Statistics and Econometrics Features

Statistics

• EViews 6 features a new factor analysis object that allows you to: (1) compute covariances, correlations, or other measure of association (if necessary), (2) specify the number of factors, (3) obtain initial uniqueness estimates, (4) extract (estimate) factor loadings and uniquenesses, (5) examine diagnostics, (5) perform factor rotation, (6) estimate factor scores.

You may select from a menu of automatic methods for choosing the number of factors to be retained, or you may specify an arbitrary number of factors. You may estimate your model using principal factors, iterated principal factors, maximum likelihood, unweighted least squares, generalized least squares, and noniterative partitioned covariance estimation (PACE). Once you obtain initial estimates, rotations may be performed using any of more than 30 orthogonal and oblique methods, and factor scores may be estimated in more than a dozen ways.

• Principal components analysis in EViews 6 has been greatly enhanced. You may now display line graphs of the ordered eigenvalues (screen plots), and examine scatterplots of the loadings and component scores (biplots). Loadings and component scores may now be computed with various weightings so that you may, for example, construct orthonormal or eigenvalue matching scores.

• In addition to the previously supported ordinary (Pearson) correlations and covariances, you may now compute alternative measures of association: Spearman rank-order, Kendall's tau-a and tau-b, as well as partial correlations and covariances. EViews 6 now performs pairwise tests of zero correlation, with or without multiple comparison adjustments.

• Mean equality tests (ANOVA) now perform tests both under the standard maintained assumption of equal variances across subgroups, and now, under the assumption that the variances are heteroskedastic (Welch 1951, Satterthwaite 1946).

Econometrics

General

• Linear quantile regression and least absolute deviations (LAD) specifications (Koenker, 2005) may now be estimated. Asymptotic covariance matrices for the quantile regression estimates may be calculated assuming i.i.d. errors, Huber's Sandwich, or bootstrap methods. Specialized tools permit you to test for slope equality across quantile estimates (Koenker and Bassett, 1982), or to test for symmetry across quantile estimates (Newey and Powell, 1987).

• EViews 6 provides stepwise regression tools for variable selection in ordinary least squares models. Among the methods and criteria that EViews supports are: undirectional-forwards, uni-directional-backwards, stepwise-forwards, stepwise backwards, swapwise-max R-squared increment, and combinatorial.

• EViews 6 offers expanded heteroskedasticity testing (including Breusch-Pagan (1979), Godfrey (1978), Harvey (1978), Glejser (1969)), as well as the ability to specify custom tests in which you can test against departures from the homoskedastic null in a number of directions (say, by combining a White and Harvey test).

• EViews 6 now offers the Quandt-Andrews Breakpoint Test (Andrews, 1993 and Andrews and Ploberger, 1994) which tests for one or more unknown structural breakpoints in an equation's sample.

• The Binary, Count, Censored, and Ordered equation estimation methods now permit you to specify your equation by expression (instead of restricting you to providing a list). This flexibility allows you to construct non-linear index specifications, or models with coefficient restrictions.

Time-series

• You may now perform cointegration tests with panel and pooled time series cross-section data using the panel cointegration statistics of Pedroni (2004), Pedroni (1999), and Kao (1999), or the Fisher-type test suggested by Maddala and Wu (1999).

• EViews now estimates multivariate GARCH models, providing support for the most popular multivariate specifications: Conditional Constant Correlation, the Diagonal VECH and (indirectly) the Diagonal BEKK. You may estimate the model assuming multivariate normal or multivariate t-distribution errors. Once estimated, you may examine the fitted conditional covariances, variances, and correlations and save results to your workfile. In addition, you may perform residuals tests on the raw or standardized residuals, where the latter may be computed using various standardization methods.

• EViews 6 allows you to estimate univariate integrated GARCH models that constrain the persistent parameters of univariate GARCH model to sum to unity. The constant term in a GARCH model can be restricted, or the variance targeted, so that the long run variance of the model equals to the sample variance of the data. Users may now choose the weight when backcasting is used to calculate the pre-sample variance.

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EViews 6 for Windows

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