EViews Features | New Features EViews 8 | System
Requirements | Further Information
EViews 8 offers academic researchers, corporations, government
agencies, and students access to powerful statistical,
forecasting, and modeling tools through an innovative, easy-to-use
Its combination of power and ease-of-use make EViews
8 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.
By now EViews is looking back on 2 decades of development work.
EViews 8 features a multiplicity of enhancements or updates in the
- General EViews Interface,
- Data Handling,
- Programming Support,
- External Interfaces,
- Econometrics and Statistics
For this reason EViews continues to set the standard for
econometric and forecasting software.
New: EViews Version 8!
One of the most exciting new feature is the full 64-bit
support! Now You have the ability to work with even
greater data files!
See also our PDF-Document to have an overview of all new
features: "Whats New in EViews 8?"
in EViews 8
EViews an Econometric Tool
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 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
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.
EViews 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
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
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
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
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
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 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
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
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
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.
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
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 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
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
Extensive Function Library
EViews 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.
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
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 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
EViews 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
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.
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 IHS EViews that will make it
possible for anyone to host a remote database.
When you import data from a database, they
are automatically converted to the frequency of your current
project. EViews 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,
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
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
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.
Modeled 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.
Windows On-Line Help
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.
- 64-bit version for much larger data sets
- General EViews Interface
- Enhanced dialog edit fields.
- Improved workfile details view.
- Workfile compare allowing quick comparison of data in
- Object Linking and Embedding (OLE) support, allowing
linking of your EViews output in other packages such as
Microsoft Excel® and Word®
- Data Handling
- Powerful new spreadsheet editing tools that allow easy
manipulation of multiple cells at once.
- Group comparison tools to compare data across multiple
- Enhanced dated data tables, including full command
- Support for writing to existing Excel® files, and
writing Excel® .XLSX files
- Transposed foreign data reading.
- Custom object attributes.
- Graphs, Tables and Spools
- New slide bar for quickly changing the visible sample in
a graph window.
- Custom lines and arrows can be drawn in graphs using the
- User defined fit lines on scatter plots.
- Graphs, tables and spools can now be saved in PDF
format. Additionally, tables may be saved as Enhanced
Econometrics and Statistics
- Error-Trend-Seasonal exponential smoothing (Hyndmen et
al., 2002 and Hyndman et al., 2008)
- Census X-13
- Panel series covariances.
- EPanel series principal components
- Switching regression (both exogenous and Markov).
- Bayesian Vector Autoregression (BVARs).
- Robust least squares.
- Breakpoint regression.
- Heckman selection models.
- Panel cointegration estimation.
- User-defined optimization.
- Testing and Diagnostics
- Multiple breakpoint testing (including Bai-Perron
- Panel serial correlation tests.
- Panel causality tests.
- Heteroskedasticity and autocorrelation consistent (HAC)
covariances for GLM models.
- Automatic computation of a robust Wald statistic for
non-intercept coefficients in models estimated with White
or HAC covariances.
- Improved model datat editing.
- Solution comparison tools.
- Enhanced command line manipulation of models
- Programming Support
- User-defined objects allowing even greater
customization of EViews
- Program editor and execution enhancements.
- New functions and commands.
- VGA, super VGA, or compatible Monitor
||Windows 2000, Windows 2003,
Windows XP (32bit or 64bit), Windows Vista (32bit or 64bit),
Windows Server 2008 (32bit or 64bit), Windows 7 (32bit or 64bit),
Windows 8 (32bit or 64bit), Windows Server 2012 (32bit or 64bit)
- 64 MB for Windows 2000
- 256 MB Windows XP
- 512 MB Windows Vista or Windows 7
- 270 MB of available hard disk space for the EViews executable,
supporting files, full documentation, and example files