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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/26121
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| Title: | Interpreting Estimated Parameters and Measuring Individual Heterogeneity
in Random Coefficient Models |
| Authors: | Greene, William |
| Keywords: | Panel data
random effects
random parameters
maximum simulated likelihood
conditional mean
conditional variance
marginal effects
confidence interval |
| Issue Date: | 6-May-2004 |
| Series/Report no.: | EC-04-08 |
| Abstract: | Recent studies in econometrics and statistics include many applications
of random parameter models. The underlying structural parameters in
these models are often not directly 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 a suggestion on
how to examine the results of estimation of a general form of random
parameter model. We also extend results on computing individual level
parameters in a random parameters setting and show how simulation based
estimates of parameters in conditional distributions can be used to
examine the influence of model covariates (marginal effects) at an
individual level |
| URI: | http://hdl.handle.net/2451/26121 |
| Appears in Collections: | Economics Working Papers
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