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st: Regressor with too many zeros


From   "joe jacob" <[email protected]>
To   [email protected]
Subject   st: Regressor with too many zeros
Date   Thu, 18 Sep 2003 05:36:44 +0000

Dear all,

I am estimating the effect of export orientation (exports/sales) by firms on their learning efforts from imported inputs. I use an -ivtobit- model due to the censored natured of the learning variable and the endogenous nature of the export intensity variable. There are a few other explanatory variables also, which capture the level of skill and technological capability of the firm. The problem is that there are a large number of non-exporting firms (hence a zero value for many observations of the export intensity variable). My estimation did not produce a significant positive relation between export intensity and learning. BUT when I added an export dummy (1 for exporters and 0 for non-exporters) the variable became highly significant. (both export intensity and export dummy were instrumented) However, the export dummy became significant Negatively with a higher coefficient value. This latter result seems very counter-intuitive.

Put simply, the question is thus, when the key regressor has too many zeros (as my export intensity variable has), how do we tackle the problem of non-variability? Simply excluding zero-valued observations don't seem right?

Please comment.

Thanks,

Joe

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