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# Re: st: Tests of overidentifying restrictions with -ivregress-

 From Roberto Pannico <[email protected]> To [email protected] Subject Re: st: Tests of overidentifying restrictions with -ivregress- Date Wed, 09 Oct 2013 18:15:11 +0200

```Hola Alfonso,
Actually I have done an endogeneity test of exo4 and this is the result:

Tests of endogeneity
Ho: variables are exogenous

Durbin (score) chi2(1)          =  13.8016  (p = 0.0002)
Wu-Hausman F(1,5731)            =  13.7747  (p = 0.0002)

So, it seems that technically the variable is endogenous. The "problem" is that theoretically this is impossible: exo4 is the amount of money that a country receives from European Union, while the dependent variable of the model is the level of support that a citizen give to European Union. And given that the amount of money that a country receives is not determined taking into account the level of support of its citizens (but the opposite is true), theoretically the regressor can not be endogenous.

Concerning your second questions, when I write

ivregress 2sls dep (endo endoXexo = instrument1 instrument2 instrument1#exo instrument2#exo) exo exo1 exo2 exo3 exo4, first

the command -ivregress- automatically uses all the regressors of the model as instrumental variables.
Finally, I am not sure I understand your last question. Why should I use the instruments as explanatory variables in the main model? in any case Stata does not allow me doing it. When I write the following model:

ivregress 2sls dep (endo endoXexo = instrument1 instrument2 instrument1#exo instrument2#exo) exo exo1 exo2 exo3 exo4 instrument1 instrument2 instrument1#exo instrument2#eco, first

Stata gives the following error message

equation not identified; must have at least as many instruments not in
the regression as there are instrumented variables

Any other suggestion?
Thank you again for your help
Roberto

----- Mensaje original -----
De: Alfonso S <[email protected]>
Fecha: Miércoles, Octubre 9, 2013 3:45 pm
Asunto: Re: st: Tests of overidentifying restrictions with -ivregress-

> Hola Roberto,
>
> my first thought is that exo4 may not be exogenous. Have you done a
> test of endogeneity? My second question would also be why don't you
> use all the exogenous variables you have as instruments, and the
> instruments you are using as explanatory variables as well?
>
> Best,
>
> Alfonso Sanchez-Penalver
>
>
>
> On Wednesday, October 9, 2013 7:47 AM, Roberto Pannico
> <[email protected]> wrote:
> Dear all,
> I need your help for interpreting some postestimation results of my
> instrumental variables model. I am using Stata 12.0 and the command
> -ivregress-. The sintax is the following:
>
> ivregress 2sls dep (endo endoXexo = instrument1 instrument2
> instrument1#exo instrument2#exo) exo exo1 exo2 exo3, first
>
> where dep is the dependent variable, endo is the endogenous
> regressor, exo is an exogenous regressor that I want to interact
> with the endogenous one, and exo1, exo2, exo3 are other exogenous
> regressors.
> After running this model I type -estat overid- and I obtain this
> result:
>
> Tests of overidentifying restrictions:
>
>   Sargan (score) chi2(2) =  .311939  (p = 0.8556)
>   Basmann chi2(2)        =  .310601  (p = 0.8562)
>
>
> This should mean that my instruments are not correlated with the
> error of the main regression and therefore they are valid. Now, I
> want to add an other exogenous regressor in the main regression,
> and for this reason I write:
>
> ivregress 2sls dep (endo endoXexo = instrument1 instrument2
> instrument1#exo instrument2#exo) exo exo1 exo2 exo3 exo4, first
>
> where exo4 is the new variable that I add to the model. The effect
> of this new factor on the dependent variable is statistically
> significant, and it also considerably  reduces the effect of endo.
> However, when I type again -estat overid-  the result is the
> following:
> Tests of overidentifying restrictions:
>
>   Sargan (score) chi2(2) =  14.1205  (p = 0.0009)
>   Basmann chi2(2)        =  14.0913  (p = 0.0009)
>
>
> This means that my instruments are not valid anymore. How it can be
> possible? The error term of the first model should incorporate also
> the effect of exo4. As far as I am aware, if my instruments are not
> correlated to it (the error term), they can not be correlated with
> the error term of the second model. I don't know how to interpret
> these results.....
> Any idea or suggestion?
> Thank you very much for help
> Roberto
>
>
>
>
>
>
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