Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

RE: st: ivreg2: interacting the endogenous regressor


From   <[email protected]>
To   <[email protected]>
Subject   RE: st: ivreg2: interacting the endogenous regressor
Date   Thu, 24 May 2012 14:59:53 +0100

(Apologies for jumping into this conversation, but I would like to add
my own questions/ignorance)

Kit, from what I understand, your suggestion is to treat the two
variables (endogenous and interaction) as independent, thus running
something like:
		ivreg2 y ex (en en_ex = z z_ex)
where 'ex' is the exogenous variable, 'en' is the endogenous variable,
'z' is the instrument (excluded variable), 'en_ex' is the interaction
between the endogenous and the exogenous variables and 'z_ex' is the
interaction between the exogenous variable and the instrument. 

My question is: doesn't this assume that 'en' and 'en_ex' are
independent? In other words, isn't it that the first-stage regressions
predict 'en' independently of the prediction of 'en_ex' (and, inversely,
predict 'en_ex' independently of the prediction of 'en')? This would be
more of a problem (I think) the higher the variance of 'en' relative to
that of 'ex'. But, importantly, if it is the other way round (i.e., if
the endogenous variable has a much lower variance than the exogenous
one, so that 'en' and 'en_ex' are not too collinear), isn't it that my
prediction of 'en_ex' using 'z_ex' will essentially be a regression of
'ex on 'ex' - and thus basically irrelevant?? 

I was thinking that ideally one ought to run a first-stage regression of
the form "reg  en z ex" (plus lags, as appropriate) and then use the
prediction to create the interaction term between the exogenous
variable, on the one hand, and the prediction of the endogenous
variable, on the other, before moving on with the second-stage
regression. Is this the wrong way of thinking about it? And, if not, is
there a way to implement this in Stata??

Many thanks in advance,
Vassilis

===============================================
Dr Vassilis Monastiriotis
Hellenic Observatory, European Institute, LSE 
email: [email protected] 
===============================================

-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Christopher
Baum
Sent: 24 May 2012 14:17
To: [email protected]
Subject: Re: st: ivreg2: interacting the endogenous regressor

<>
On May 24, 2012, at 8:33 AM, Jana wrote:

> Hi -- thanks for the idea, Kit (Go Blue!). Unfortunately, even decent 
> instruments are very hard to find. Essentially, I am trying to test 
> whether the effect of the instrumented variable depends on the values 
> that the variable x1 takes on. Is there some way to do this that 
> doesn't involve trying to find a second instrument (which is near- 
> impossible)? I've split x1 into "low" and "high" and run separate 
> regressions, but that doesn't allow cross-estimation comparisons,
right?

I didn't say you needed to find two instruments. You need an instrument
z1 and you need to interact it with x1. That adds up to two instruments,
but ony one excluded variable will be used to define them both.  There
should not be any difficulty testing for an interaction effect using
this strategy.

Kit


Kit Baum   |   Boston College Economics & DIW Berlin   |
http://ideas.repec.org/e/pba1.html
                             An Introduction to Stata Programming  |
http://www.stata-press.com/books/isp.html
  An Introduction to Modern Econometrics Using Stata  |
http://www.stata-press.com/books/imeus.html


*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/

Please access the attached hyperlink for an important electronic communications disclaimer: http://lse.ac.uk/emailDisclaimer

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index