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Re: st: comparing equality of coefficients from two subsamples
From
Mario Jose <[email protected]>
To
[email protected]
Subject
Re: st: comparing equality of coefficients from two subsamples
Date
Wed, 20 Feb 2013 22:10:42 +0000
Thank you Rebecca for the links, they were very useful to understand
the previous Jay's comment.
I have implemented the strategy of Bill Gould (allowing for different
variances), but it appeared the message of error "weight must be
constant within id"... Anyway I do not want to introduce interactions
with all independent variables but to only one.
Below I expose what the specific problem I have.
I have a panel sample of firms, and in the middle of the period
(2004) it was implemented by the government a specific fiscal
measure. I want to test whether this measure had impacts on the
profits reported by firms. As I think that the measure had impacts in
a specific subsample of firms, I divided the sample in two subsamples
- group1 group2 (splitted according the debt/assets ratio of firms).
I run the model for the two groups separately:
xtreg, Y x1 control1 control2 ... i.pos i.pos#c.x1 if group==1, fe
xtreg, Y x1 control1 control2 ... i.pos i.pos#c.x1 if group==2, fe.
(pos is binary taking value 1 for years after the implementation of the policy)
and I obtain the following estimates for group 1 and 2, respectively:
*******output excerpt************
-----------------------------------------------------------------------------------
| Robust
Y | Coef. Std. Err. t P>|t| [95%
Conf. Interval]
------------------+----------------------------------------------------------------
x1 | -2.053274 .5641935 -3.64 0.000 -3.159248
-.9473006
control1 | .5904103 .0267907 22.04 0.000 .5378933 .6429273
control2 | .0947558 .0233539 4.06 0.000 .0489758 .1405358
... | -.0234459 .2617354 -0.09 0.929 -.5365189
.4896271
year dum.. |
1.pos | -.5814072 .1512517 -3.84 0.000 -.877902 -.2849124
1.pos#c.x1 | 1.256448 .4183398 3.00 0.003 .4363875 2.076508
_cons | -6.099231 1.766059 -3.45 0.001 -9.561191 -2.637272
------------------+----------------------------------------------------------------
sigma_u | 2.1744991
sigma_e | .77651905
rho | .88690051 (fraction of variance due to u_i)
-----------------------------------------------------------------------------------
-----------------------------------------------------------------------------------
| Robust
Y | Coef. Std. Err. t P>|t| [95%
Conf. Interval]
------------------+----------------------------------------------------------------
x1 | -2.047585 .6997248 -2.93 0.003 -3.41921
-.6759593
control1 | .4552402 .0232387 19.59 0.000 .4096868 .5007936
control2 | .028412 .0110095 2.58 0.010 .0068306 .0499933
...
year dum .. |
1.pos | -.4291118 .1817098 -2.36 0.018 -.7853059 -.072917
1.pos#c.x1 |.6220617 .5078439 1.22 0.221 -.3734318 1.617555
cons | -7.341474 1.606579 -4.57 0.000 -10.49075 -4.192201
------------------+----------------------------------------------------------------
sigma_u | 2.4369753
sigma_e | .70849863
rho | .92206421 (fraction of variance due to u_i)
-----------------------------------------------------------------------------------
**********end of excerpt*************
These results are in the direction of the predicted, but when I pooled
the sample for me to compare the coefs, the estimates appear to be
significantly different. They are as follows:
*******output excerpt************
--------------------------------------------------------------------------------------------------
| Robust
Y | Coef. Std. Err. t
P>|t| [95% Conf. Interval]
---------------------------------+----------------------------------------------------------------
x1 | -1.601963 .5324727 -3.01
0.003 -2.645681 -.5582453
control1 | .5435240 .0232387 19.59 0.000
.4096868 .5007936
control2 | .03976 .0110095 2.58 0.010
.0068306 .0499933
... |
year dum .. |
1.pos | -.382873 .1487651 -2.57 0.010
-.6744726 -.0912734
pos#c.x1 | .5273469 .4331443 1.22 0.223
-.3216739 1.376368
1.group | .2575 .175552 1.47 0.142
-.0866054 .60
1.group#c.x1 | -.8550352 .5470408 -1.56 0.118
-1.927308 .217238
1.group#pos | -.2539677 .1681945 -1.51 0.131
-.5836514 .075716
1.goup#pos#c.x1 | .8948809 .528096 1.69 0.090
-.140258 1.93002
_cons | -6.485282 1.161574 -5.58 0.000
-8.762123 -4.208441
---------------------------------+----------------------------------------------------------------
sigma_u | 2.2954577
sigma_e | .76123454
rho | .90092029 (fraction of variance due to u_i)
**********end of excerpt*************
Do you find something wrong with the last equation?
I would appreciate any help.
Best
MJ
2013/2/20 Rebecca Pope <[email protected]>:
> Jay has given you important advice as it pertains to the group
> residual variances.
> You are correct that Wooldridge gives an explanation of interaction
> terms. He also notes that a fully interacted model (as I assume you
> will be estimating since your initial post seemed to suggest that you
> expect different coefficients for all covariates for males and
> females) assumes group error homogeneity (pg 245 of the 4th ed).
> Unfortunately, there doesn't appear to be any discussion, at least in
> that section, of how to address heteroskedasticity between the groups.
> I didn't read through the rest of the book
> You might want to take a look at this FAQ by Bill Gould:
> http://www.stata.com/support/faqs/statistics/pooling-data-and-chow-tests/
>
> And these slides from a talk by Bobby Gutierrez:
> http://www.stata.com/meeting/fnasug08/gutierrez.pdf
>
> Only you can see your data and judge whether the constrained variance
> model is appropriate or not. I wouldn't just dismiss the issue out of
> hand though.
>
> Rebecca
>
> On Wed, Feb 20, 2013 at 5:47 AM, Mario Jose <[email protected]> wrote:
>> Thanks you for comments. Testing for equality of coefficients from
>> different subsamples, as suggested by Marteen, can be solved by
>> interactions.
>> There is an excellent explanation of the procedure in Wooldridge:
>> Introd.Econometrics ModernApproach; pp. 243-246 and pp. 449-450 and in
>> the following link:
>> http://www.stata.com/support/faqs/statistics/chow-tests/
>>
>> Best,
>> MJ
>>
>> 2013/2/18 JVerkuilen (Gmail) <[email protected]>:
>>> As someone else indicated, your syntax is odd.
>>>
>>> The main question I have is whether you want to allow for different
>>> group residual variances. If not, interaction. If so, then I guess the
>>> easiest approach would be -suest-.
>>>
>>> On Mon, Feb 18, 2013 at 11:15 AM, Mario Jose <[email protected]> wrote:
>>>> Dear Statalisters,
>>>>
>>>> I have tryed to solve the question below, searching for help in the
>>>> Stata Archiv without too much success...
>>>>
>>>> I have estimated a fixed effects linear regression for two different
>>>> groups on my sample (say, sex male/female), using this strategy:
>>>> xtreg dv iv, if sex==male
>>>> xtreg dv iv, if sex==female
>>>>
>>>> I am interested in testing whether or not the coefficient b1 is
>>>> identical to each other in the two subsamples.
>>>>
>>>> I would really appreciate any help.
>>>> Regards
>>>> MJ
>>>> *
>>>> * 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/
>>>
>>>
>>>
>>> --
>>> JVVerkuilen, PhD
>>> [email protected]
>>>
>>> http://lesswrong.com/
>>>
>>> "Everybody loves progress but nobody likes change." ---Fortune cookie, 1/13/13.
>>> *
>>> * 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/
>>
>> 2013/2/18 JVerkuilen (Gmail) <[email protected]>:
>>> As someone else indicated, your syntax is odd.
>>>
>>> The main question I have is whether you want to allow for different
>>> group residual variances. If not, interaction. If so, then I guess the
>>> easiest approach would be -suest-.
>>>
>>> On Mon, Feb 18, 2013 at 11:15 AM, Mario Jose <[email protected]> wrote:
>>>> Dear Statalisters,
>>>>
>>>> I have tryed to solve the question below, searching for help in the
>>>> Stata Archiv without too much success...
>>>>
>>>> I have estimated a fixed effects linear regression for two different
>>>> groups on my sample (say, sex male/female), using this strategy:
>>>> xtreg dv iv, if sex==male
>>>> xtreg dv iv, if sex==female
>>>>
>>>> I am interested in testing whether or not the coefficient b1 is
>>>> identical to each other in the two subsamples.
>>>>
>>>> I would really appreciate any help.
>>>> Regards
>>>> MJ
>>>> *
>>>> * 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/
>>>
>>>
>>>
>>> --
>>> JVVerkuilen, PhD
>>> [email protected]
>>>
>>> http://lesswrong.com/
>>>
>>> "Everybody loves progress but nobody likes change." ---Fortune cookie, 1/13/13.
>>> *
>>> * 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/
>> *
>> * 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/
>
>
>
> On Wed, Feb 20, 2013 at 5:47 AM, Mario Jose <[email protected]> wrote:
>> Thanks you for comments. Testing for equality of coefficients from
>> different subsamples, as suggested by Marteen, can be solved by
>> interactions.
>> There is an excellent explanation of the procedure in Wooldridge:
>> Introd.Econometrics ModernApproach; pp. 243-246 and pp. 449-450 and in
>> the following link:
>> http://www.stata.com/support/faqs/statistics/chow-tests/
>>
>> Best,
>> MJ
>>
>> 2013/2/18 JVerkuilen (Gmail) <[email protected]>:
>>> As someone else indicated, your syntax is odd.
>>>
>>> The main question I have is whether you want to allow for different
>>> group residual variances. If not, interaction. If so, then I guess the
>>> easiest approach would be -suest-.
>>>
>>> On Mon, Feb 18, 2013 at 11:15 AM, Mario Jose <[email protected]> wrote:
>>>> Dear Statalisters,
>>>>
>>>> I have tryed to solve the question below, searching for help in the
>>>> Stata Archiv without too much success...
>>>>
>>>> I have estimated a fixed effects linear regression for two different
>>>> groups on my sample (say, sex male/female), using this strategy:
>>>> xtreg dv iv, if sex==male
>>>> xtreg dv iv, if sex==female
>>>>
>>>> I am interested in testing whether or not the coefficient b1 is
>>>> identical to each other in the two subsamples.
>>>>
>>>> I would really appreciate any help.
>>>> Regards
>>>> MJ
>>>> *
>>>> * 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/
>>>
>>>
>>>
>>> --
>>> JVVerkuilen, PhD
>>> [email protected]
>>>
>>> http://lesswrong.com/
>>>
>>> "Everybody loves progress but nobody likes change." ---Fortune cookie, 1/13/13.
>>> *
>>> * 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/
>>
>> 2013/2/18 JVerkuilen (Gmail) <[email protected]>:
>>> As someone else indicated, your syntax is odd.
>>>
>>> The main question I have is whether you want to allow for different
>>> group residual variances. If not, interaction. If so, then I guess the
>>> easiest approach would be -suest-.
>>>
>>> On Mon, Feb 18, 2013 at 11:15 AM, Mario Jose <[email protected]> wrote:
>>>> Dear Statalisters,
>>>>
>>>> I have tryed to solve the question below, searching for help in the
>>>> Stata Archiv without too much success...
>>>>
>>>> I have estimated a fixed effects linear regression for two different
>>>> groups on my sample (say, sex male/female), using this strategy:
>>>> xtreg dv iv, if sex==male
>>>> xtreg dv iv, if sex==female
>>>>
>>>> I am interested in testing whether or not the coefficient b1 is
>>>> identical to each other in the two subsamples.
>>>>
>>>> I would really appreciate any help.
>>>> Regards
>>>> MJ
>>>> *
>>>> * 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/
>>>
>>>
>>>
>>> --
>>> JVVerkuilen, PhD
>>> [email protected]
>>>
>>> http://lesswrong.com/
>>>
>>> "Everybody loves progress but nobody likes change." ---Fortune cookie, 1/13/13.
>>> *
>>> * 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/
>> *
>> * 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/
> *
> * 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/
*
* 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/