Dear Bruno, It seems that you are running a regresion with boht logarea and yhat1, however, gretl drops one of the variable because they collinear. That is right given that correlation is 99.93%
abertura logrendpc logarea yhat1
1.0000 0.1402 -0.6693 0.6698 abertura
1.0000 -0.1715 0.2093 logrendpc
1.0000 -0.9993 logarea
1.0000 yhat1
Now, your question is why you have a different dropped variable if you
change the order of the regressors, right? I am not sure why that is the
case, but it happens also in other packages. I remember similar issue in
Stata, when you have a different dropped variable if you use a different
command, but forcing to apply the same procedure. For example comparing OLS
con IV (but with trivial instruments).
Although, I don't have the question I think is not a serious problem. If 2
variables are highly correlated then any of those can be used. Indeed, many
times you could cut down your regressor into principal components to avoid
collinearity. Moreover, yhat1 is predicted variable from a previous model
and it is likely that logarea (or some similar variable) is a relevant in
that model.
Best, Rodrigo.
2012/10/4 Henrique Andrade <henrique.coelho(a)gmail.com>
> Dear Bruno,
>
> The problem is simple: the variable "logarea" is not equal to "yhat1".
>
> logarea yhat1
> 1 13.73169 17.32861
> 2 13.88510 16.59191
> 3 14.90278 9.24835
> 4 10.38514 43.42590
> 5 5.48064 80.59877
> 6 10.92590 37.84531
> ...
>
> Um abraço,
> Henrique
>
> _______________________________________________
> Gretl-users mailing list
> Gretl-users(a)lists.wfu.edu
> http://lists.wfu.edu/mailman/listinfo/gretl-users
>
Dear Bruno,
It seems that you are running a regresion with boht logarea and yhat1, however, gretl drops one of the variable because they collinear. That is right given that correlation is 99.93%
abertura logrendpc logarea yhat1
1.0000 0.1402 -0.6693 0.6698 abertura
1.0000 -0.1715 0.2093 logrendpc
1.0000 -0.9993 logarea
1.0000 yhat1
1.0000 0.1402 -0.6693 0.6698 abertura
1.0000 -0.1715 0.2093 logrendpc
1.0000 -0.9993 logarea
1.0000 yhat1
Now, your question is why you have a different dropped variable if you change the order of the regressors, right? I am not sure why that is the case, but it happens also in other packages. I remember similar issue in Stata, when you have a different dropped variable if you use a different command, but forcing to apply the same procedure. For example comparing OLS con IV (but with trivial instruments).
Although, I don't have the question I think is not a serious problem. If 2 variables are highly correlated then any of those can be used. Indeed, many times you could cut down your regressor into principal components to avoid collinearity. Moreover, yhat1 is predicted variable from a previous model and it is likely that logarea (or some similar variable) is a relevant in that model.
Best, Rodrigo.
2012/10/4 Henrique Andrade <henrique.coe...@gmail.com>
Dear Bruno,
The problem is simple: the variable "logarea" is not equal to "yhat1".
logarea yhat1
1 13.73169 17.32861
2 13.88510 16.59191
3 14.90278 9.24835
4 10.38514 43.42590
5 5.48064 80.59877
6 10.92590 37.84531
...
Um abraço,
Henrique
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