Thank you Michael.
Grant
-----Original Message-----
From: Michael Hanson <[email protected]>
To: [email protected]
Date: Wed, 18 Mar 2009 21:57:12 -0400
Subject: Re: st: fully modified OLS and dynamic OLS
On Mar 18, 2009, at 6:37 PM, Grant Peter Kabango wrote:
> I would like to estimate using the fully modified OLS (FMOLS) and
> dynamic OLS (DOLS), and I wish to find out the Stata command for
> these processes.
On Mar 18, 2009, at 7:01 PM, Martin Weiss wrote:
> -findit- does not return any results. Are these procedures known
> under any other name?
The short answers are no (to Grant: "Are FM-OLS or DOLS currently
implemented in Stata?") and no (to Martin: "Are they known by other
names?"). Note that this request and the corresponding response
about alternative names reappear on Statalist roughly every year or
two (and apparently has been more popular recently):
<http://www.stata.com/statalist/archive/2004-08/msg00355.html>
<http://www.stata.com/statalist/archive/2006-05/msg00010.html>
<http://www.stata.com/statalist/archive/2008-01/msg00078.html>
<http://www.stata.com/statalist/archive/2008-04/msg00725.html>
<http://www.stata.com/statalist/archive/2008-08/msg01166.html>
FM-OLS and DOLS are single equation estimators for cointegrated
relationships. Given that this is a fairly specialized topic in time
series analysis, I don't believe they can be found in other
Stata .ado files under different names. (Although I would be happy
to be proven wrong on that point.)
Dynamic OLS is quite easy to implement in Stata, since it just
involves augmenting a (super-consistent) OLS estimate of the
cointegrating relationship with leads and lags of the RHS variable.
For appropriate inference, HAC standard errors must be used. Below
is a simple (and very stylized) example. Note that this example uses
both -ivreg2- and -freduse-, which are available from SSC.
// Begin example
clear
freduse GDPC96 PCECC96
gen t = qofd(daten)
format t %tq
drop date*
tsset t
gen y = ln(GDPC96)
gen c = ln(PCECC96)
ivreg2 c y L(-4/4)D.y, bw(auto) robust
ivregress 2sls c y L(-4/4)D.y, vce(hac nw opt)
// End example
The coefficient on y in each regression will be the estimate of the
parameter B in the cointegrating vector [1 -B], such that [c y] [1 -
B]' ~ I(0). Note that -ivreg2- will work with Stata 9 or better
(once installed); -ivregress- was introduced in Stata 10. They
should return identical results in the above example.
The FM-OLS estimator is a little more sophisticated, and -- as far as
I can tell -- no one has contributed a user-written version. Thus,
your options are (1) write it yourself (see the references below --
would be a good exercise to implement in Mata); (2) use a system
estimator (such as -vec-); or (3) use a different statistical
package. (For example, FM-OLS has been implemented in RATS: see
<http://www.estima.com/procs_perl/fm.src> and <http://www.estima.com/
procs_perl/panelfm.src>. Procedures may also have been written for
R, but a quick search did not turn up anything.)
Hope this helps. Perhaps the next time someone looks for the DOLS or
FM-OLS estimators, they will search the mailing list archive first.
-- Mike
References:
Banerjee, Anindya, et al, "Co-integration, Error-Correction, and the
Econometric Analysis of Non-Stationary Data," Oxford University
Press, 1993.
Maddala, G.S. and In-Moo Kim, "Unit Roots, Cointegration, and
Structural Change," Cambridge University Press, 1998.
Phillips, Peter and Bruce Hansen, "Statistical Inference in
Instrumental Variables Regression with I(1) Processes," Review of
Economic Studies, v.57, 1990, pp. 99-125.
Phillips, Peter, "Fully Modified Least Squares and Vector
Autoregression," Econometrica, v.63 n.5, 1995, pp. 1023-1078.
Stock, James and Mark Watson, "A Simple Estimator of Cointegrating
Vectors in Higher Order Integrated Systems," Econometrica, v.61 n.4,
1993, pp. 783-820.
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