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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.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 52293.

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Date of creation: 20 Dec 2013
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Handle: RePEc:pra:mprapa:52293

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

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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.
  2. Arthur Lewbel, 1999. "Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables," Boston College Working Papers in Economics 454, Boston College Department of Economics.
  3. Borghans, Lex & Duckworth, Angela Lee & Heckman, James J. & Weel, Bas ter, 2008. "The Economics and Psychology of Personality Traits," MERIT Working Papers 010, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  4. James J. Heckman & Jora Stixrud & Sergio Urzua, 2006. "The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior," NBER Working Papers 12006, National Bureau of Economic Research, Inc.
  5. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute for the Study of Labor (IZA).
  6. Melissa Osborne & Herbert Gintis & Samuel Bowles, 2001. "The Determinants of Earnings: A Behavioral Approach," Journal of Economic Literature, American Economic Association, vol. 39(4), pages 1137-1176, December.
  7. Yoshio Takane & Jan Leeuw, 1987. "On the relationship between item response theory and factor analysis of discretized variables," Psychometrika, Springer, vol. 52(3), pages 393-408, September.
  8. Jeff Douglas, 1997. "Joint consistency of nonparametric item characteristic curve and ability estimation," Psychometrika, Springer, vol. 62(1), pages 7-28, March.
  9. Poirier, Dale J., 1998. "Revising Beliefs In Nonidentified Models," Econometric Theory, Cambridge University Press, vol. 14(04), pages 483-509, August.
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