointegration analysis of the same data. Copyright © 2002 John Wiley & Sons, Ltd.