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Re: st: RE: RE: RE: RE: Autocorrelation test for pooled cross section data
From
Scott Merryman <[email protected]>
To
[email protected]
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
<[email protected]> 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
>
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