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st: Re: "Crude" Random Effects Estimates


From   "Rodrigo A. Alfaro" <ralfaro76@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: "Crude" Random Effects Estimates
Date   Thu, 25 May 2006 11:20:23 -0400

Dear Dean

HT is computed in 3 steps: (1) FE for time-variant, (2) IV for 
time-invariant and (3) IV for both (where the variables have the GLS 
transformation to control for the random effect). As it is discussed in the 
paper (Econometrica, vol 49 n6 1981, 1377-1398) the last step is to compute 
efficient estimators. In (1) you have consistent estimators for time-variant 
variables, with these you compute a proxy of the unobservable and run a 
regression of this proxy against time-invariant variables using instruments 
(2). These estimators (for time-invariant variables) are also consistent. A 
technical paper of Hahn and Meinecke (Econometric Theory 21, 2005. 455-469) 
shows that we still have consistency for non-linear models (a generalization 
of HT). In conclusion, you can force the FE coefficient for the time variant 
variables... but you will need to compute a IV regression for the 
time-invariant (in the second step as you suggest) dealing with the decision 
of instruments. Note that in the case of (manually) two-step regression you 
can include other instruments that are not in the model.

For practical purposes, I suggest you to run a FE model and compare the 
coefficients of the time-variant variables with HT. If they are different 
you can gain something doing the 2-step procedure. In addition, find other 
exogenous variables (time-invariant) that can be used in the second step. 
Once, you estimate both set of parameters you have to compute the standard 
error for 2-steps. Maybe you could be interested in robust-estimation of 
that. Wooldridge textbook offers the formulas to compute it.

Rodrigo.


----- Original Message ----- 
From: "Dean DeRosa" <dderosa@adr-i.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Thursday, May 25, 2006 10:44 AM
Subject: st: "Crude" Random Effects Estimates


I am estimating the parameters of a gravity trade model, using a large panel 
data set of international trade flows and explanatory variables. A number of 
the explanatory variables are time-invariant, so I am mainly interested in 
obtaining random effects (within cum between) estimates. I am experimenting 
with Hausman-Taylor (HT) estimates using -xthtaylor- but so far find these 
estimates difficult to evaluate given that different combinations of 
endogenous (versus instrumental) variables lead to a variety of coefficient 
estimates for the time-varying explanatory variables, with no decisive, or 
best, outcome in terms of the Hausman test of the difference between the HT 
and within estimates.

My query is whether it is tenable to run the random effects regression 
command -xtreg, re- constraining the coefficient estimates for the 
time-varying explanatory variables to be equal to "first-stage" fixed 
effects (within) estimates. Per force, this would seem to eliminate possible 
correlation between the time-varying expanatory variables and the 
unobservable specific effect variable, and to obviate the necessity of 
evaluating the random effects estimates using the -hausman- test. But, would 
it still leave the "second stage" random effects estimates subject to 
possible correlation between the time-invariant explanatory variables and 
the unobservable specific effect variable? Also, is there any precedent in 
the panel data literature for pursuing such a crude approach to obtaining 
random effects estimates?

Dean DeRosa


ADR INTERNATIONAL LTD | POTOMAC ASSOCIATES
Dean A. DeRosa
200 Park Avenue, Suite 306
Falls Church, Virginia 22046 USA
Tel: 703 532-8510 | Skype V-Tel: ADRintl
info@ADR-Intl.com | info@PotomacAssocs.com
www.ADR-Intl.com | www.PotomacAssocs.com
TRADE POLICY ANALYSIS & ECONOMIC RESEARCH



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