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Psychology in econometric models: conceptual and methodological foundations

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  • Thum, Anna-Elisabeth

Abstract

Personality, ability, trust, motivation and beliefs determine outcomes in life and in particular those of economic nature such as finding a job or earnings. A problem with this type of determinants is that they are not immanently objectively quantifiable and that there is no intrinsic scale - such as in the case of age, years of education or wages. Often we think of these concepts as complex and several items are needed to capture them. In the measurement sense, we dispose of a more or less noisy set of measures, which indirectly express and measure a concept of interest. This way of conceptualizing is used in latent variables modelling. I examine in this article in how far economic and econometric literature can contribute to specifying a framework of how to use latent variables in economic models. As a semiparametric identification strategy for models with endogeneous latent factors I propose to use existing work on identification in the presence of endogeneous variables and examine which additional assumptions are necessary to apply this strategy for models with latent variables. I discuss several estimation strategies and implement a Bayesian Markov Chain Monte Carlo (MCMC) algorithm.

Suggested Citation

  • Thum, Anna-Elisabeth, 2013. "Psychology in econometric models: conceptual and methodological foundations," MPRA Paper 52293, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:52293
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    File URL: https://mpra.ub.uni-muenchen.de/52293/1/MPRA_paper_52293.pdf
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    References listed on IDEAS

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    1. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
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    4. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    5. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 411-482, July.
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    More about this item

    Keywords

    latent variable modelling; identification with endogenous regressors; monte carlo markov chain;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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