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Ok, now I am able to do some kind of test, but I don't know if this is sufficient because the lags may be between several months and not the same lag for all observations. If i only do the FE-estimation with cluster, will this be a good way to control for potential autocorrelation? Also, as I have returns as dependent variable, I i believe that I have done what is normal to do for time series of stock prices to get a stationary process. What I want to find is whether trading based on different factors based on stock price and company specific factors will be statistical significant on the returns and may give excess returns.
1) I have a problem with xtset and I hope you can help me. I have to run a negative binomial regression because I have count data which has an exponential distribution.
When I was trying "xtset ID Year" (year range from 2005 to 2013), STATA called me that I have gaps but i don´t have any gaps in my data. Do you know what happened?
I have 93 IDs and 709 Years, unbalanced panel.
2) When I am trying xtset ID Year and I will include time dummies, is it possible or complicated? Or would it be better with xtset ID and then include time dummies?
3) I have 20 sector dummies and that could be a problem for my regressions. Up to now I have two levels (93 company and 709 observations) and 20 sector dummies. Could be a solution that I include a third level?
1 sector-ID
2 company-ID (93 IDs)
3 observations
Ok, now I am able to do some kind of test, but I don't know if this is sufficient because the lags may be between several months and not the same lag for all observations. If i only do the FE-estimation with cluster, will this be a good way to control for potential autocorrelation? Also, as I have returns as dependent variable, I i believe that I have done what is normal to do for time series of stock prices to get a stationary process. What I want to find is whether trading based on different factors based on stock price and company specific factors will be statistical significant on the returns and may give excess returns.
I suggest looking at the literature. If everyone just uses a static fixed effects regressions when trying to predict returns, you're good to go.
1) I have a problem with xtset and I hope you can help me. I have to run a negative binomial regression because I have count data which has an exponential distribution.
When I was trying "xtset ID Year" (year range from 2005 to 2013), STATA called me that I have gaps but i don´t have any gaps in my data. Do you know what happened?
I have 93 IDs and 709 Years, unbalanced panel.
2) When I am trying xtset ID Year and I will include time dummies, is it possible or complicated? Or would it be better with xtset ID and then include time dummies?
3) I have 20 sector dummies and that could be a problem for my regressions. Up to now I have two levels (93 company and 709 observations) and 20 sector dummies. Could be a solution that I include a third level?
1 sector-ID
2 company-ID (93 IDs)
3 observations
Thank you and best regards,
Marcus
Please create a separate topic for this, and include a data sample using -dataex-.
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