Re: st: Is my parameter significant or not?

[Scott Merryman <scott.merryman@gmail.com>]

The two specifications are the same though to evaluate the
coefficients in first specification you need to add the main effect to
the interactions.

For example:

webuse grunfeld,clear
areg invest L.mval com#cL.mval, ab(com)
lincom _b[2.company#cL.mvalue] +  _b[L.mvalue]
qui areg invest  com#cL.mval, ab(com)
disp _b[2.company#cL.mvalue] "  " _se[2.company#cL.mvalue]


Scott


On Wed, Aug 21, 2013 at 10:52 AM, Herman Haugland
<herman.haugland@gmail.com> wrote:
> Hi,
>
> I would appreciate someone could provide me an answer to the following question:
>
> I am estimating the following model:
>
> . areg beta L.lev group#cL.lev i.year, absorb(group)
>
> Group is a categorical variable: 1, 2
> Lev is a continuous variable
> Year are year effects
> Group are fixed effects
>
> Under that specification of the model, I get the following results:
>
> . areg beta L.lev group#cL.lev i.year, absorb(group)
>
> __________________________________________________________________
>
> Linear regression, absorbing indicators           Number of obs   =        285
>                                                   F(  17,    266) =       4.04
>                                                   Prob > F        =     0.0000
>                                                   R-squared       =     0.3540
>                                                   Adj R-squared   =     0.3103
>                                                   Root MSE        =     0.3038
>
> ------------------------------------------------------------------------------
>                       beta |       Coef.       Std. Err.      t
>    P>|t|        [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>                         lev |
>                        L1. |    .059685  |  .014907  |   4.00 |  0.000
>    [ .0303342    .0890358]
>
>        group#cL.lev |
>                          2  |  -.0451045   .0178834    -2.52   0.012
>  -.0803155   -.0098936
>
> ____________________________________________________________________
>
> What I would like to highlight from here, is the fact that the P value
> for group#cLlev 2 is significant at the 5% level.
>
>
> If I run the same model in a different way, like this:
>
> ____________________________________________________________
>
> . areg beta group#cL.lev i.year, absorb(group)
>
> Linear regression, absorbing indicators           Number of obs   =        285
>                                                   F(  17,    266) =       4.04
>                                                   Prob > F        =     0.0000
>                                                   R-squared       =     0.3540
>                                                   Adj R-squared   =     0.3103
>                                                   Root MSE        =     0.3038
>
> ------------------------------------------------------------------------------
>               beta |      Coef.        Std. Err.      t         P>|t|
>        [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> group#cL.lev |
>                  1  |    .059685    .014907       4.00     0.000    [
> .0303342    .0890358]
>                  2  |   .0145805   .0114004     1.28     0.202
> [-.0078661     .037027]
>
> ________________________________________________________________
>
>
> The P value for group 2 is not significant at the 5% level.
>
>
> So the question is, which P-value should I consider as correct?  In
> other words, is my parameter estimate significant or not?
>
> (Please note that I get exactly the same parameter estimates from both
> methods, but the associated P-values and t-values change).
>
>
>
> Thank you for your consideration.
>
>
>
>
> Med vennlig hilsen / Best regards,
>
> Herman Haugland
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