Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: Outlier diagnostics for tobit (postestimation)
From
"Timo Beck" <[email protected]>
To
[email protected]
Subject
Re: st: Outlier diagnostics for tobit (postestimation)
Date
Fri, 19 Oct 2012 11:48:09 +0200
Dear Nick and Jay,
Thank you for your help.
@ Nick: I already checked cases for clear outliers, e.g., implausible values (and also simulated different versions). Further I used logarithmic transformation for specific variables which also helped. Still I wanted to use some "established" method for a further check (not for the main analysis, but rather as a robustness check). Not sure, what you mean by number 3) though.
@ Jay: Thank you for the hint, I will definitely look into that.
Once again quickly re my other question, maybe you also have an opinion on whether, just as a robustness test, I could fit OLS as an approximation of the tobit model and use outlier diagnostics thereafter and then simulate the tobit without these identified cases? Or would I be doing something completely wrong? According to Wooldridge a linear model is a good approximation for E(y) in a corner solution model which is what I am looking at. That's why I am thinking that way.
Thanks in advance again!
Timo
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/