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CATS: Version 2.0
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distribuito in Italia da TStat S.r.l. |
PRODUCT DESCRIPTION
CATS (Cointegration Analysis of Time Series) is a
set of cointegration analysis procedures for use with the RATS software
program. It was written by Henrik Hansen and Katarina Juselius, and is
based on the research of Johansen, Juselius, and Hansen. Version 2.0 is
a major update to CATS that introduces significant new econometrics
capabilities, a re-designed and expanded user interface, and a new,
significantly expanded User's Manual
The CATS package includes a cd-rom containing the
CATS procedure and sample programs and data files, plus an all-new 200
page user's manual describing the econometrics of the cointegrated VAR
model and how to interpret the output. All features of the program are
illustrated by a worked example. The manual also includes a technical
appendix describing the mathematics of CATS.
CATS provides a wide variety of tools for analyzing
your data and choosing and testing a cointegration model. The program
is almost completely menu- and dialog-driven. You simply need to create
a "set-up" file which defines your data and sample period and executes
the CATS procedure, and then run this file in RATS. From there, you
select the desired operations from the CATS menu, and CATS will prompt
you for any needed input.
New Econometrics Features
- Bartlett small-sample correction of the tests for the cointegrating rank
and hypotheses on Beta.
- A new “CATSmining” automated model-selection procedure.
- Estimation and hypothesis testing of the I(2) model, including testing
hypotheses on the multi-cointegrating relations and the I(1) relations among
the system variables
- Estimation of structural moving average models.
- System reduction tests for lag length determination.
- Missing observations in data allowed.
- Updated recursive estimation routine includes new tests for eigenvalue
fluctuation, constancy of the cointegrating space and the log-likelihood
function.
- Allows for “backwards” recursion for investigating parameter constancy
over the beginning of the sample.
- For most model specifications, CATS now reports the correct critical
values and p-values for the rank test. For other models, you can simulate the
critical values using a built-in procedure.
- Includes a procedure for estimation and identification of structural
moving average models.
New Interface Features
- All-new user interface, with separate menus for various categories of
operations, including I(1) analysis, I(2) analysis, graphics, and automated
tests.
- All model settings, including the deterministic terms and lag structure,
are menu-controlled, so you can now change the underlying VAR model without
quitting and re-starting CATS.
- All procedure settings, such as maximum number of iterations and
convergence criteria for the switching algorithms, screen output format, and
more, can be set via a "Preferences" dialog box
- The estimated model can now be exported as a RATS “MODEL” making it much
easier to compute forecasts and impulse responses.
- The graphs created by CATS can be customized.
- Output can be exported in tex or csv formats.
- Restrictions can be saved and re-loaded, making it easier to replicate
analyses or continue your work at a later time.
- ATS offers the option of running in a true batch mode that does not
require user interaction to generate basic output. This allows it to be used
in loop.
Additional Features
These features carry over from Version 1.0:
- “Batch” tests for long-run exclusion, weak exogeneity, and stationarity on
all model variables (now available from the cats menu). Also includes a test
for unit vectors in alpha, which corresponds to testing if the cumulated
disturbances of any of the variables do not enter the common trends
- Support for partial systems, models with structural breaks, and various
forms of dummy variables.
- Multivariate and univariate tests of the estimated residuals.
- Recursive estimation for assessing constancy of the estimated model
parameters, including tests for constancy of the estimated eigenvalues, the
cointegrating space, the log-likelihood function, the parameters of an
identified system, and the adequacy of one-step-ahead predictions.
- Options for testing hypothesis on the long-run relations in Beta as well
as on the adjustment coefficients in Alpha.
- Choice of normalization for each cointegrating vector (CATS 2 simplifies
this by suggesting default choices).
- Estimation of the parameters of the moving average model, e.g. the
long-run impact matrix C and the loadings to the common trends (with
asymptotic t-values).
- A large variety of preset graphics illustrating various key aspects of the
estimated model.
NOTE: CATS 2.0 requires RATS version 6.2
Copyright © 2010 Estima
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