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re:Re: Re: st: RE: dfuller: why do I get different results?

From   Christopher Baum <>
To   "" <>
Subject   re:Re: Re: st: RE: dfuller: why do I get different results?
Date   Sat, 19 Nov 2011 10:42:52 -0500


I still need the formal statistical test - for a research paper a
general plot will not be sufficient.

BTW: I just ran manually the first 10 panels. It is not a
representative sample, but as you can see below indeed, in most of
them the unit-root hypothesis was not rejected at the 1% significance

Unit root tests have notoriously low power with < 100 observations -- that's why we have panel unit root tests.
Three rejections at 5% out of 10 samples suggests that "most" might be I(1), but then a df test with no constant nor trend is a queer bird indeed. The process you are modeling has to make sense under both null and alternative hypotheses for the test to be valid. A bit of algebra shows that a DF regression without a constant implies that the mean of Y is the mean of epsilon == 0 under the alternative hypothesis of stationarity. If your data in levels do not have a mean of zero, this model is incapable of reproducing the data with any choice of ]beta < 0, and so the test is flawed.


Kit Baum   |   Boston College Economics & DIW Berlin   |
                             An Introduction to Stata Programming  |
  An Introduction to Modern Econometrics Using Stata  |

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