In article <[EMAIL PROTECTED]>, sk <[EMAIL PROTECTED]> wrote: >Hi everyone,
>I have two structural equations of the following form: >Y1= a Y2+ b X1 >Y2= c Y1+ d X2 >I first etimated these two equations using OLS (i.e. ignoring >endogeneity). Next I estimated them using 2sls. Essentially what >happened was the endogeneous variables (Y2,Y1) changed signs (went >from positive significant to negative significant). I was wondering if >this was cause for concern. Does it reflect some underlying problems >with the data/ model? Or is this just an outcome of endogeneity? I >should mention 3sls produced coefficients with the same signs as 2sls. >Any insight would be much appreciated. If this is your model, there is no need to do anything that difficult; just use X2 as the instrumental variable for the first equation, and X1 for the second, or just run the regression of Y1 and Y2 on X1 and X2 and transform these regression equations to the desired form. This is what 2sls and 3sls approximate when X1 and X2 have more than one element. But in a just identified model, it is not necessary to approximate. OLS is appropriate for prediction ONLY; that is, if you will get the values of Y2 and X1, and what to predict Y1 from those, use OLS. It can be far off when it comes to the structural equations. -- This address is for information only. I do not claim that these views are those of the Statistics Department or of Purdue University. Herman Rubin, Department of Statistics, Purdue University [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
