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 <[email protected]>:
> 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
> [email protected]
>
> 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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