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Determining the Proper Specification for Endogenous Covariates in Discrete Data Settings

In: Bayesian Model Comparison

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  • Angela Vossmeyer

Abstract

An important but often overlooked obstacle in multivariate discrete data models is the specification of endogenous covariates. Endogeneity can be modeled as latent or observed, representing competing hypotheses about the outcomes being considered. However, little attention has been applied to deciphering which specification is best supported by the data. This paper highlights the use of existing Bayesian model comparison techniques to investigate the proper specification for endogenous covariates and to understand the nature of endogeneity. Consideration of both observed and latent modeling approaches is emphasized in two empirical applications. The first application examines linkages for banking contagion and the second application evaluates the impact of education on socioeconomic outcomes.

Suggested Citation

  • Angela Vossmeyer, 2014. "Determining the Proper Specification for Endogenous Covariates in Discrete Data Settings," Advances in Econometrics, in: Bayesian Model Comparison, volume 34, pages 223-247, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320140000034010
    DOI: 10.1108/S0731-905320140000034010
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    More about this item

    Keywords

    Bayesian estimation; data augmentation; educational attainment; financial contagion; latent data; marginal likelihood; C35; C52; G01; I00;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G01 - Financial Economics - - General - - - Financial Crises
    • I00 - Health, Education, and Welfare - - General - - - General

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