EViews 8 New Econometrics and Statistics: Computation

EViews 8 features a number of additions and improvements to its toolbox of basic statistical procedures. Among the highlights are new tools for exponential smoothing, panel series covariances and principle components, as well as support for the new Census X-13 seasonal adjustment tools.

ETS Exponential Smoothing

EViews 8 now offers support for exponential smoothing using the dynamic nonlinear model framework of Hyndman, Koehler, et al. (2002).

The ETS (Error-Trend-Seasonal or ExponenTial Smoothing) framework defines an extended class of exponential smoothing methods that encompasses standard ES models (e.g., Holt and Holt–Winters additive and multiplicative methods), but offer a variety of new methods.

In addition ETS smoothing offers a theoretical foundation for analysis of these models using state-space based likelihood calculations, with support for model selection and calculation of forecast standard errors.

Read more about ETS smoothing in EViews 8

Census X-13

EViews 8 offers an easy-to-use front-end for working with the U.S. Census Bureau’s new X-13 seasonal adjustment tools. In addition to providing a wide range of new features (including ARIMA regression prior to the seasonal adjustment step), X-13 is capable of performing updated versions of X-11/X-12 or TRAMO/SEATS ARIMA seasonal adjustment.

Read more about Census X-13 in EViews 8

Panel Covariances

Panel covariances and correlations are widely used in panel data analysis. For example:

• Contemporaneous correlations between macroeconomic variables are often used to examine the nature of relationships between different countries (see for example, Obstfeld and Rogoff, 2001, p. 368).
• The contemporaneous covariances of residuals from panel regression are used in computing cross-sectional Zellner SUR-type estimators (Johnston and Dinardo, 1997, p.318) and in tests of cross-section dependence (Pesaran, 2004). Similarly, panel covariances are used as a first step in obtaining common factors for unit root and other tests (Bai and Ng, 2004). Note that EViews does not have these tests built in, but the inclusion of the panel covariance calculations allows you to calculate the test statistics manually.

Panel Principal Components

In addition to computing measures of association for a series across cross-sections or periods EViews 8 also computes the principal components of the panel variable using one of the measures of association.

As with the other principal components tools in EViews, you may display the table of eigenvalues and eigenvectors, display line graphs of the ordered eigenvalues, and examine scatterplots of the loadings and component scores. Furthermore you may save the component scores and corresponding loadings to the workfile.