EViews 7.2 Standard
Powerful Analytical Tools
In contrast with most other econometric software, there is no reason for most users to learn a complicated command language. EViews' built-in procedures are a mouse-click away and provide the tools most frequently used in practical econometric and forecasting work.
Basic Statistical Analysis
EViews supports a wide range of basic statistical analyses, encompassing everything from simple descriptive statistics to parametric and nonparametric hypothesis tests.
Basic descriptive statistics are quickly and easily computed over an entire sample, by a categorization based on one or more variables, or by cross-section or period in panel or pooled data. Hypothesis tests on mean, median and variance may be carried out, including testing against specific values, testing for equality between series, or testing for equality within a single series when classified by other variables (allowing you to perform one-way ANOVA). Tools for covariance and factor analysis allow you to examine the relationships between variables.
You can visualize the distribution of your data using histograms, theoretical distribution, kernel density, or cumulative distribution, survivor, and quantile plots. QQ-plots (quantile-quantile plots) may be used to compare the distribution of a pair of series, or the distribution of a single series against a variety of theoretical distributions.
You can even perform Kolmogorov-Smirnov, Liliefors, Cramer von Mises, and Anderson-Darling tests to see whether your series is distributed normally, or whether it comes from another distribution such as an exponential, extreme value, logistic, chi-square, Weibull, or gamma distribution.
EViews also produces scatter plots with curve fitting using ordinary, transformation, kernel, and nearest neighbor regression.
Time Series Statistics and Tools
Explore the time series properties of your data with tools ranging from simple autocorrelation plots to frequency filters, from Q-statistics to unit root tests.
EViews provides autocorrelation and partial autocorrelation functions, Q-statistics, and cross-correlation functions, as well as unit root tests (ADF, Phillips-Perron, KPSS, DFGLS, ERS, or Ng-Perron for single time series and Levin-Lin-Chu, Breitung, Im-Pesaran-Shin, Fisher, or Hadri for panel data), cointegration tests (Johansen for with MacKinnon-Haug-Michelis critical values and p-values ordinary data, and Pedroni, Kao, or Fisher for panel data), causality, and independence tests.
EViews also provides easy-to-use front-end support for the U.S. Census Bureau's X11 and X12-ARIMA seasonal adjustment programs, as well as the Tramo/Seats software, which is quite frequently used by European researchers. Simple seasonal adjustment using additive and multiplicative difference methods is also supported in EViews.
You can even use EViews to compute trends and cycles from time series data using the Hodrick-Prescott filter, Baxter-King, Christiano-Fitzgerald fixed length and Christiano-Fitzgerald asymmetric full sample band-pass (frequency) filters.
Panel and Pooled Data Statistics and Tools
EViews features a wide variety of tools designed to facilitate working with both panel or pooled/time series-cross section data. Define panel structures with virtually no limit on the number of cross-sections or groups, or on the number of periods or observations in a group. Dated or undated, balanced or unbalanced, and regular or irregular frequency panel data sets are all handled naturally within the EViews framework.
Data structure tools facilitate transforming your data from stacked (panel) to unstacked (pooled) formats, and back again. Smart links, auto series, and data extraction tools, allow you to slice, match merge, frequency convert, and summarize your data with ease.
Support for basic longitudinal data analysis ranges from convenient by-group and by-period statistics, tests, and graphs, to sophisticated panel unit root (Levin-Lin-Chu, Breitung, Im-Pesaran-Shin, or Fisher) and cointegration diagnostics (Pedroni (2004), Pedroni (1999), and Kao, or the Fisher-type test).
Specialized tools for displaying panel data graphs allow you to view stacked, individual, or summary displays. Display line graphs of each graph in a single graph frame or in individual frames. Or show summary statistics for the panel data taken across cross-sections, with mean (or median) and standard deviation (or quantile) bands.