Psychology in econometric models: conceptual and methodological foundations

Anna Thum-Thysen

MPRA Paper from University Library of Munich, Germany

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.

Keywords: latent variable modelling; identification with endogenous regressors; monte carlo markov chain (search for similar items in EconPapers)
JEL-codes: C11 C14 C38 J24 (search for similar items in EconPapers)
Date: 2013-12-20
New Economics Papers: this item is included in nep-dcm and nep-ecm
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