Re: st: How to get mean coefficients and t-statistics from several regressions

[Nick Cox <njcoxstata@gmail.com>]

-xtfmb- (SSC) does not return -e(r2_a)-.

To find that out takes two minutes running an example and checking the code.

A Stata expert is just someone who just gets into certain habits:
reading the help, looking at the code and running examples to check
what is going on.

I guess you need to clone the program and modify the cloned version to
work out adjusted R-square.

Nick
njcoxstata@gmail.com


On 30 July 2013 16:00, Nahla Betelmal <nahlaib@gmail.com> wrote:
> Thanks Nick for the reply, I tried that as well, but it gave me
> missing adjusted R-squared, although the value of R-squared was
> available. So I assumed that something wrong with this command,
> because the papers reported adjusted R-square.
>
> Why the adjusted R square is missing? It would be great if there is a
> way to get it.
>
> Also, I wonder if there is another way than statsby to get the mean of
> the regressions betas and mean adjusted R square and matched standard
> errors.
>
> Many thanks again
>
> Nahla
>
> On 30 July 2013 15:09, Nick Cox <njcoxstata@gmail.com> wrote:
>> Quite where the error is coming from is for you to tell us.
>>
>> Meanwhile this seems confused:
>>
>>  forval  i= 1/50 {
>>        statsby _b e(r2)  e(r2_a) , by(industry):xtfmb DV IV1 IV2 IV3 if
>>  industry== `i'
>> }
>>
>> Much of the point of the -statsby- command is that it does the looping
>> for you. It seems more likely that you want
>>
>> statsby _b e(r2)  e(r2_a) , by(industry): xtfmb DV IV1 IV2 IV3
>>
>> Nick
>> njcoxstata@gmail.com
>>
>>
>> On 30 July 2013 14:43, Nahla Betelmal <nahlaib@gmail.com> wrote:
>>> Hi Richard, thanks for your previous comments, and sorry for the delay
>>> in replying. I had to do some readings to see how researchers solve
>>> this issue.
>>>
>>> In industry-year context rather than firm-year context, authors seem
>>> to report mean of the mean rather than just Fama-MacBeth  time series
>>> mean.
>>>
>>> first they perform Fama-MacBeth on each industry alone to get the time
>>> series mean . In other words, they perform cross-sectional  on the
>>> firms-years observations in each industry to produce  time series mean
>>> of each industry. This could be easily obtained by the following
>>> Fama-MacBeth command available in Stata:
>>>
>>> tsset firm_id year
>>>
>>> forval  i= 1/50 {
>>>     xtfmb DV IV_1 IV_2 IV_3 if  industry== `i'
>>> }
>>>
>>> Therefore, there will be 50  time series mean betas, 50 mean R-square
>>> for the 50 industries I have. This is easy to execute.
>>>
>>> The second stage is to take the mean of these 50 time series means
>>> beta and the mean of these 50 means R-square, and of course the
>>> standard error and the t-stat of mean of the mean betas.
>>>
>>> In this way, they can obtain the time series mean across industries
>>> (rather than firms).
>>>
>>> Unfortunately, due to my humble knowledge with Stata, I have not
>>> figured out the command of how to get stage two (i.e. mean of the mean
>>> betas and matched standard error). I tried the following but there is
>>> an error
>>>
>>> forval  i= 1/50 {
>>>       statsby _b e(r2)  e(r2_a) , by(industry):xtfmb DV IV1 IV2 IV3 if
>>>  industry== `i'
>>> }
>>>
>>> collapse (mean) _b_cons _b_IV1 _b_IV2  _b_IV3  _eq2_stat_1 _eq2_stat_2///
>>>  (semean) _se_cons = _b_cons _se_IV1 = _b_IV1  _se_IV2 = _b_IV2
>>> _se_IV3 = _b_IV3
>>>
>>> foreach v in cons IV1 IV2 IV3 {
>>> generate _t_`v' = _b_`v' / _se_`v'
>>>  }
>>>
>>> I got error:
>>>
>>> no; data in memory would be lost
>>> r(4);
>>>
>>>
>>> If I remove  by(industry) in the first line of the loop , I got an error as well
>>>
>>> industry not found
>>> r(111);
>>>
>>>
>>> I would highly appreciate it if you can help me to figure out the
>>> right command. Also, I do hope this thread to be useful for other
>>> people who face this issue as well.
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