CATS is an add-on program to RATS: Regression Analysis of Time Series , the cointegration facilities in Microfit, and a beta version of PC-FIML 8 is. By David Tufte; CATS in RATS: cointegration analysis of time series: version . CATS in RATS: Cointegration Analysis of Time Series. Front Cover. Henrik Hansen, Katarina Juselius. Estima, – Cointegration – 87 pages.
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These help make RATS an ideal tool for new users and for use in educational settings.
The model given by equation 1. The models are referred to vointegration the X-form and R1-form, respectively. Dennis, provides a worked-through example, explanations and formulas.
This pops up when the recursive graphs have been produced, but is also available by selecting I Misc: Dt can also contain stationary stochastic variables that are weakly exogenous, or that can be excluded from the cointegrating space.
The editor also offers more than 40 menu-driven Wizards that provide point-and-click access to most common tasks, including reading analysiis, displaying graphs, doing transformations, estimating a variety of models, and hypothesis testing. NA CT 3 The dialog has 6 menu items: Actual and tted values top leftstandardized residuals bottom leftautocorrelations top seridsand histogram bottom right. To make the discussion more clear, we rewrite the error correction model 1.
CATS in RATS: cointegration analysis of time series: version 1.01
If the model contains any restricted deterministic variables, you can choose to maintain those in the cointegrating relations when testing for stationarity using the pop-up dialog shown in gure 3. The response on a shock to the German itme rate is higher prices analysi Germany and a small, probably insigni cant, effect on the US prices.
The interest rate parity relation imposes three restrictions on the second -vector and the design matrix H2 is input as shown in gure 3.
As noted earlier, the choice of the cointegrating rank r should be based on a well-speci ed model, so we recommend that you use the residuals from the unrestricted model to decide whether your model is acceptable or not.
The test statistic is asymptotically distributed as 2 with nr degrees of freedom, where n is the number of restrictions imposed by R.
CATS Cointegration Analysis
Convergence Criterion Sets the convergence criterion for the switching algorithm. The rst supplementary card will always be coibtegration for specifying the endogenous variables.
Specify R, the degrees of freedom, and normalize on dpc1 and dp2 to get the same output as shown above. If you have xed some user relations, it is most likely that basic cointegrration very similar to these will not be included in the preferred models, and you should be able to remove these without running the risk of ruling out the best model. The vectors are normalized so that VO 0 S11 VO D I p1 which is convenient for the analysis of the model properties but is most likely to have no economic interpretation.
Katarina Juselius – Google Scholar Citations
The User Settings dialog. An I 1 Analysis plying that 1lp1t 1lp2t and 1ls12 are I. Also reported are B 0 1 1 The number n is decided by the convergence criterion for the CQ coef ecients and the maximal number of iterations allowed. Here you set the number of decimals used in the screen output. Only the German in ation rate is signi cantly adjusting to the rst relation so it will be interpreted as describing a German in ation rate relation.
Restrictions on Each Beta Vector imposes restrictions on each of the vectors in. This feature is described in section 6. We note that the eigenvalues show no sign of non-constancy over the base sample period which is supported by the uctuation test. Note that CATS will recognize options and choice values by the rst three characters in their names. The properties of the error correction model are determined by the properties of the characteristic polynomial of the process given by X k 1 A.
By reestimating all parameters in each step model 1. As an illustration, we will test whether the restricted dummy C. RATS can handle time series of virtually any frequency, including daily and weekly, as well as panel and cross-section data. Zero-Restrictions on Beta opens a dialog for imposing zero-restrictions onsee paragraph 3.
If you transform your data, or if you think that the original variable names in the data le are not suf ciently informative, you can use RATS’ LABELS instruction to create labels for the cointegraiton. Under the assumption that all roots of the characteristic polynomial 1.
Hence, the shift is not necessary for accepting stationarity of the relation 3. First, the dummy variable is only included as regressor, i.