Spectral analysis with RATS includes the Fourier transform, spectra and cross spectra, and coherence and phase. In addition to conventional analysis in the time domain, RATS can estimate time series in the frequency domain, also known as spectral analysis of time series. Mainly a time series package, one can also programme models of cross section and panel data with RATS.
Therefore, even if GARCH procedures were not provided, the user can write one with, e.g., RATS functions and the maximum likelihood procedure.Īs such, virtually all kinds of contemporary time series models can be estimated with RATS, though sometimes it involves great complexity and requires much experience and skill. One of the advantages for using RATS is that, while a specialist package for time series analysis equipped with many readily executable procedures, the user can write or easily adapt a procedure for her/his own specific needs, or s/he can even write a procedure from scratch. Like EViews, RATS also has User’s Guide and Reference Manual in the electronic form, though it is an industry norm now. With RATS version 7 there are many new features and improvements over the previous versions, such as more instrument variable/GMM support, and improved graphics. RATS, Regressional Analysis of Time Series, is one of the most authoritative packages in the area. For more detail and purchase information visit the website given. The state space model and the Kalman filter can only do basic things, which are far from enough to cope with the requirement encountered in modern empirical studies featured by sophisticated model specifications and extensions. Although there are many variations of GARCH available, they are all univariate.
However, the menu-driven feature also means that the package is not flexible to adapt to the need of specific requirements. Its help system in the electronic form is excellent, e.g., the Estimation Methods part provides detailed information on model specification and estimation, as well as the background and origin of the model. It can easily handle most modern econometric models such as binary dependent variable models, univariate GARCH, cross section and panel data, and so on. 1 EViewsĮViews, or Econometric Views, is a menu-driven and user-friendly package. Following is a list of popular contemporary packages being widely, but not exclusively, used by financial economists and econometricians. None of modern financial econometrics projects can be executed without making use of an econometrics package.
9 Econometric software packages for financial and economic data analysis
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