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st: RE: winsorize the effect of outliers (?)
Maarten Buis has already drawn attention to relevant
stuff. But other comments are possible:
1. Only those who recognise the reference "Cleary (1999)"
can say precisely what he or she did. I guess that -2
and 2 means winsorize 2 at the bottom and 2 at the top
but I don't then know what 1 and 0 means. I suspect
a typo there.
2. On the evidence here different amounts of winsorizing
were applied to different variables. If that is
based on inspection of the data any P-values that follow
are suspect, from at least one point of view.
3. Winsorizing is a kind of ad hoc method some 50 years
old. Aren't there now better ways of getting model fits
robust to outliers?
P.S. I did write -winsorize-, but I never use it. Someone
asked how to do it....
> In an working paper I read: "To avoid the effect of outliers,
> we winsorized the observations [time series panel data]
> following Cleary (1999). The cutoff value are -2 and 2 for
> "var1[_t-1]", -5 and 5 per "var 2[_t-1]", 1 and 0 for "var3".
> Note: [_t-1] means a value taken in (t-1).
> Given these three variables (var1, var2 and var3), could
> somebody tell me how to "winsorize" this way? Thank you.
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