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Parametric and nonparametric inference in equilibrium job search models

Koop, G.M. (2008) Parametric and nonparametric inference in equilibrium job search models. Advances in Econometrics, 23. pp. 217-244. ISSN 0731-9053

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    Abstract

    Equilibrium job search models allow for labor markets with homogeneous workers and firms to yield nondegenerate wage densities. However, the resulting wage densities do not accord well with empirical regularities. Accordingly, many extensions to the basic equilibrium search model have been considered (e.g., heterogeneity in productivity, heterogeneity in the value of leisure, etc.). It is increasingly common to use nonparametric forms for these extensions and, hence, researchers can obtain a perfect fit (in a kernel smoothed sense) between theoretical and empirical wage densities. This makes it difficult to carry out model comparison of different model extensions. In this paper, we first develop Bayesian parametric and nonparametric methods which are comparable to the existing non-Bayesian literature. We then show how Bayesian methods can be used to compare various nonparametric equilibrium search models in a statistically rigorous sense.

    Item type: Article
    ID code: 7753
    Keywords: parametric inference, nonparametric inference, equilibrium job search models, econometrics, Economic Theory, Statistics, Economics and Econometrics
    Subjects: Social Sciences > Economic Theory
    Social Sciences > Statistics
    Department: Strathclyde Business School > Economics
    Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 20 Mar 2009 15:36
    Last modified: 05 Sep 2014 13:37
    URI: http://strathprints.strath.ac.uk/id/eprint/7753

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