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Aggregation of Non Stationary Demand Systems

Author

Listed:
  • Jérôme Adda

    (UCL - University College of London [London])

  • Jean-Marc Robin

    (EUREQUA - Equipe Universitaire de Recherche en Economie Quantitative - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper studies under which conditions a cross-sectional regression yields unbiased estimates of the parameters of an individual dynamic model with fixed effects and individual-specific responses to macro shocks. We show that the OLS estimation of a relationship involving non stationary variables on a cross-section yields estimates which converge to the true value when calendar time tends to infinity. We then consider the particular case of an AI demand model, and we show, using French quarterly aggregate time-series, that budget shares, relative prices and the log of real total expenditure are I(1) and form a cointegrated system. We compare these macro estimates to estimates obtained from three Family Expenditure Surveys and find large differences.

Suggested Citation

  • Jérôme Adda & Jean-Marc Robin, 2003. "Aggregation of Non Stationary Demand Systems," Post-Print hal-00357750, HAL.
    • Handle: RePEc:hal:journl:hal-00357750
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    Keywords

    Non Stationary Demand Systems;

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