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From |
"Twinemanzi Tumubweinee" <tkt011000@utdallas.edu> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: Estimating random effects that vary over time and cross-sections with Panel Data |

Date |
Sun, 12 Apr 2009 19:16:14 -0500 |

specification y_[it] = x_[it]*a_[it]+ w_[it]*b_[it]+ e_[it] where i=cross sectional units (Banks) and t=time(Quarter). And x_[it] are the co-variates and the error term e_[it] is assumed to follow a Gaussian distribution. I have 45 time periods, 21 cross-sectional units and about 669 observations since this is an unbalanced panel. My first question: Is it correct, that in using -gllamm- to estimate the above model I should do the following: Step 1-Define an equation "slope" for co-variates that vary over cross-sections (banks) and time (quarters) Step 2-Then define another equation "slope2" for the co-variates that vary only over time eq slope: x1 x2 x3 eq slope2: x4 x5 gllamm y x1 x2 x3 x4 x5, i(Quarter Bank) nrf(1,1) nip(7,7) adapt eqs(slope slope2) robust cluster(Bank) trace dots On doing this however I fail to get any kind of convergence for the maximum likelihood. Is there any suggestion on how I should go about this? The second question: if -gllamm- is not appropriate for the above model, is there a STATA command/ routine or some kind of work around that would enable me estimate random coefficients that vary over time and cross sections for unbalanced Panel data? Many thanks, Twinemanzi Tumubweinee (Twine) PhD Student School of Economics, Political and Policy Sciences University of Texas at Dallas Tel: 972-883-4913 tkt011000@utdallas.edu * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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