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A panel data model for subjective information on household income growth

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  • Das, J.W.M.

    (Tilburg University, School of Economics and Management)

  • van Soest, A.H.O.

    (Tilburg University, School of Economics and Management)

Abstract

Subjective expectations about future income changes are analyzed, using household panel data. The models used are extensions of existing binary choice panel data models to the case of ordered response. We consider static models with random and fixed individual effects. We also look at a dynamic random effects model which includes a measure for permanent and transitory income. We find that income change expectations strongly depend on realized income changes in the past: those whose income fell, are more pessimistic than others, while those whose income rose are more optimistic. Expected income changes are also significantly affected by employment status, family composition, permanent income, and past expectations. Expectations are then compared to the head of households ex post perception of the realized income change for the same period. The main finding is that rational expectations are rejected, and that in particular, households whose income has decreased in the past underestimate their future income growth.

Suggested Citation

  • Das, J.W.M. & van Soest, A.H.O., 1996. "A panel data model for subjective information on household income growth," Other publications TiSEM a6683363-b5a6-4fe7-b062-7, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:a6683363-b5a6-4fe7-b062-7e32d4fbf5c8
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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