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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