New EViews version 6
19/03/2007
EViews 6.0 gives you powerful statistical, forecasting and modelling tools through an innovative, easy-to-use object-oriented interface. EViews is the worldwide leader in Windows-based econometric software and the choice of those who demand the very best.
The EViews combination of power and ease-of-use make it the ideal package for anyone who works with time series, cross-section or longitudinal data. With EViews, you can quickly and efficiently manage your data, perform econometric and statistical analysis, generate forecasts or model simulations, and produce high quality graphs and tables for publication or inclusion in other applications.
Featuring an innovative graphical object oriented user-interface and a sophisticated analysis engine, EViews blends the best of modern software technology with the features you’ve always wanted. The result is a state-of-the art program that offers unprecedented power within a flexible, easy-to-use interface.
EViews 6 features a wide range of exciting changes and improvements. The following is a brief summary of some of the most important new features in Version 6.
New Improved Performance & Capacity
Nonlinear estimation, model solution, and other operations involving evaluation of series expressions are significantly faster since EViews now compiles expressions to native machine code.
Using Windows 32-bit XP or Vista with the 3G switch, or Windows 64-bit XP or Vista, data capacity can be up to two and one-half times as large as under EViews 5.1.
New Statistics Features
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, generalised 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 (scree 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).
New Econometrics Features
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. Specialised 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.
New Time-Series Features
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 integrated univariate GARCH models, constraining the persistent parameters of GARCH model to sum up 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.
New Graphics Features
Completely revamped graphics engine, allowing you greater control over the display of data, and supporting the construction of categorical graphs.
New basic graph types: Dot plot, Area Band.
Graphs may easily be displayed for summary statistics of your data (e.g., showing a bar graph of the mean values of each series in a group).
Histograms, boxplots, or kernel density graphs may be displayed in the margins of observation (line, bar, scatter, etc.) graphs.
EViews 6 offers a number of new univariate statistical graphs: histograms with options for controlling bins, frequency polygons, histogram edge polygons, average shifted histograms, fitted theoretical distribution plots (e.g., a normal density fit to sample data), empirical log survivor plots, confidence ellipses.
In addition, statistical graphs may now be overlaid on other graphs so that you may, for example, draw a kernel density and fitted normal distribution graph on top of a histogram, or you can overlay both a fitted linear regression line and a kernel regression plot on top of a scatterplot.
EViews 6 now supports line graphs containing mixed frequency data.
You may now save EViews graph output in .bmp, .gif, .png, and .jpg formats.
New Categorical Graph Tools
Categorical graph tools allow you to construct observation or analytical graphs formed using various subsets of the data, where the subsets are defined using the values of one or more categorical conditioning variables. Using these tools, you may quickly and easily perform complex tasks such as:
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Displaying a bar plot comparing the mean incomes of individuals living in each state.
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Producing a scatterplot of wages and hours worked, where the subset of males is drawn using one plotting symbol, and the subset of females uses a different symbol.
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Showing wage-education profiles for both male and female workers.
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Drawing histograms and boxplots of wages for union and non-union workers in different industries.
New Customisation Tools
Data may now be assigned to any axis (including bottom and top). Among other things, this allows you to produce rotated graphs.
EViews 6 supports character labeling of axis using the workfile structure, with optional rotation of the label.
You may now specify custom label elements for axes in frozen graphs.
You may now apply fade effects to fill colors in bars and backgrounds.
New Output Management Features
EViews 6 offers a new spool object that allows you to create collections of various EViews output. The EViews spool object is essentially a container that allows you to store multiple tables, graphs, text, and spools. Various management tools allow you to add, delete, extract, resize, annotate, hide and edit the objects in the spool.
You may find spools to be useful for organising results, for example for creating a log of the results for a project or an EViews session, or perhaps for gathering output for a presentation.
New Modelling Features
EViews 6 model solution may be up to 30 times faster than under EViews 5.1.
A new solution algorithm has been added to models. Broyden's method is a quasi-Newton method that uses a secant approximation to the Jacobian instead of the true Jacobian when solving for the Newton step. The method has many of the desirable properties of Newton's method without requiring the Jacobian to be evaluated and factored at each step.
The model solver can now reorder equations within simultaneous blocks so that a set of variables in the block can be solved recursively, conditional on the values of the remaining variables in the block. This structure is used by the Newton and Broyden solution algorithms to substantially reduce the time required to solve models consisting of large sparse systems of equations.
Stochastic simulations can now be based on bootstrapped residuals as an alternative to normally distributed random numbers. Bootstrapped residuals may be drawn independently for each equation, or may be drawn from the same period across all equations.
The complete set of results from each repetition of a stochastic simulation can now be saved as a new page in the workfile.
Equations for endogenous variables can now be excluded from the model (treated as exogenous variables) automatically based on whether actual values are available for the variable in each period. This makes it easy to perform forecasts using all available data when some series may be obtained more quickly than others.
New Database Features
Support has been added for direct access from within EViews to databases from Datastream (a service of Thomson Financial), Moody's Economy.Com and FactSet, for users who are subscribers to these services. (Enterprise edition only.)
Series imported into workfiles from a database can now maintain a link to the source database, allowing the data to be refreshed from the database each time the workfile is opened, or upon user request.
New Features - Miscellaneous
EViews 6 provides over 100 new series expression functions, including new sets of functions for moving statistics (e.g., @movstdev), cumulative statistics (e.g., @cumstdev), and statistics on the rows of a group (e.g., @rmean, which computes the mean across the series in the group), financial calculations (various present value and rate calculations), ranks, and maximum likelihood and unbiased variance calculations.
New matrix language functions for various element operations (matrix element multiply divide, power), and for row and column scaling.
Series classification tools allow you to create classification variables based on the values in a series. You may use this to create custom "binning" of series, for example, using an income series to group observations into categories using a grid of income values, marginal tax brackets, or quantiles of income.
New functions allow you to start the Windows command shell or to spawn a process from within EViews.
EViews 5 Now Shipping
13/08/2004
EViews 5 - blending the best of modern spreadsheet and relational database technology with the traditional tasks of statistical software.
In March of 1994, EViews 1.0 set the standard for what statistical software could be by bringing modern windowing and object-based techniques to econometric software. With the release of EViews 5 the result is a program that provides unprecedented power wrapped in an intuitive easy-to-use user interface.
Whether you use EViews for general statistical analysis, time series estimation and forecasting, cross-section or panel data analysis, large scale model simulation, presentation graphics, or simple data management, EViews 5 provides new features that expand your capabilities.
When working with cross-section data, panel data, irregularly dated financial data, or simple time series data, EViews 5 simplifies the process of managing your data. Need to merge data between multiple sources or want your data to be updated whenever you begin a new EViews session? No problem. New linking and updating technologies allow you to embed within your workfile relationships based on formula, match merges, frequency conversion, and references to external data. And if your work requires more than simple numbers, new alphanumeric and date handling features will cover your needs.
Data import and export have never been easier. If your data are currently in Excel, SPSS, SAS, Stata, Rats, TSP, or over a dozen other popular file formats, simply drag-and drop your file onto EViews and the data will automatically appear. EViews automatically detects the number of rows and columns in your dataset, determines the data type of each column, and even automatically analyses the date structure, frequency and range of the incoming data. EViews 5 also understands HTML, making importing data from web pages a snap. And support for ODBC in the EViews Enterprise Edition makes it easy to exchange data with your company database, including products such as Oracle, Microsoft SQL Server and IBM DB2.
But EViews 5 is not simply about data management. Powerful new statistical techniques have been added to the already impressive EViews toolkit. For time series analysis, new GARCH estimators, band-pass filters, and equation diagnostic tools are now available. Panel data analysis is supported by a new panel workfile structure, with new panel unit root tests, dynamic panel data estimators, and a full compliment of fixed and random effects specifications. New functions for dealing with categorical data, including but not limited to the automatic generation of categorical dummy variables, simplify the process of analysing cross-section and panel data.
EViews Version 4
30/03/2002
Whether you use EViews for general statistical analysis, time series estimation and forecasting, large scale model simulation, presentation graphics, or simple data management, Version 4 provides new features that expand your capabilities.
Estimation and Estimation Object
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In addition, changes have been made in convergence testing to improve estimator robustness. More informative output keeps track of your estimation settings. Expanded global options allow you to define default settings for estimation procedures.
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VAR and VEC Estimation and Testing
EViews now handles coefficient restrictions in vector error correction (VEC) models. You may impose and test linear restrictions on the cointegrating relations and/or adjustment coefficients. This allows you to choose your own normalization for the cointegrating vectors and to impose weak exogeneity restrictions. EViews displays LR test statistics for binding restrictions.
There are a number of new views in VARs that allow you to examine the structure of your specification. With a few clicks of the mouse, you can display the inverse roots of the characteristic AR polynomial, perform Granger causality and joint lag exclusion tests, evaluate various lag length criteria, and view correlograms and autocorrelations.
VARs also perform various multivariate residual based diagnostics. In addition to displaying pairwise cross correlograms, EViews computes serial correlation (portmanteau and LM), heteroskedasticity (White’s), and normality (with various options for orthogonalization) tests.
EViews VARs now provide various options for the impulse response specification. In addition to the default Cholesky factorization, you can now set the impulse to one-unit or one- standard deviation residuals (ignoring correlations), generalized impulses (Pesaran and Shin 1998), structural factorization, or a user specified vector/matrix. Monte Carlo standard errors are now available for variance decompositions.
Structural factorizations (VARs) may be estimated by imposing short-run (Sims 1986) or long-run (Blanchard and Quah 1989) restrictions. Restrictions may be specified as in text form, or as patterned matrices. Over-identifying restrictions may be tested using the LR statistic reported by EViews.
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State Space Estimation
The state space engine has been completely rewritten to provide you with greater power and flexibility. A brand new syntax allows you to specify much more general state space models than was possible in EViews 3.1. Among other things, we now allow exogenous variables in the state equation and fully parameterized variance specifications.
New procs and views give you better access to powerful filtering and smoothing tools so that you can view or generate one-step ahead, filtered, smoothed signals, states, errors, etc.
Sophisticated forecasting procedures provide easy-to-use tools for in- and out-of-sample forecasting using n-step ahead or smoothed values.
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ARCH Estimation
In addition to the default exponential smoothing backcasting methods for initializing ARCH variances and residuals, EViews 4 now allows you to initialize these values to the unconditional variance. New EViews programming examples show how you can use the EViews Logl object to estimate multivariate GARCH models of up to three-variables.
Model Solution and Analysis
The model object, which is used for simultaneous equation simulation and solution, has been completely revised. A powerful new graphical interface allows you to view the structure of your model organized by variable or by equation. Variable dependencies and the block structure of the model’s equations are displayed with a simple mouse click.
Simulation/solution options have been to provide full stochastic simulation. You may specify alternative assumptions about residual uncertainty, coefficient uncertainty, and exogenous variable uncertainty. It is now possible to generate confidence intervals for your multiple equation forecasts. Multi-period policy multipliers, including confidence intervals, can easily be generated and displayed graphically.
A new Newton solver has been added to complement the existing Gauss-Seidel solver, allowing solution of models that could not be solved in previous versions of EViews.
Forward solution (currently unavailable with stochastic solution) allows you to solve for model consistent expectations.
In addition to expanded solution options, a variety of other features have been added to models. Multiple solution scenarios are easily managed and their output compared graphically or in tabular form. Greatly expanded add factor support, including equation normalization, is now provided. Simple control problems may be solved where the values for an exogenous control variable are found so that an endogenous variable achieves a user specified target.
Enhanced Graphics
The EViews graphics engine has been completely revamped to provide the user with greater control over the display of graphics. Users can now control aspect ratios and provide independent choices of line type, line thickness, symbol, and color. New options allow the user to customize axes scaling, tickmarks, labeling and label placement. Every option can be set either interactively through the new graph option interface or in programs using an expanded set of graphics commands.
New graph types allow you to plot multiple pairs of series in a single XY-line graph or scatterplot. New types have also been added for high-low-(open-close) graphs, spike graphs, and points with error bars. A specialized graph allows quarterly and monthly series to be displayed by season to assist in the visualization of seasonal patterns.
Transferring graphs to other programs has been improved with support for Windows Enhanced Metafiles.
Statistics
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Principal Components
New principal components tools can be used to summarize your data or to analyze colinearity. The principal components view of a group of series finds the linear combinations of the series with the largest or smallest possible variance. You may also ask for the principal components of a sample covariance or correlation matrix. The eigenvalues, eigenvectors, and any number of principal components can be easily stored as named series in the workfile.
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Distribution Tests
EViews provides built-in Kolomogorov-Smirnov, Lilliefors, Cramer-von Mises, Anderson-Darling, and Watson empirical distribution tests. You can test whether your series is normally distributed, or whether it comes from, among others, an exponential, extreme value, logistic, chi-square, Weibull, or gamma distribution. You may provide parameters for the distribution, or EViews will estimate the parameters for you.
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Independence Tests
A new series view carries out the BDS test for independence. The BDS test is a portmanteau test for time based dependence in a series. It can be used for testing against a variety of possible deviations from independence including linear dependence, non-linear dependence, or chaos.
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Resampling Tools
EViews new resampling tools may be used as the basis for Monte Carlo techniques such as nonparametric bootstrapping and permutation tests. The resampling tools allow you to draw a random sample with or without replacement from observations in a series or group of series, or from the rows of a matrix. The series/group resample provides various options for missing value handling.
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Random Number Generators
Two new random number generators have been added: the L’Ecuyer (1998) "optimally" combined multiple recursive generator and the Matsumoto and Nishimura (1998) Mersenne Twister.
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Distribution and Kernel Density Plots
You can now save the results from your distribution and kernel density plots in matrix objects.
Seasonal Adjustment
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Census X12-ARIMA
EViews 4 includes support for the U.S. Census Bureau X12-ARIMA program. As with the existing X11, EViews provides a front-end interface to the official Census release. The new interface provides you with easy-to-use, menu-driven access to the most commonly used X12 features, and a new command interface to the full power of the Census X12-ARIMA program.
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Tramo/Seats
Tramo (Time Series Regression with ARIMA Noise, Missing Observations, and Outliers) performs estimation, forecasting, and interpolation of regression models with missing observations and ARIMA errors, in the presence of possibly several types of outliers. Seats (Signal Extraction in ARIMA Time Series) performs an ARIMA-based decomposition of an observed time series into unobserved components. Used together, Tramo and Seats provide a popular alternative to the Census X12 program for seasonally adjusting a series. The two programs were developed by Victor Gomez and Agustin Maravall.
EViews provides a convenient front-end to the Tramo/Seats programs as a series proc, using both a graphical and command line interface.
Data Management
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Displaying and Editing Data
A new spreadsheet feature allows you to display and edit your data in difference (1 period or 1 year) or percent difference (1 period, 1 year, or 1 period annual rate) forms. Simply open a series or group spreadsheet, and tell EViews that you want to display your data in "1-period percent changes" and EViews will automatically change the spreadsheet display to show the differences in percent terms. You may then edit the percent change for an observation and all of the underlying series data will be modified to reflect this change.
Dated Data Tables have been enhanced to allow user placed heading rows.
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Workfile Extraction
You can now create subsets of an existing workfile. Simply specify a sample, the types of objects you wish to keep, and a description of the names of objects to be kept and to be dropped. EViews will create a new workfile containing the objects and data that you selected.
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Database Support for RATS, TSP, GiveWin, and Aremos TSD Files
EViews now supports RATS, TSP, PcGive, GiveWin, and Aremos TSD files through the same interface provided for EViews databases. For example you can open a RATS file and copy-and-paste series into an EViews workfile or database. All EViews database operations, reading, writing, querying, etc., can be applied to these file formats.
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Enterprise Edition Support for FAME, DRIBase, and Haver Analytics Databases
As part of the EViews Enterprise Edition (an extra cost option over EViews Standard Edition) support is provided for proprietary data formats of commercial data and database vendors. You can access FAME local and server based databases, Standard and Poors DRIBase databases, and native Haver Analytics DBX databases. The same, easy to use, EViews database interface has been extended to these data formats.
Programming
EViews programming language has been enhanced with better error handling, new object data members, and a wide range of new functions: new statistical distribution functions, functions for computing elapsed time, functions for determining current date and time, functions to retrieve installation and working directory paths, and functions that return the number of observations in the active workfile range and sample.
Online Documentation
The EViews Help System has been expanded with more extensive discussion of estimators, screen shots, and additional hypertext links. In addition, the entire EViews User’s Guide and EViews Command and Programming Reference are provided in Adobe PDF format (along with Adobe Acrobat Reader). Both manuals are extensively hypertext linked, making it easy to find the information you need.
Order EViews 4 from Hearne online.