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Habits, Complementarities and Heterogeneity in Alcohol and Tobacco Demand: A Multivariate Dynamic Model

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  • David Aristei
  • Luca Pieroni

Abstract

In this paper we test the existence of forward‐looking behaviour in a multivariate model for alcohol and tobacco consumption. The theoretical framework, based on a dynamic adjustment cost model with forward‐looking behaviour, is enhanced to include the intertemporal interactions between the two goods. The analysis of the within‐period preferences completes the intertemporal model, allowing to evaluate the static substitutability/complementarity relationships. The empirical strategy consists in a two‐step estimation procedure. In a first stage, we obtain the parameters of the demand system, while in a second stage Euler equations are estimated. Results, based on a cohort data set constructed from a series of cross‐sections of the Italian Household Budget Survey, reveal a significant complementarity relationship between alcohol and tobacco. Estimation of the Euler equations does not lead to rejection of the hypothesis of intertemporal dependence, providing evidence for a forward‐looking behaviour in alcohol and tobacco consumption. Moreover, we find significant intertemporal interactions that support the adjustment cost setting in a multivariate model with rational expectations.

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  • David Aristei & Luca Pieroni, 2010. "Habits, Complementarities and Heterogeneity in Alcohol and Tobacco Demand: A Multivariate Dynamic Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(4), pages 428-457, August.
    • Handle: RePEc:bla:obuest:v:72:y:2010:i:4:p:428-457
    DOI: 10.1111/j.1468-0084.2010.00590.x
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    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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