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From |
Scott Merryman <scott.merryman@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: RE: RE: RE: Autocorrelation test for pooled cross section data |

Date |
Wed, 29 Sep 2010 11:28:24 -0500 |

-xtregar, lbi- report the Baltagi-Wu locally best invariant (LBI) test statistic that rho = 0 and a modified version of the Bhargava, Franzini, Narendranathan (1982) Durbin-Watson statistic be calculated and reported. . webuse grunfeld,clear . xtregar inve mval, fe lbi (output omitted) modified Bhargava et al. Durbin-Watson = .50577251 Baltagi-Wu LBI = .82334942 The BFN Durbin Watson is also easy to calculate: . qui xtreg inve mval, fe . predict double e,e . gen double bfn = sum((e- l.e)^2)/sum(e^2) . cl bfn in l, noobs bfn .5057725 The original BFN paper supplies upper and lower bounds for Durbin Watson statistic. For a large number of cross sections, if it less than 2 then it would indicate positive serial correlation. See: Bhargava, A., Franzini, and W. Narendranathan. 1982. "Serial correlation and fixed effects model." Review of Economic Studies 49, p. 533 - 549. Scott On Wed, Sep 29, 2010 at 10:37 AM, Elizabeth Dhuey <elizabeth.dhuey@utoronto.ca> wrote: > Due to the length of my time period, I have some concern regarding > correlated errors over time. I have plotted the residuals and see some > evidence of correlation over time. > > However, my attempt to find a formal test that produces a p-value is based > on a request from a journal referee. My main issue is that I can't seem to > find any formal test that is appropriate for pooled cross sectional data. My > current thought is to calculate a durbin-watson statistic for each state and > report the distribution of the statistic. However, I suspect that someone > has already formalized a produce for this kind of data structure. > > Elizabeth > * * 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/

**References**:**st: RE: Autocorrelation test for pooled cross section data***From:*Nick Cox <n.j.cox@durham.ac.uk>

**st: RE: RE: RE: Autocorrelation test for pooled cross section data***From:*Nick Cox <n.j.cox@durham.ac.uk>

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