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Re: st: RE: Re: RE: questions about stationarity test results using IPSHIN


From   Jeannette Wicks-Lim <janetlim@econs.umass.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Re: RE: questions about stationarity test results using IPSHIN
Date   Thu, 18 Nov 2004 18:38:53 -0500

Hi Nick, 
Thanks for clarifying your response. What I find puzzling is that the lngap is 
behaving relatively similarly to lnq5 rather than lnmin1, since lnmin1 is 
nonstationary. Isn't it unusual for a ratio of a nonstationary and stationary  
variable to be stationary?
Thanks!
J
-- 
Jeannette Wicks-Lim
Department of Economics
University of Massachusetts, Amherst
Amherst, MA 01003


Quoting Nick Cox <n.j.cox@durham.ac.uk>:

> My comment is very simple: put another way,  
> on the t-bar statistics -lnq5- and -lngap- 
> are behaving relatively similarly, whereas -lnmin1- 
> differs from both. No more than that, and no 
> less. 
> 
> The help for -ipshin- makes it clear that
> to judge significance you need to get 
> results from the original paper. 
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> Jeannette Wicks-Lim
>  
> > Maybe I'm misunderstanding the results ( I am a real novice 
> > re: time series 
> > issues). I thought that the t-bar being further from zero for lngap 
> > indicates that it is stationary (more negative then the cv1). Is that 
> > incorrect?
> 
> Nick Cox
>  
> > > Your commentary seems at odds with your results
> > > in that t-bar is further from zero for -lngap-
> > > than for the other variables.
> 
> Jeannette Wicks-Lim
> 
> > >> I've conducted the IPSHIN test on two variables, one of which
> > >> appears to be
> > >> nonstationary (log of the minimum wage, or "lnmin1") and the
> > >> other appears
> > >> to be stationary (log of the 5th wage percentile, or "lnq5").
> > >> When I create
> > >> a third variable (log of 5th wage percentile - log of minimum wage,
> > >> or"lngap"), the IPSHIN test indicates that it is stationary.
> > >> How can it be
> > >> that the ratio of a stationary and nonstationary variable is
> > >> stationary?
> > >> (Some background info: the panels in this dataset are US
> > >> states -- all 50,
> > >> the time points are 6 month intervals over 20 years).
> > >>
> > >> Here are my results:
> > >>
> > >> . ipshin lnmin1 if gestcen~=53, lags(17) trend
> > >>
> > >> Im-Pesaran-Shin test for cross-sectionally demeaned lnmin1
> > >> Deterministics chosen: constant & trend
> > >>
> > >> t-bar test, N,T = (50,40)         Obs = 1593
> > >> Augmented by 17 lags (average)
> > >>
> > >>     t-bar     cv10      cv5       cv1   W[t-bar]    P-value
> > >>    -1.456   -2.320    -2.360    -2.440        .         .
> > >>
> > >> . ipshin lnq5 if gestcen~=53, lags(17) trend
> > >>
> > >> Im-Pesaran-Shin test for cross-sectionally demeaned lnq5
> > >> Deterministics chosen: constant & trend
> > >>
> > >> t-bar test, N,T = (50,40)         Obs = 1593
> > >> Augmented by 17 lags (average)
> > >>
> > >>     t-bar     cv10      cv5       cv1   W[t-bar]    P-value
> > >>    -3.087   -2.320    -2.360    -2.440        .         .
> > >>
> > >> . ipshin lngap if gestcen~=53, lags(17) trend
> > >>
> > >> Im-Pesaran-Shin test for cross-sectionally demeaned lngap
> > >> Deterministics chosen: constant & trend
> > >>
> > >> t-bar test, N,T = (50,40)         Obs = 1593
> > >> Augmented by 17 lags (average)
> > >>
> > >>     t-bar     cv10      cv5       cv1   W[t-bar]    P-value
> > >>    -3.585   -2.320    -2.360    -2.440        .         .
> 
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