EViews 6.0
- Latest
version now available!
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.
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 XP with
the 3G switch, Vista, or 64-bit XP or Vista, data capacity can be up
to two and one-half times as large as under EViews 5.1.
Statistics and
Econometrics Features
Statistics
• 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, generalized 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).
Econometrics
General
• 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. Specialized 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.
Time-series
• 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.
Graphics
We have completely revamped
our graphics engine, allowing you greater control over the display
of data, and supporting the construction of categorical graphs.
Basic Features
• 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.
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:
• Displaying a bar plot
comparing the mean incomes of individuals living in each state.
• 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.
• Showing wage-education
profiles for both male and female workers.
• Drawing histograms and
boxplots of wages for union and non-union workers in different
industries.
Customization 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
Output Management
• 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 organizing 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.
Models
EViews 6 model solution may be
up to 30 times faster than under EViews 5.1. Among the improvements:
• 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.
Databases
• 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.
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.
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 (ODBC support is provided
only the Enterprise Edition). (Access to SAS native format files,
version 8 or earlier, is available using SAS ODBC drivers which must
be purchase separately from SAS.)
Drag-and-drop
support for reading data; simply drop files into EViews for
automatic conversion of foreign data into EViews workfile format.
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.
Additional
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.
Added 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.
Cointegration
tests now use the MacKinnon-Haug-Michelis critical values and
p-values. Output displays the critical value for any user-specified
size.
Bivariate normal
density and cumulative distribution function evaluation support is
now provided.
Graph and Tables
Filled area
graphs.
Boxplots
Formatted
spreadsheet display allows you to customize the display of your
series and group data values.
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.
Evaluation Copy
We provide an evaluation copy of EViews software. The evaluation copy
is the full version of the software allowing the user to install it
on their computer for 1 month. The price for the evaluation copy is Singapore
Dollars
250 (for Singapore) and Singapore Dollars 330 (for overseas). This fee is deducted
from the purchase price if the software is ordered within 30 days
from the completion date of the evaluation. The fee covers postage
and administration costs.
PRICING AND ORDER
INFORMATION
Please contact us for additional information
about EViews & its products, including price quotes at
eviews@eastasiatc.com.sg |
