[R-sig-finance] VAR, VECM, Kalman, ... non-R software recommendations?

[Patrick Brandt]

I've been a RATS user for about 6 years (*NIX and Windows) and a Stata 
user for 10.   RATS is a great package for doing all of the standard 
econometric time series, esp VARs and VECMs.  The good thing is that it 
includes pre-packaged routines for doing impulse responses, 
forecasting, and decompositions.  It is my favorite for time series, 
because it is one of the few packages that does not strive to do 
everything -- it works to do time series well.

For basic multivariate time series modelling, RATS and Stata can do the 
job well.  I have my quibbles with both (such as Stata not having a 
well defined set of time series "objects" or methods that really 
understand how to work with ts data) and RATS "unique" syntax.  Both 
will allow you to do the standard VAR and VECM models in Hamilton or 
Johansen.

That said, programming in RATS is not for the faint at heart.  Using 
the standard routines works well, but once you start doing more exotic 
things (complex, high dimensional SVARs come to mind), or posterior 
simulations for Bayesian VARs (BVARs), things get more complicated (in 
part because the RATS syntax has a combination of old fashioned Fortran 
and C declarations).  My guess is that while these can all be done in 
RATS with some degree of effort, the effort necessary to do them in 
Stata will be monumental.  I find that whenever I work in RATS I have 
to have a set of manuals nearby.

For these reasons (and as part of a larger project to model 
international conflict data and political economy data), I have started 
on an R package that will estimate VARs, Bayesian VARs, and 
Markov-switching BVARs.  This is being done in R for the obvious 
reasons: 1) it is free / open source, 2) R is gaining wider use in the 
social sciences, 3) I can write the computationally intensive functions 
for the BVARs and MS-BVARs in C++ and make them very fast, and 4) the 
object, scope and method aspects of R lend themselves more easily to 
programming these models.

At present, few if any of these VAR / SVAR extensions are present in 
Stata (even with the new VAR routines they have added, one cannot 
estimate the BVAR models, or any error bands for the impulse 
responses).  RATS has the capacity to offer all of these methods.

Another option is Ox, which is open for academic use, and a reasonable 
fee for non-academic use: http://www.nuff.ox.ac.uk/Users/Doornik/  Ox 
can estimate VAR and VECM models, with many specialized addons.  Also, 
the Ox syntax is remarkably similar to C++.  There is a package for Ox 
that will do most of the state-space modeling outlined in Durbin and 
Koopman as well.


Patrick T. Brandt
Assistant Professor
Department of Political Science
University of North Texas
http://www.psci.unt.edu/~brandt