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dc.contributor.authorGreene, William-
dc.date.accessioned2008-05-22T11:54:44Z-
dc.date.available2008-05-22T11:54:44Z-
dc.date.issued2003-09-
dc.identifier.urihttp://hdl.handle.net/2451/26172-
dc.description.abstractRecent 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.en
dc.language.isoen_USen
dc.relation.ispartofseriesEC-03-19en
dc.subjectPanel dataen
dc.subjectrandom effectsen
dc.subjectrandom parametersen
dc.subjectmaximum simulated likelihooden
dc.subjectposterior meanen
dc.subjectposterior varianceen
dc.subjectmarginal effectsen
dc.subjectconfidence intervalen
dc.titleInterpreting Estimated Parameters and Measuring Individual Heterogeneity in Random Coefficient Modelsen
dc.typeWorking Paperen
Appears in Collections:Economics Working Papers

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