Interpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Models

11 Pages Posted: 31 Oct 2008

See all articles by William H. Greene

William H. Greene

New York University Stern School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: September 2003

Abstract

Recent studies in econometrics and statistics include many applications of randomparameter models. There is some ambiguity in how estimation results in these modelsare interpreted. The underlying structural parameters are often not informative about the statistical relationship of interest. As a result, standard significance tests of structural parameters in random parameter models do not necessarily indicate the presence or absence of a significant relationship among the model variables. This note offers some suggestions on how to interpret and use the results of estimation of a general form of random parameter model and how simulation based estimates of parameters in conditional distributions can be used to examine the influence of model covariates.

Keywords: Panel data, random effects, random parameters, maximum simulated likelihood, posterior mean, posterior variance, marginal effects, confidence interval

Suggested Citation

Greene, William H., Interpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Models (September 2003). NYU Working Paper No. EC-03-19, Available at SSRN: https://ssrn.com/abstract=1292639

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