Joe,
Quoting joe jacob <[email protected]>:
> Chris and others,
>
> I should apologise for not describing the variables in the first
> mail. Let
> me explain.
>
> I have an establishment level data set for about 8 years (100,000
> plus
> observations)
>
> The key equation of interest is
> IRD= EXPINT+ drd+ droy+ skill+ outshare+gov+ forg /*Eqn 1.*/
>
> where, IRD captures learning efforts from embodied R&D (derived from
>
> sectoral R&D stock of OECD countries and distributed across
> establishments
> of a developing country) EXPINT is the export intensity
> variable.(Other
> variables are basically control variables.) Since this variable
> (EXPINT) is
> an endogenous variable we have a second equation,
>
> EXPINT = IRD+ drd+ droy+ wagerate+ skill+ size+ size2+ forg /*Eqn
> 2.*/
>
> This calls for using a simultaneous estimation procedure like
> 3sls.
>
> The problem is, since all firms don't export, there is a selection
> bias,
> which has to be accounted for using the Heckman procedure.
Since the key equation of interest is the IRD equation, would you be
satisfied with consistent estimates of only that equation? In other
words, you don't have to estimate the system with 3SLS or whatever; you
can estimate just the IRD equation.
I may be mistaken, but I think in principle you can do single-equation IV
(2SLS or GMM or LIML) on the IRD eqn and get consistent estimates of your
parameters of interest. The question is whether you have valid
instruments (the variables that are in the EXPINT eqn but not the IRD
eqn), i.e., excluded instruments that are correlated with export intensity
and are both orthogonal to the error term in the IRD eqn and don't belong
in the IRD eqn as regressors in their own right. A partial answer to this
question of the validity of your instruments can be had from an
overidentifying restrictions test.
Hope this helps.
--Mark
Prof. Mark Schaffer
Director, CERT
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3008
email: [email protected]
web: http://www.sml.hw.ac.uk/ecomes
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