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st: RE: ivreg2 bandwidth


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: ivreg2 bandwidth
Date   Thu, 13 Oct 2011 16:51:25 +0100

Mirko,

It depends partly on what you think the source of autocorrelation is.

If the autocorrelation is purely the result of the fact that these are 3-day MAs - so that the autocorrelation will disappear after 3 days - then the right kernel to use is the truncated kernel (a.k.a. "Hansen-Hodrick") with a bandwidth of 3.  It's not guaranteed to be PD in finite samples, but this might not be a problem in practice in your case.

If you suspect that there is autocorrelation beyond the 3rd lag, you could try the automatic bandwidth selection option - just say bw(auto).

HTH,
Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Mirko
> Sent: 13 October 2011 15:21
> To: statalist@hsphsun2.harvard.edu
> Subject: st: ivreg2 bandwidth
> 
> Dear all,
> 
> I am estimating a times-series equation where the dependent 
> variable and the endogenous variable are 3-day moving averages.
> 
> I am using -ivreg2- with -gmm2s- and -robust- to obtain 
> heteroskedasticity and autocorrelation-robust standard errors such as
> this:
> 
> qui count
> local band = round(r(N)^1/3)
> ivreg2 y x1 (x2=  z1 z2), gmm2s robust bw(`band') first
> 
> I am not sure about the correct bandwidth specification in 
> this specific case as I am using moving averages. For a 
> Bartlett kernel function, it is usually suggested to use 
> N^1/3. However, I am not sure whether this is correct 
> specification when using moving averages.
> 
> I would be grateful to receive any suggestion.
> 
> Best wishes,
> Mirko
> --
> Mirko Moro
> Lecturer in Economics
> Economics Division
> University of Stirling
> FK94LA
> Scotland (UK)
> t: +44(0)1786467479
> f: +44(0)1786467469
> e: mirko.moro@stir.ac.uk
> 
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