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st: re: How to correct standard errors of a 2sls performed by

Christopher F Baum
<>
John wrote
How would one deal with systems of equations (i.e., reg3) and
concurrently have heteroskedastic-robust standard errors?  Would
bootstrapping with reg3 just be the simplest solution?


In the absence of cross-equation constraints, just estimate each equation with single-equation methods, i.e. -ivregress- or -ivreg2- using robust or cluster-robust VCE. Nothing is lost in doing so beyond a possible gain in efficiency.

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


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Re: st: re: How to correct standard errors of a 2sls performed by

JOHN ANTONAKIS
Hi:

What if the system is non-recursive (with feedback loops) and with
multiple equations, e.g.,

y = x1 + x2 + z
x1 = m1 + m2 + x2 + z
x2 = n1 + n2 + x1 + z
m1 = q1 + q2 + z
m2 = p1 + p2 + z

Here one would need reg3, but how would one ensure consistency of
standard errors (in the presence of heteroskedasticity), apart from
bootstrapping (and Roodman's -cmp- would not here as it is only for
recursive systems)?

Thanks,
J.

____________________________________________________

Prof. John Antonakis, Associate Dean
Faculty of Business and Economics
Department of Organizational Behavior
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland

Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Faculty page:
http://www.hec.unil.ch/people/jantonakis

Personal page:
http://www.hec.unil.ch/jantonakis
____________________________________________________



On 06.02.2010 02:02, Kit Baum wrote:

> <>
> John wrote
> How would one deal with systems of equations (i.e., reg3) and
> concurrently have heteroskedastic-robust standard errors?  Would
> bootstrapping with reg3 just be the simplest solution?
>
>
> In the absence of cross-equation constraints, just estimate each equation with single-equation methods, i.e. -ivregress- or -ivreg2- using robust or cluster-robust VCE. Nothing is lost in doing so beyond a possible gain in efficiency.
>
> 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/
>  
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st: New versions of/extensions to ivreg2, xtivreg2, ranktest, xtoverid, ivreg29

Schaffer, Mark E
Dear Statalisters:

New versions of and extensions to the Baum-Schaffer-Stillman packages
ivreg2, xtivreg2, ranktest and xtoverid, and a new program, ivreg29, are
now available from ssc.

The main extensions and upgrades are:

1.  2-way clustering.

2-way clustering, introduced by Cameron, Gelbach and Miller (2006) and
Thompson (2009), is now supported.  2-way clustering, e.g.,

        ivreg2 y x1 x2, cluster(id year)

or
        ivreg2 y (x = z1 z2), gmm2s (cluster id year)

allows for arbitrary within-cluster correlation in two cluster
dimensions.  In the examples above, standard errors and statistics are
robust to disturbances that are autocorrelated (correlated within
panels, clustering on id) and common (correlated across panels,
clustering on year).  In the second example, estimates also are
efficient in the presence of arbitrary within-panel and within-year
clustering.  As with 1-way clustering, the numbers of clusters in both
dimensions should be large.

2.  Angrist-Pischke first-stage F statistics

ivreg2 and xtivreg2 now provide Angrist-Pischke first-stage F
statistics.  Angrist and Pischke (2009, pp. 217-18) introduced
first-stage F statistics for tests of under- and weak identification
when there is more than one endogenous regressor.  In contrast to the
Cragg-Donald and Kleibergen-Paap statistics, which test the
identification of the equation as a whole, the AP first-stage F
statistics are tests of whether one of the endogenous regressors is
under- or weakly identified.

3.  SEs that are robust to autocorrelated across-panel disturbances

Following Thompson (2009), cluster-robust and kernel-robust SEs can be
combined and applied to panel data to produce SEs that are robust to
arbitary common autocorrelated disturbances.  This can also be combined
with 2-way clustering to provide SEs and statistics that are robust to
autocorrelated within-panel disturbances (clustering on panel id) and to
autocorrelated across-panel disturbances (clustering on time combined
with kernel-based HAC).

4.  ivreg2 has been Mata-ized

... and is noticably faster, in particular with time series and the CUE
(continuously-updated) GMM estimator.

5.  ivreg29 for users who don't yet have Stata 10 or 11

ivreg2 requires Stata 10 or later.  For those who have only Stata 9, we
have provided a new program, ivreg29.  ivreg29 is basically the previous
version of ivreg2 plus support for AP F-statistics and some minor bug
fixes.  ivreg29 does not support the other features described above.

For full details and examples, see the new help files accompanying the
programs.

--Kit, Mark and Steve


References

Angrist, J.D. and Pischke, J.-S. 2009. Mostly Harmless Econometrics: An
Empiricist's Companion.  Princeton: Princeton University Press.

Cameron, A.C., Gelbach, J.B. and Miller, D.L.  2006.  Robust Inference
with Multi-Way Clustering.  NBER Technical Working paper 327.
http://www.nber.org/papers/t0327.

Thompson, S.B.  2009.  Simple Formulas for Standard Errors that Cluster
by Both Firm and Time.  http://ssrn.com/abstract=914002.


Prof. Mark Schaffer FRSE
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS
tel +44-131-451-3494 / fax +44-131-451-3296
http://ideas.repec.org/e/psc51.html
 


--
Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


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st: RE: New versions of/extensions to ivreg2, xtivreg2, ranktest, xtoverid, ivreg29

Schaffer, Mark E
Hi all.  Just want to correct a typo in the announcement about the
features in ivreg2 et al.  The examples of 2-way clustering should read:

        ivreg2 y x1 x2, cluster(id year)

        ivreg2 y (x = z1 z2), gmm2s cluster(id year)

Cheers,
Mark

> -----Original Message-----
> From: [hidden email]
> [mailto:[hidden email]] On Behalf Of
> Schaffer, Mark E
> Sent: 06 February 2010 11:17
> To: [hidden email]
> Subject: st: New versions of/extensions to ivreg2, xtivreg2,
> ranktest, xtoverid, ivreg29
>
> Dear Statalisters:
>
> New versions of and extensions to the Baum-Schaffer-Stillman
> packages ivreg2, xtivreg2, ranktest and xtoverid, and a new
> program, ivreg29, are now available from ssc.
>
> The main extensions and upgrades are:
>
> 1.  2-way clustering.
>
> 2-way clustering, introduced by Cameron, Gelbach and Miller
> (2006) and Thompson (2009), is now supported.  2-way clustering, e.g.,
>
> ivreg2 y x1 x2, cluster(id year)
>
> or
> ivreg2 y (x = z1 z2), gmm2s (cluster id year)
>
> allows for arbitrary within-cluster correlation in two
> cluster dimensions.  In the examples above, standard errors
> and statistics are robust to disturbances that are
> autocorrelated (correlated within panels, clustering on id)
> and common (correlated across panels, clustering on year).  
> In the second example, estimates also are efficient in the
> presence of arbitrary within-panel and within-year
> clustering.  As with 1-way clustering, the numbers of
> clusters in both dimensions should be large.
>
> 2.  Angrist-Pischke first-stage F statistics
>
> ivreg2 and xtivreg2 now provide Angrist-Pischke first-stage F
> statistics.  Angrist and Pischke (2009, pp. 217-18)
> introduced first-stage F statistics for tests of under- and
> weak identification when there is more than one endogenous
> regressor.  In contrast to the Cragg-Donald and
> Kleibergen-Paap statistics, which test the identification of
> the equation as a whole, the AP first-stage F statistics are
> tests of whether one of the endogenous regressors is
> under- or weakly identified.
>
> 3.  SEs that are robust to autocorrelated across-panel disturbances
>
> Following Thompson (2009), cluster-robust and kernel-robust
> SEs can be combined and applied to panel data to produce SEs
> that are robust to arbitary common autocorrelated
> disturbances.  This can also be combined with 2-way
> clustering to provide SEs and statistics that are robust to
> autocorrelated within-panel disturbances (clustering on panel
> id) and to autocorrelated across-panel disturbances
> (clustering on time combined with kernel-based HAC).
>
> 4.  ivreg2 has been Mata-ized
>
> ... and is noticably faster, in particular with time series
> and the CUE
> (continuously-updated) GMM estimator.
>
> 5.  ivreg29 for users who don't yet have Stata 10 or 11
>
> ivreg2 requires Stata 10 or later.  For those who have only
> Stata 9, we have provided a new program, ivreg29.  ivreg29 is
> basically the previous version of ivreg2 plus support for AP
> F-statistics and some minor bug fixes.  ivreg29 does not
> support the other features described above.
>
> For full details and examples, see the new help files
> accompanying the programs.
>
> --Kit, Mark and Steve
>
>
> References
>
> Angrist, J.D. and Pischke, J.-S. 2009. Mostly Harmless
> Econometrics: An Empiricist's Companion.  Princeton:
> Princeton University Press.
>
> Cameron, A.C., Gelbach, J.B. and Miller, D.L.  2006.  Robust
> Inference with Multi-Way Clustering.  NBER Technical Working
> paper 327.
> http://www.nber.org/papers/t0327.
>
> Thompson, S.B.  2009.  Simple Formulas for Standard Errors
> that Cluster by Both Firm and Time.  http://ssrn.com/abstract=914002.
>
>
> Prof. Mark Schaffer FRSE
> Department of Economics
> School of Management & Languages
> Heriot-Watt University, Edinburgh EH14 4AS tel
> +44-131-451-3494 / fax +44-131-451-3296
> http://ideas.repec.org/e/psc51.html
>  
>
>
> --
> Heriot-Watt University is a Scottish charity registered under
> charity number SC000278.
>
>
> *
> *   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/
>


--
Heriot-Watt University is a Scottish charity
registered under charity number SC000278.


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