[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

---------------------------------------------------------------------------- ---- David Greenberg wrote: > Beck and Katz urge the use of panel-corrected standard errors to accompany > OLS estimation for the special case when T is large and N is small. Enrico > Pellizzoni's case is one when T is small and N is large. I don't believe > that such methods as generalized least squares perform badly in that > situation. Thanks for your comments. I've flicked through the three Beck/Katz papers on their critique of FGLS, and I reckon I'm reasonably sure of my ground. In their 1995 paper, their Monte Carlo simulations show that FGLS performs _worse_ in terms of overconfidence (i.e., the degree to which it underestimates estimator variability) when T is small (pp 639-40). Many savvy researchers recognised this and simply used FGLS to correct for panel heteroscedasticity, hence Kmenta's CHTA (or PWLS, as B/K call it). In their 1996 paper, they ran another MC simulation and concluded that PWLS should only be used when T=>20 and where there is actually panel heteroscedasticity in the errors that needs correcting (pp 20-3)! By the 2001 paper, B/K summarise all this by making their earlier material (slightly) easier to digest (mainly for thickards like me!), say that OLS-PCSE performs better against both rivals in these circumstances and conclude that "... the Parks-Kmenta [FGLS] estimator simply should not be used" (Beck, 2001: 276). I don't know about you, but reading this paper after their two others led me to believe that one should take this injuction as _universal_ and not partial. Of course, there may be many (F)GLS lovers out there who would violently disagree with B/K on this, but there you are. By the way, what -xt- would you suggest where T=6 and N=3456 (he asks cheekily)? Neal Beck himself simply warned me against the use of PCSEs in such a context. Anyone else is welcome to make a suggestion as well. C. REFERENCES: Beck N and Katz JN (1995) "What to Do (and Not to Do) With Time-Series Cross-Sectional Data", AMER POL SCI REV 89(3): 634-47. Beck N and Katz JN (1996) "Nuisance vs. Substance: Specifying and Estimating Time-Series Cross-Section Models", POL ANALYSIS 6(1): 1-34. Beck N (2001) "Time-Series Cross-Section Data: What Have We Learned in the Past Few Years", ANNU REV POL SCI 4: 271-93 CLIVE NICHOLAS |t: 0(44)191 222 5969 Politics Building |e: clive.nicholas@ncl.ac.uk School of Geography, |f: 0(44)870 126 2421 Politics & Sociology | University of | Newcastle-upon-Tyne | Newcastle-upon-Tyne | NE1 7RU | United Kingdom |http://www.ncl.ac.uk/geps * * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

- Prev by Date:
**Re: st: Autocorrelation and heteroskedasticity in panel models** - Next by Date:
**st: RE: beta-binomial regression, ebb.ado** - Previous by thread:
**Re: st: Autocorrelation and heteroskedasticity in panel models** - Next by thread:
**st: RE: beta-binomial regression, ebb.ado** - Index(es):

© Copyright 1996–2017 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |