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Interpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Models

Authors: Greene, William
Keywords: Panel data;random effects;random parameters;maximum simulated likelihood;posterior mean;posterior variance;marginal effects;confidence interval
Issue Date: Sep-2003
Series/Report no.: EC-03-19
Abstract: Recent studies in econometrics and statistics include many applications of random parameter models. There is some ambiguity in how estimation results in these models are 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.
Appears in Collections:Economics Working Papers

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