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New standard of econometric software.
Designed for the modern generation of 32-bit Windows operating systems, and featuring major enhancements to both data management and modeling tools, EViews 5 sets the standard for econometric analysis, forecasting, and modeling software...
Whether you use EViews for general statistical analysis, time series estimation and forecasting, large scale model simulation, presentation graphics, or simple data management, Version 5 of EViews provides new features that expand your capabilities...
Featuring a modern, graphical object-oriented user interface, EViews provided an alternative to antiquated, software design.
The combination of power and ease-of-use made EViews an immediate best seller.
We are pleased to announce the public availability of EViews 5 Beta, a pre-release version of the next generation of our best selling EViews software. EViews 5, which is scheduled for release by April 2004, features the most extensive changes and innovation in the program since the initial version of EViews.
EViews 5 New Features:
Workfile
| • | Multi-page workfiles. |
| • | Support for complex data structures including irregular dated data, cross-section data with observation identifiers, dated and undated panel data. |
| • | Match merge, join, append, subset, resize, sort, and reshape (stack and unstack) workfiles. |
| • | Convert data between EViews and various spreadsheet, statistical, and database formats, including: Microsoft Access files, Gauss Dataset files, ODBC Dsn files (Enterprise Version), ODBC Query files (Enterprise Version), SAS Transport files, native SPSS files, SPSS Portable files, Stata files, Excel files, raw ASCII text or binary files, HTML, or ODBC Databases and queries (Enterprise Version). |
General Data
| • | Alphanumeric (string) series, with an extensive library of string manipulation functions. |
| • | Date series, with an extensive library of date manipulation functions. |
| • | Dynamic frequency conversion and match merging using link objects. Frequency conversion and match merge links will be updated whenever the underlying data change. |
| • | Auto-updating series that depend upon a formula are automatically recalculated whenever the underlying data change. |
| • | Value labels (e.g., "High", "Med", "Low", corresponding to 2, 1, 0) may be used with numeric and alpha series. Function support allows you to work with either the underlying or the mapped values. |
| • | Improved sample object processing allows for the direct use of sample objects in series expressions. In addition, set operators may now be used with sample objects, allowing you to form samples using the operators AND, OR, and NOT. |
| • | New functions facilitate assigning values from the computation of by-group descriptive statistics to individual observations. |
| • | Automatic creation of sets of dummy variables for use in estimation. |
Alpha Series and String Support
| • | New library of string functions and operators. |
| • | Functions for converting between string representations of dates and EViews numeric date values. |
Date series and Date support
| • | Full support for calendar dates with extensive library of functions for manipulating dates and EViews numeric date values. |
| • | Functions for converting between EViews numeric date values and string or numeric representations of dates. |
Panel and Pool data
| General | |
| • | Workfile tools reshape data to and from panel (stacked) and pool (unstacked) workfile structures. |
| • | Panel unit root tests: Levin-Lin-Chu, Breitung, Im-Pesaran-Shin, Fisher-type tests using ADF and PP tests (Maddala-Wu, Choi), Hadri. |
| • | Linear equation estimation with additive cross-section and period effects (fixed or random). Two-way random and mixed effects models supported for balanced data only, most others for both balanced and unbalanced data. |
| • | Quadratic unbiased estimators (QUEs) for component variances in random effects models: Swamy-Arora, Wallace-Hussain, Wansbeek-Kapteyn. |
| • | Generalized least squares for models with cross-section or period heteroskedastic and correlated specifications. Support for both one-step and iterative weighting. |
| • | Two-stage least squares (2SLS) / Instrumental variables (IV) estimation with cross-section and period fixed or random effects. Generalized 2SLS/IV estimation of GLS specifications. |
| • | Most specifications support estimation with AR errors using nonlinear least squares on the transformed specification. |
| • | Robust standard error calculations including seven types of robust White and Panel-corrected standard errors (PCSE). |
| Panel Specific | |
| • | Structured workfiles support large cross-section panels. |
| • | Panel data graphs. Various plots by cross-section in multiple graphs or combined. Graphs of summary values across cross-section. |
| • | Nonlinear equation estimation with additive effects. |
| • | GMM estimation for models with cross-section or period heteroskedastic and correlated specifications. Support for both one-step and iterative weighting. |
| • | Linear dynamic panel data estimation using first differences or orthogonal deviations, with period specific instruments (Arellano-Bond one-step, one-step robust, two-step, iterated). Flexible specification of instrument lists. |
| Pool Specific | |
| • | Define groups of cross-sections for dummy variable processing. |
| • | Support for period specific effects, coefficients, instruments and weights. |
Garch Estimation
| • | Student's t and Generalized Error Distribution support with optional fixed distribution parameter. |
| • | More flexible EGARCH and TARCH specifications allow for estimation of a wider range of econometric models. |
| • | Power ARCH specifications with optional fixed power parameter. |
Statistics/Econometrics
| • | Confidence ellipses showing the joint confidence region of any two functions of estimated parameters from an EViews estimation object. |
| • | ARMA equation diagnostics. Display the inverse roots of the AR and/or MA characteristic polynomial; compare the theoretical (estimated) autocorrelation pattern with the actual correlation pattern for the structure residuals; display the ARMA impulse response to an innovation shock. |
| • | Band-pass (frequency) filters for a series object. EViews can compute the Baxter-King, Christiano-Fitzgerald fixed length, and the Christiano-Fitzgerald asymmetric full sample filters. |
Graph and Tables
| • | Filled area graphs. |
| • | Boxplots. |
| • | Enhanced table customization with control over font face, font size and color, cell background color, and borders, with cell merging and annotation. |
| • | Improved interactive and program interface for working with tables. Selecting cells, resizing columns, and changing numeric and other display formats should be much more straightforward and intuitive. |
| • | Write graphs as PostScript files. Improved Windows Metafile support now comes with control over output sizing. |
| • | Tables may be written to HTML and RTF files. |
Speed
| • | Greatly improved speed of operation. |
Software econometria
analisi econometrica
econometria
analisi statistiche
serie temporali
calcolo di previsione
stime di previsione
covarianza del coefficiente
variabile dipendente
equazioni lineari
equazioni non lineari
sistemi
statistica descrittiva
grafici quantili
kernel
filtro di kalman
minimi quadrati
modelli arch
test diagnostici
In response to user requests, QMS have added several new features to EViews 4.0. Some of these features, like added function support, an expanded Wald test output, and extensions to the model program language, are minor improvements to existing routines. Others, like the new unit root testing features, and extensions to both the state space error, and system instrumental variables specification languages, represent significant improvements in the set of tools for working with, and analyzing your data.
Unit Root Testing
EViews 4.1 includes support for the newest generation of unit root tests. In addition to the existing Augmented Dickey-Fuller and Phillips-Perron tests, EViews now allows you to compute the GLS-detrended Dickey-Fuller (Elliot, Rothenberg, and Stock, 1996), Kwiatkowski, Phillips, Schmidt, and Shin (KPSS, 1992), Elliott, Rothenberg, and Stock Point Optimal (ERS, 1996), and Ng and Perron (NP, 2001) unit root tests.
EViews will also perform Newey-West (1992) and Andrews (1991) automatic bandwidth selection for kernel based estimators, or automatic information criteria based selection of lag length for Dickey-Fuller tests and AR spectral density estimators.
System Extensions
QMS have expanded the flexibility of instrumental variables specifications estimated by 2SLS and 3SLS.
Previously, all instrumental variables projections in systems were performed on an equation-by-equation basis. In EViews 4.1, the new @stackinst statement provides a new way of specifying instruments for systems of equations that allows for cross-equations on the projections of variables on instruments. You can now stack your equations and instruments prior to performing the projection. The easy-to-use syntax provides you with full control over the instrument stacking so that you may combine the earlier ordinary instrument and new stacked instrument specifications.
Sspace Improvements
EViews 4.1 extends the features of the sspace object in two distinct ways.
First, extensions to the state space syntax in EViews 4.1 allow you to write the error term for any equation as a linear combination of named errors. This syntax allows users to specify a wide range of important models in a more natural fashion.
Second, new sspace object data members give you access to output matrices containing intermediate calculations from the Kalman filter.
Enhanced Model Features
EViews 4.1 provides new modeling tools to aid you in model building and solution. An enhanced command syntax provides you with greater control over the model solution procedure, enhanced tools for working with scenarios, and additional commands to maintain the links in your model.
Miscellaneous Statistical Features
The output of the Wald test has been expanded to provide additional information about the restrictions and the restriction variances. As a result, you can use the expanded output to find the standard errors of functions of your coefficients.
The "Statistics by Classification" view of a series now allows you to compute arbitrary quantiles of your data by group.
New Functions
EViews 4.1 now supports a family of percentage change functions that complement the existing functions. These functions eliminate the need to rescale function values when working in percentage terms.
In addition, we have added functions for computing base-10 and arbitrary base logarithms.
The goal in designing EViews was to make it both powerful and intuitive. A wide range of statistical and graphical techniques had to be made available without requiring users to memorize complicated command syntax or navigate layers and layers of menus. The solution is an innovative object-oriented user interface.
EViews is built around the concept of objects. Series, equations, and systems are just a few examples of objects. Each object has its own window, its own menus, its own procedures, and its own views of its data. Most statistical procedures are simply alternative views of the object. For example, a simple menu choice from a series window changes the display between a spreadsheet, line and bar graphs, a histogram-and-statistics view, a correlogram, and a unit root test.
Similarly, an equation window allows you to switch between a display of the equation specification, basic estimation results, the coefficient covariance matrix, graphics depicting the actual, fitted, and residual values for the dependent variable, tables, forecast graphs and evaluations, and more than a dozen diagnostic and hypothesis tests.
Naturally, you can cut-and-paste any of these views into your favorite word processor with a simple menu selection. And it's just as easy to exchange data and results with your spreadsheet and database programs. Of course if you don't like cut-and-paste, EViews supports direct file access to Lotus WKS, WK1, and WK3 files, Microsoft Excel XLS files, and Microsoft Windows Metafiles and Enhanced Metafiles.
Of course, programming isn't for everybody. Unlike some other econometric software, there is no reason for most users to learn complicated 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 Statistics
Basic descriptive statistics are easily computed over an entire sample, by categorization based on one or more variables, or by both cross-section and period in pooled data. Hypothesis tests on mean, median and variance may be carried out, including test against specific values, equality between series, or equality within a single series when classified by other variables (which allows you to perform one-way ANOVA).
Graphical presentations of histograms, cumulative distribution, survivor, and quantile plots characterize the distribution of your data. QQ-plots (quantile-quantile plots) 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 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.EViews also calculates kernel density estimates, and produces scatterplots with curve fitting using ordinary, transformation, kernel, and nearest neighbor regression.
Unit root tests (ADF and Phillips-Perron), cointegration tests, causality tests, autocorrelation and partial autocorrelation functions, Q-statistics, and cross-correlation functions, let you explore the time series properties of your data.
EViews provides random number generators, density functions and cumulative distribution functions for eighteen different distributions. These may be used in generating new series as well as scalar and matrix expressions.
Seasonal Adjustment
EViews 4 includes support for additive and multiplicative difference seasonal adjustment methods, and provides easy-to-use front-end support for the U.S. Census Bureau's X11 seasonal adjustment program, the newly released Census X12-ARIMA, and 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.
EViews includes a wide range of single and multiple equation estimation techniques for both time series and cross section data.
Basic estimators include ordinary least squares (multiple regression), two-stage least squares and nonlinear least squares. Weighted estimation is available with all of these techniques. Specifications may include polynomial lag structures on any number of independent variables.
In addition to these basic estimators, EViews supports estimation and diagnostics for a variety of advanced models.
EViews sophisticated calculus engine computes and displays analytic derivatives for the majority of nonlinear regression specifications.
ARCH models
You may estimate a variety of Autoregressive Conditional Heteroskedasticity (ARCH) models. EViews handles GARCH(p,q), EGARCH, TARCH, and Component GARCH specifications. The mean equation of ARCH models may include ARCH and ARMA terms, and both the mean and variance equations allow for exogenous variables.
Generalized Method of Moments
EViews supports GMM estimation for both cross-section and time series data (single and multiple equation). Weighting options include the White covariance matrix for cross-section data and a variety of HAC covariance matrices for time series data. The HAC options include prewhitening, either quadratic or Bartlett kernels, and fixed, Andrews, or Newey-West bandwith selection methods.
Limited Dependent Variables
EViews estimates models for binary, ordered, censored and truncated (Tobit), and count data. The binary, ordered, censored, and truncated models may be estimated for likelihood functions based on normal, logistic, and extreme value errors. Count models may use Poisson, negative binomial, and quasi-maximum likelihood (QML) specifications. EViews optionally reports generalized linear model or QML standard errors.
System Estimation
EViews supports estimation of both linear and nonlinear systems of equations by OLS, two-stage least squares, seemingly unrelated regression, three-stage least squares, GMM, and FIML. The system may contain cross equation restrictions and autoregressive errors of any order.
Vector Autoregression
Vector Autoregression and Vector Error Correction models are easily estimated. Once estimated, you may examine the impulse response functions and variance decompositions for the VAR or VEC. VAR impulse response functions and decompositions feature standard errors calculated either analytically or by monte carlo methods (analytic not available for decompositions) and may be displayed in a variety of graphical and tabular formats.
You may impose and test linear restrictions on the cointegrating relations and/or adjustment coefficients. EViews VARs also along you to estimate Structural factorizations (VARs) by imposing short-run (Sims 1986) or long-run (Blanchard and Quah 1989) restrictions.Over-identifying restrictions may be tested using the LR statistic reported by EViews.
VAR views 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, view correlograms and autocorrelations, or perform various multivariate residual bsaed diagnostics.
Pooled Time Series-Cross Section
EViews features a Pool object designed to facilitate working with pooled, time series-cross section data. Unbalanced or balanced data sets with unlimited length time series and up to several hundred cross sections are easily analyzed.
Estimation options include fixed and random effect specifications for the intercept, weighted least squares, and seemingly unrelated regression, plus all of the estimators allowed for EViews system objects. Coefficients on specific variables (including AR terms) can be constrained to be identical, or allowed to differ across the cross-section.
State-Space Models
A sspace object allows estimation of a wide variety of single- and multi-equation models dynamic structural time-series models using the Kalman Filter algorithm. Among other things, you can use the sspace object to estimate random and time-varying coefficient models and ML ARMA specifications.
Sophisticated procs and views give you access to powerful filtering and smoothing tools so that you can view or generate one-step ahead, filtered, smoothed signals, states, errors, etc. EViews' built-in forecasting procedures also provide easy-to-use tools for in- and out-of-sample forecasting using n-step ahead or smoothed values.
User-Defined Maximum Likelihood Estimation
EViews 4 features an object (the LogL) for handling user-specified maximum likelihood estimation problems.
Simply use standard EViews expressions to describe the log likelihood contribution of each observation in your sample, and EViews will do the rest...
Once an equation or system is estimated, you can use EViews to perform a wide array of specification evaluation and diagnostic tests.
These tests include Wald tests of linear and nonlinear coefficient restrictions, likelihood ratio and F-tests for omitted variables, Lagrange multiplier tests for serial correlation and ARCH, White heteroskedasticity tests, Ramsey RESET tests, and Chow forecast and breakpoint tests.
Additional tests exist for specific models. As with other object views, all hypothesis tests can be generated by a simple menu selection from an equation or system window.
With EViews, you need not concern yourself about the complexities of making forecasts. You can concentrate on the substance of the forecasting problem. For single equation models, just select a menu item and EViews will compute a static or dynamic forecast with optional forecast standard errors and a graph of the 95 percent forecast confidence. Successful forecasting equations can be saved in your workfile or stored in an EViews database.
Simultaneous Equation Solution and Simulation
The model object, which is used for simultaneous equation simulation and solution provides the features most commonly requested by model builders.
Variable dependencies and the block structure of the model’s equations are displayed with a simple mouse click. Reference equations by name and the model is updated automatically whenever the equation is reestimated. You can even use the model to manage multiple solution scenarios for comparing simulation results under various sets of assumptions.
The EViews model object makes it easy to perform non-stochastic or stochastic simulation using either Gauss-Seidel or Newton solvers. Built-in views and procedures display simulation results in graphical or tabular form. Forward solution (currently unavailable with stochastic solution) allows you to solve for model consistent expectations. EViews provides sophisticated add factor support, including equation normalization. You can even solve simple control problems where the values for an exogenous control variable are found so that an endogenous variable achieves a user specified target.
Powerful modeling tools are only useful if you can easily access your data. EViews provides the widest range of data management tools available in any econometric software.
Extensive Function Library
EViews 4 contains an extensive library of functions for working with and transforming your data. In addition to standard mathematical and trigonometric functions, EViews provides functions for computing descriptive statistics, specialized date and time series data functions, functions for working with a variety of statistical distributions, as well as special functions.
EViews’ powerful tools for expression handling mean that you can use expressions virtually anyplace you would use a series. You don't have to create new variables to work with the logarithm of Y, the moving average of W, or the ratio of X to Y (or any other valid expression). Instead, you can use the expression in compute descriptive statistics, as part of an equation or model specification, or in constructing graphs.
When you forecast using an equation with an expression for the dependent variable, EViews will (if possible) allow you to forecast the underlying dependent variable and will adjust the estimated confidence interval accordingly.
For example, if the dependent variable is specified as LOG(Y), you can elect to forecast either the log or the level of Y, and to compute the appropriate, possibly asymmetric, confidence interval.
EViews 4 has built-in database features. An EViews database is a collection of EViews objects maintained in a single file on disk. It need not be loaded into memory in order to access an object inside it, and the objects in the database are not restricted to being of a single frequency or range. EViews databases support powerful query features which can be used to search through the database for a particular series or select a set of series with a common property.
Series contained in EViews databases may be accessed and used by EViews procedures without being fetched into workfiles. Automatic search capabilities allow you to specify a list of databases to be searched when a series you need cannot be found in the current workfile.
Database Support for RATS, TSP, GiveWin, and Aremos TSD Files
EViews 4 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.
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 DLX databases. The same, easy to use, EViews database interface has been extended to these data formats.
Remote Data Access
In addition to local databases, EViews has the ability to query and access data from remote databases via the Internet. Initially, remote access is only available to databases hosted by Standard & Poor’s/DRI. In the future, software will be available from QMS that will make it possible for anyone to host a remote database.
Frequency Conversion
When you import data from a database, they are automatically converted to the frequency of your current project. EViews 4 has options for frequency conversion, as well as support for the conversion of daily and weekly data. Series may be assigned a preferred conversion method, allowing you to use different methods for different series without having to specify the conversion method every time a series is accessed.
File Import and Export
EViews provides extensive read/write support for foreign files including ASCII text files, Excel .XLS files, Lotus .WK1 and .WK3 files and TSD files. In EViews 4, ASCII reads have been extended so you can precisely specify which characters should be treated as delimiters, and what text should be treated as missing values. Reading of Excel files has also been extended to allow reading from particular named sheets, and support has been added for Excel 8 (Excel 97) spreadsheets.
EViews supports a wide range of graph types including line graphs, bar graphs, pie charts, scatter diagrams, mixed line-bar graphs, high-low graphs, and scatterplots.
A variety of options give you control over line types, color, border characteristics, headings, shading and scaling, including logarithmic scaling and dual scale graphs.
Legends are automatically created and you can add labels in any scalable Windows fonts anywhere on your graph. Any number of graphs can be combined in a single graph for presentation.
You can easily incorporate your customized graphs into other Windows applications using copy-and-paste, or by exporting Windows metafiles.
Need help? EViews provides a full Windows-style help system with index and search capabilities. 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.
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EViews 4 Enterprise Edition is an enhanced version version of EViews 4. It contains all of the features of EViews 4 plus support for the proprietary data formats of several commercial data and database vendors.
The Enterprise Edition provides transparent access to Standard and Poor's DRIBase, Haver Analytics DLX, and FAME format databases. The familiar, easy-to-use EViews database interface has been extended to these data formats so that you may work with foreign databases as easily as native EViews databases.
The DRIBase system is a client server system used by DRI to provide databases at the client site which can be kept current by remote updates. Customers can also use DRIBase as a means of storing their own databases in an Sybase or Microsoft SQL Server system.
The Haver database format is a binary format used by Haver Analytics when distributing data.
The FAME format is a binary format written by FAME database products. FAME provides a variety of products and services for working with time series data.
EViews Basics is a reduced feature version of EViews 4. It contains all of the features of EViews 4 except:
| • | Database Features: EViews Basics supports only read access to EViews databases. It cannot not create new databases or write into databases. It does not provide access to Haver Analytics databases. Remote DRI database access is supported. You will still be able to read data from and write data to Excel spreadsheet files or plain text ASCII files in the Basics version. |
| • | Dated Data Tables: The EViews table editor that allows you to create presentation tables of data, including mixed frequencies is not included. |
| • | Advanced estimators for ARCH, GMM, Pooled cross section-time series, Censored variable models (TOBIT), Ordered choice models, Count models, State Space models, System Estimation (3SLS, SUR, GMM), and user-specified maximum likelihood (LogL) are not included. Included in Basics are: Linear & Nonlinear LS and TSLS, ARMA, Logit, Probit, VARs, Cointegration analysis, and all other statistical procedures of EViews 4. |
| • | Model simulation is limited to models of ten equations or less. |
The EViews Student Version is a low-cost alternative to the full version of EViews, and is specially designed for classroom instructional settings where the full power of EViews is not required.
EViews 3.1 Student Version provides students with access to the innovative object-oriented user interface of EViews 3.1. As always, EViews' built-in procedures are only a mouse click away and provide the tools most frequently used in practical econometric and forecasting work.
While it does contain some capacity and feature limitations, EViews 3.1 Student Version provides most of the capabilities of our Standard Version. We are confident that EViews 3.1 Student Version will prove to be an ideal solution to all of your instructional and academic needs.
Now on CD-ROM!
The EViews 3.1 Student Version package includes a 56-page Student Version manual (featuring an extended case study), as well as a CD-ROM disc containing the software, sample data, a full Windows-style Help System, and Portable Document Format (PDF) files of documentation for both the Student and Standard Versions of EViews 3.1. Both the Windows Help System and the PDF files are searchable and hypertext linked for quick access to program documentation.
A Modern Interface
EViews Student Version uses the same easy-to-use Windows interface as our Standard Version. It's all there...Full mouse support takes advantage of all of the features of a modern, graphical user interface. Context sensitive menus and dialogs guide you thorugh your analysis, showing you the different views and procedures available for analyzing your data, and where necessary, prompting you for additional input. Multiple window support allows you to examine various aspects of your data or results; for example, two sets of equation results, or both the coefficient estimates and graphs of forecasted values.
You can also use the Windows clipboard to transfer data and results between EViews and other Windows applications. Highlight your Microsoft Excel data and copy-and-paste it directly into EViews. Copy-and-paste your regression results to Microsoft Word, and EViews will use create a formated table of results in Word. Of course if you don't like cut-and-paste, EViews supports direct file access to Lotus WKS, WK1, and WK3 files, Microsoft Excel XLS files, and Microsoft Windows Metafiles).
Need help? EViews provides a full Windows-style help system containing the bulk of our printed documentation. Use Windows Help's indexing and search capabilities to find the information you need to get the job done.
Basic Statistics
EViews provides sophisticated tools for computing descriptive statistics and for performing hypothesis tests (including simple one-way ANOVA).
Graphical presentations of histograms, cumulative distribution, survivor, and quantile functions allow you to characterize the distribution of your data. Quantile-quantile plots allow you to compare your data to empirical and theoretical distributions. EViews also calculates kernel density estimates, and produces scatterplots with curve fitting using ordinary, transformation, kernel, and nearest neighbor regression.
Do you work with time series data? EViews built-in unit root tests (ADF and Phillips-Perron), cointegration tests, causality tests, and tools for computing autocorrelation and partial autocorrelation functions, Q-statistics, and cross-correlation functions, let you explore the time series properties of your data...
Estimating Equations
EViews Student Version includes basic estimators such as ordinary least squares (multiple regression), two-stage and nonlinear least squares. You can perform weighted estimation, and can add polynomial lag structures on any number of independent variables with these specifications. EViews Student Version also provides built-in tools for estimating binary probit and logit models.
EViews automatically displays appropriate summary statistics for most specifications: coefficients, t-statistics, standard errors (ordinary, White, or Newey-West) and covariances, F-Statistic with probability, R-square, R-square adjusted for degrees of freedom, sum-of-squared residuals and standard error of the regression, log-likelihood, Durbin-Watson statistic, Akaike and Schwarz Information Criteria.
EViews advanced estimators allow you to estimate sophisticated time series models involving autoregressive and moving average errors, using the backcasting method of Box and Jenkins, or conditional least squares. Seasonal autoregressive and seasonal moving average specifications may also be estimated.
Once your specification is estimated, EViews provides powerful evaluation, testing and forecasting tools. You can easily compute Wald and likelihood ratio tests for coefficient restrictions and omitted or redundant variables; correlogram, Q-statistic and normality tests for residuals; serial correlation LM and Durbin-Watson, ARCH LM, White Heteroskedasticity, Chow Forecast and breakpoint, Ramsey RESET, and (for linear models only) recursive least squares, recursive residual, CUSUM, CUSUM of squares, One-step and N-step forecast tests.
Need to perform a forecast? Built-in procedures make constructing forecasts a snap. Use single, double, or Holt-Winters exponential smoothing to create your forecast. If you prefer, you can use the results from a previously estimated equation. Simply specify the forecast interval, whether you want dynamic or static forecasts, and EViews will do the rest.
Student Version Limitations
The Student Version is a restricted version of EViews 3.1 that differs from the Standard Version along two primary dimensions. First, there are capacity restrictions which limit the size of projects. Each series is limited to 1,000 observations, and the total number of data points (series x observations per series) is limited to 10,000. In addition, there is a limit of 50 objects (series, equations, graphs, etc.) in each workfile.
Second, the Student Version lacks EViews' more advanced analytical and programming features. The following features, though available in the Standard Version of EViews 3.1, are not available in the Student Version:
• X-11 seasonal adjustment. Seasonal adjustment by the ratio-to-moving average and difference-from-moving average techniques are included in the Student Version.
• Write access to EViews databases.You may, however, read from existing EViews databases, and read and write from standard EViews workfiles. Read-Write access to the DRI Basic Economics Database and the Haver databases is not provided.
• Generalized Method of Moments (GMM), State space estimation, ARCH estimation and forecasting, ordered discrete choice, count, and censored/truncated equation estimation, user-specified log-likelihood estimation.
• System estimation by Seemingly Unrelated Regression, Two and Three-Stage Least Squares, GMM and FIML.
• Programming Capabilities. EViews 3.1 contains an advanced programming language that allows you to write and execute sophisticated programs in batch mode. The Student Version is limited to interactive use.
• Matrix Operations. The standard version of EViews 3.1 provides an extensive set of functions for matrix algebra and manipulation that is not available in the Student Version.
System Requirements:
EViews 3.1 Student Version is a 32-bit program that requires and takes full advantage of the new features of Windows 9x, and Windows NT 4.0 or 2000.
Since EViews 3.1 Student Version is distributed on CD-ROM, you will need access to a CD-ROM drive to install and/or run the software.