Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down at the end of May, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: IV with robust covariance matrx in case of (H)ACSC standard errors (heteroscedasticity, autocorrelation and spatial corrlelation)


From   Garloff Alfred <Alfred.Garloff2@iab.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: IV with robust covariance matrx in case of (H)ACSC standard errors (heteroscedasticity, autocorrelation and spatial corrlelation)
Date   Thu, 12 May 2011 19:13:45 +0200

Hi,

I am trying to implement an estimator for the following problem: Standard errors are allowed to be correlated over time and over space (across regions, which are the observation units), not necessarily to be heteroscedastic. In addition, one RHS variable (basically the only RHS variable besides time and region dummies) is endogenous and I have presumably a good instrument. 

So, here is the question: How to implement this all at a time. In my mind, 

- ivreg2, hac bw() cannot handle the case of spatial correlation
- xtscc, fe cannot handle an endogenous variable

Probably, an approach like doing the first stage by hand and using the projected values in the second stage together with xtscc is feasible. But then, standard errors have to be corrected and I am not able to transfer the correction from a standard "2-stage estimated by hand IV" to the actual case.

Thanks to anyone considering this question!

Alfred Garloff

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index