Dear Satalist users
I am estimating a quantile regression for various quantiles with about
6000 individual observations and ca. 30 explanatory variables. Since I
have both aggregate(state) and individual level data combined, I thought
it might be better to have bootstrapped standard errors.
One economterician told me that I should use about 1000 replications,
but, on the other hand, I read that for bootstrapping only standard
errors but not the coefficients in a linear model (?) about 100
replications would suffice.
So my first question is: do I need 1000 replications ?
Second, I observed that the bootstrapping procedure does not converge
(with 1000 rep.). Stata then interrupts the bootstrapping process and
starts from the beginning again.
I have already used the wlsiter option to have more repetitions of the
first stage of the regression (now: 20), when a weighted estimation is
carried out. Increasing the number in the wlsiter option should solve
convergence problems - but is does not in my case.
How can I make this animal converge ?
(This problem is a bit mitigated when I use a smaller number of
replications (e.g. 100) but still tendes to persist)
Thanks a lot
Justina
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
