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

When your dependent variable takes on a limited set of values or is censored or truncated, EViews can take account of this information in the estimation procedure. 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/Error Correction Models

Vector Autoregression and Vector Error Correction models can be easily estimated by EViews. 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.

VARs support a variety of views to allow you to examine the structure of your estimated 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 based diagnostics.

Panel Data Analysis and Pooled Time Series-Cross Section

EViews features a wide variety of tools designed to facilitate working with panel or /pooled time series-cross sectiondata. Unbalanced or balanced data sets with unlimited length time and/or cross-sections are easily analyzed. In addition to ordinary linear and non-linear least-squares, equation estimation methods include 2SLS/IV and Generalized 2SLS/IV, which can be used to estimate complex dynamic panel data estimation including Anderson-Hsiao and Arellano-Bond types of estimators.

All of these methods allow both time and cross-section fixed and random effect specifications. For random effects models, quadratic unbiased estimators of component variances include Swamy-Arora, Wallace-Hussain and Wansbeek-Kapteyn. 

Also supported are AR specifications, weighted least squares, and seemingly unrelated regression. Coefficients on specific variables (including AR terms) can be constrained to be identical, or allowed to differ across the cross-section.

State-Space Models

The state-space 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 space-state 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 5 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...

Specification Evaluation and Diagnostics

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.

Forecasting and Simulation

In 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.

Data Management

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 5 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, by-group statistics, specialized date and time series data functions, functions for working with a variety of statistical distributions and date and string handling.

Sophisticated Expression Handling

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.

Links, Formulas and Values Maps

Links allow you to create series that link to data contained in other workfiles or workfile pages. Links allow you to combine data at different frequencies, or match merge in data from a summary page into an individual page such that the data is dynamically updated whenever the underlying data change. Similarly, within a workfile, formulas can be assigned to data series so that the data series are automatically recalculated whenever the underlying data is modified. 

Value labels (e.g., "High", "Med", "Low", corresponding to 2, 1, 0) may be applied to numeric or alpha series so that categorical data can be displayed with meaningful labels. Built-in functions allow you to work with either the underlying or the mapped values when performing calculations.

Data types

EViews can handle complex data structures, including irregular dated data, cross-section data with observation identifiers, and dated and undated panel data. In addition to numerical data, an EViews workfile can also contain alphanumeric (character string) data and series containing dates, which can be further manipulated using an extensive library of functions.

File Import and Export

EViews provides extensive read/write support for foreign formats, including Excel, ASCII/Text, SPSS, SAS (transport), Stata,  Html, Microsoft Access, Gauss Dataset, Rats, WinGive/PC Give, TSP, Aremos, dBase, Lotus and Binary. Access to SAS native format files, version 8 or earlier, is also available if a SAS ODBC driver is installed on the system (which must be purchased separately through SAS)

EViews Databases

EViews 5 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.

Enterprise Edition Support for ODBC, 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 access to data contained in relational databases (via ODBC drivers) and to databases in a variety of proprietary formats used by commercial data and database vendors. Open Database Connectivity (ODBC) is a standard supported by many relational database systems including Oracle, Microsoft SQL Server and IBM DB2. EViews allows you to read or write entire tables from ODBC databases, or to create a new workfile from the results of a SQL query. For time series data, EViews also supports access to FAME databases, both local and server based, Global Insight's DRIBase databases, and Haver Analytics DLX databases. For time series databases, the same, easy to use, EViews database interface is available no matter what the source of the data.

Frequency Conversion

When you import data from a database, they are automatically converted to the frequency of your current project. EViews 5 has many options for frequency conversion, and includes support for the conversion of daily, weekly or irregular-frequency 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.

Graphics

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.

Customizing a graph is as simple as dragging graphic elements around the screen. Want to change the characteristics of a legend or a text label? Just click on it and your options are immediately presented in easy to understand dialogs.

You can easily incorporate your customized graphs into other Windows applications using copy-and-paste, or by exporting Windows metafiles.

Windows On-Line Help

Need help? EViews provides a full Windows-style help system with index and search capabilities.  n 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.

A Powerful Programming Language

Point-and-click is fine, but you feel more comfortable entering commands. Besides, you need programming tools and capabili-ties. Well, EViews is really two programs in one. In addition to its state-of-the-art windowing interface, EViews includes a powerful command language that allows access to all menu items.

Modelled loosely after the BASIC programming language but with new object-oriented extensions and matrix handling capabilities.EViews allows you to enter individual commands for immediate or batch execution. Your programs can make use of advanced capabilities such as looping and condition branching, as well as subroutine and macro processing. Matrix primitives, from simple multiplication and inversion, to more advanced procedures for Kronecker products, eigenvector solution, and singular value decomposition, provide you with the tools you need for solving most complex problems.

Data Capacity and System Technical Requirements

EViews 5 supports most versions of the Windows Operating system including: Windows 98/Me/NT 4.0/2000/XP. With sufficient memory in your computer, you can tackle problems involving millions of observations or thousands of series. The only fundamental capacity limit is that no single data series or matrix may contain more than 4 million observations. And because we take full advantage of 32-bit Windows’ virtual memory, you can work with data sets that exceed your system’s physical memory.

• CPU
  Pentium
• Operating Systems
  Windows 95, Windows 98 (SE), Windows NT 4.0, Windows Me, Windows 2000, Windows XP.
• Memory
  32 MB for Windows 98, Me or NT 4.0; 64 MB for Windows 2000 or Windows XP.
• Disk Space
  60.5 MB of available hard disk space for the program, supporting files, example files and documentations. 32 MB for program and help systems only
• Monitor
  VGA, super VGA, or compatible display
• Hardware
  CD-ROM

© Copyright 2004 QMS