Riti--
This looks a lot like a homework question, disallowed by the Statalist
FAQ, but I think you can find an answer reading
http://www.ats.ucla.edu/stat/stata/webbooks/reg/chapter3/statareg3.htm
On 10/23/07, [email protected] <[email protected]> wrote:
> Dear STATA users,
>
> When I use the following to estimate a difference-in-difference model:
>
> Score = constant + a0bonus + a1bonusbaseline + a2baseline + e
>
> score bonus control baseline bonusbaseline controlbaseline
> 0.4 1 0 1 1 0
> 0.2 1 0 1 1 0
> 0.1 1 0 0 0 0
> 0.9 1 0 0 0 0
> 0.5 0 1 1 0 1
> 0.6 0 1 1 0 1
> 0.7 0 1 0 0 0
> 0.76 0 1 0 0 0
> *bonusbaseline=bonus x baseline
> ** controlbaseline=control x baseline
>
> The OLS estimates are:
> Number of obs = 8
> Source SS df MS F( 3, 4) = 0.72
> Model 0.1876 3 0.0625 Prob > F = 0.5895
> Residual 0.3468 4 0.0866 R-squared = 0.351
> Total 0.5344 7 0.0763 Adj R-squared = -0.1357
> Root MSE = 0.2944
> score Coef. Std. Err. t P>t [95% ConfInterval]
> bonus -0.23 0.2944 -0.78 0.478 -1.0472 0.5875
> bonusbasel~e -0.02 0.4164 -0.05 0.964 -1.1761 1.1361
> baseline -0.18 0.2944 -0.61 0.574 -0.9975 0.6375
> _cons 0.73 0.2082 3.51 0.025 0.15192 1.3080
>
> If instead I estimate:
> Score = constant + b0bonus + b1bonusbaseline + b2controlbaseline + u
>
> The OLS estimates are:
> Number of obs = 8
> Source SS df MS F( 3, 4) = 0.72
> Model 0.1876 3 0.0625 Prob > F = 0.5895
> Residual 0.3468 4 0.0866 R-squared = 0.351
> Total 0.5344 7 0.0763 Adj R-squared = -0.1357
> Root MSE = 0.2944
> score Coef. Std. Err. t P>t [95% ConfInterval]
> bonus -0.23 0.2944 -0.78 0.478 -1.0475 0.5875
> bonusbasel~e -0.2 0.2944 -0.68 0.534 -1.0175 0.6175
> controlbas~e -0.18 0.2944 -0.61 0.574 -0.9975 0.6375
> _cons 0.73 0.2082 3.51 0.025 0.1519 1.3080
>
> As seen above, I get the same coefficients and standard errors for
> bonus and _cons in the two regressions. Moreover, the coefficient and
> standard error for controlbaseline are the same as baseline in the
> first regression. Both sets of regressions have the same goodness of
> fit measures. Both sets also yield the same predicted means and
> marginal effects. However, the coefficients for bonusbaseline are
> different across regressions.
>
> Question: What explains the difference in the coefficients for
> bonusbaseline across regression models?
>
> Thanks,
> Riti
>
*
* 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/
