EViews Quick Reference

EViews Quick Reference
inspired by the R Reference Card . . .
This ‘Quick Reference’ shows only a small selection of
EViews commands and functions, for a more extensive
summary see \Quick Help Reference” in the EViews Help
menu. The complete manual is available as pdf in the
EViews Help menu.
Workfile, Pages, Input & Output
cd change default directory, e.g. cd \c:nmydata”;
wfcreate Create a new workfile;
Cross section:
wfcreate u num observations
e.g.: wfcreate(wf=mywf) u 60
Time series and panel data:
wfcreate frequency start end [num cross sect]
frequencies: a annual, q quarterly, m monthly, . . . ;
wfopen opens EViews workfile; can also open foreign file
formats, use options type = [stata, spss, excel, . . . ]
wfsave save workfile
pagecreate creates new page within existing workfile,
e.g.
pageappend
pagestruct assign a structure to the active workfile page;
pageload
pagecopy
pagecontract smpl spec
pagedelete
pagesave
smpl sets the workfile sample to use for statistical operations and series assignment expressions;
Special keywords: @all, @first, @last;
Examples:
smpl 1986 2003; or smpl 1986 @last;
smpl @all if x1 > 0
Resetting sample: smpl @all
show show object window
print print view
freeze create view object (graph or table)
output redirect printer output
read
write
Auxiliary Commands
rename guess what
delete guess what
copy also for frequency conversions or merging data
@expand may be added in estimation to indicate the use
of one or more automatically created dummy variables.
Objects
For extensive help on objects see EViews Help ! Quick
Help Reference ! Object Reference
series Series of numeric observations; Accessing individual values: ser(i) i-th element of the series ser
from the beginning of the workfile.
@elem(ser, j ) function to access the j -th observation of the series ser, where j identifies the date or
observation.
Example: series x2 = x1 – @mean(x1)
Creating dummy varables:
series D1 = condition produces dummy variable
which is 1 if condition is fullfilled and else 0, e.g.
series D1 = @all if x1 >= @mean(y)
frml create numeric series object with a formula
for auto-updating.
group create a group object.
Example: group mygroup1 ser1 ser2 . . .
groups can also be used as regressor list, e.g.
ls y c mygroup1
equation Equations are used for single equation estimation, testing, and forecasting.
Equation Methods: ls, tsls (2-stage ls), binary
(logit, probit), ordered, arch, censored, gmm, . . .
Data Members: Scalar Values: @aic Akaike information criterion; @coefcov(i,j ) covariance of coefficient estimates i and j ; @coefs(i) i-th coefficient value; @dw Durbin-Watson statistic; @f Fstatistic; @meandep mean of the dependent variable;
@ncoef number of estimated coefficients; @r2 Rsquared statistic; @rbar2 adjusted R-squared statistic; @regobs number of observations in regression;
@schwarz Schwarz information criterion; @sddep
standard deviation of the dependent variable; @se
standard error of the regression; @ssr sum of squared residuals; @stderrs(i) standard error for coefficient i; @tstats(i) t-statistic value for coefficient
i; c(i) i-th element of default coefficient vector for
equation (if applicable).
Vectors and Matrices: @coefcov covariance matrix
for coefficient estimates; @coefs coefficient vector;
@stderrs vector of standard errors for coefficients;
@tstats vector of t-statistic values for coefficients.
graph Specialized object used to hold graphical output.
Declaration either with graph or freeze
Examples: graph myline.line ser1, or
freeze(myline) ser1.line;
graph myscat.scat ser1 ser2, or
group grp2 ser1 ser2, freeze(myscat) grp2.scat
table Formatted two-dimensional table for output display. Declaration either with table or freeze
Example:
table(2,2) mytable ’ creates 2 × 2 table
mytable(1,1) = “First row, first column”
mytable(2,1) = “R2 = “
mytable(2,1) = [email protected]
sample description of a set of observations to be used in
operations.
text Object for holding arbitrary text information.
scalar a scalar holds a single numeric value. Scalar values may be used in standard EViews expressions
in place of numeric values.
vector declare vector object (one dimensional array of
numbers). Example: vector(10) myvect1 ’ creates
myvect1 with 10 rows.
rowvector declare rowvector object. Example:
rowvector(10) myvect2 ’ creates myvect2 with
10 columns.
coef coefficient vector. Coefficients are used to represent
the parameters of equations and systems.
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matrix declare matrix object (two-dimensional array).
Accessing elements: Simply append \(i, j )” to the
matrix name (without a ‘.’)
Examples: matrix(10,3) results;
matrix [email protected]
sym symmetric matrix (symmetric two-dimensional array).
alpha Alpha (alphanumeric) series. An EViews alpha series contains a set of observations on a variable containing string values.
system System of equations for estimation. System Methods: 3sls, 3sls, arch, fiml, gmm, ls, sur, tsls,
wls, wtsls.
var Vector autoregression and error correction object.
model declare model object, a set of simultaneous equations used for forecasting and simulation
logl Likelihood object. Used for performing maximum
likelihood estimation of user-specified likelihood
functions.
Matrix Commands and Functions
stom series to matrix; converts a group to a matrix;
stom(groupname, matrixname)
mtos matrix to series; converts a vector or matrix to a
series or group; mtos(matrixname, groupname)
@det Calculates the determinant of a square matrix or
sym.
@transpose Transposes matrix object.
@inverse Returns the inverse of a square matrix object or sym.; e.g.: let X be a N × K matrix and y a N × 1 vector, then the coefficient vector b of the OLS regression (for
K = 3) can be calculated by: coef(3) b =
@inverse(@transpose(X )*X )*@transpose(X )*y
@inner Computes the inner product of two vectors or series, or the inner product of a matrix object; e.g. OLS estimator: coef(3) b =
@inner(X )*@transpose(X )*y
Tests
auto [eq] Breusch-Godfrey LM tests for serial correlation
in the estimation residuals.
hettest [eq] test for heteroskedasticity, can be a
Breusch-Pagan-Godfrey (the default option), Harvey, Glejser, ARCH or White style test;
white [eq] White’s test for heteroskedasticity of residuals;
chow [eq] Chow breakpoint or Chow forecast tests for
parameter constancy;
facbreak [eq] factor breakpoint test for stability, using
Dummy;
reset [eq] Ramsey’s regression specification error test;
statby [series] statistics by classification;
stats [series, group] descriptive statistics table, e.g.: wage.statby(max,min) sex race;
testadd, testadrop [eq, panel] likelihood ratio test
whether to add (drop) regressors to (from) an estimated equation;
testby [series] equality test by classification, e.g.: wage.testby(med) race;
testbtw [group] tests of equality for mean, median, or
variance, between series in group
teststat [series] simple hypothesis tests;
ubreak [eq] Andrews-Quandt test for parameter stability
at some unknown breakpoint;
uroot [series, group, panel] unit root test;
wald [eq] Wald test of coefficient restrictions for an equation object;
Panel & Pool
auto [eq] Breusch-Godfrey LM tests for serial
pagestruct assign a structure to the active workfile page;
pagestack
pageunstack
Descriptive Statistics
stats [series, group, vector, . . . ] Computes and displays
a table of means, medians, maximum and minimum
values, standard deviations, and other descriptive
statistics of one or more series or a group of series.
freq [series, alpha] performs a one-way frequency tabulation. The options allow you to control binning
(grouping) of observations.
hist computes descriptive statistics and displays a histogram for the series.
boxplot [series, group, vector, . . . ] display boxplots for
each series or column.
Some Functions
@abs(x) absolute value of x.
@obs(x) the number of non-missing observations for x in
the current sample.
@mean(x) average of the values in x.
@median(x) median of the values in x.
@quantile(x; q) the q-th quantile of the series x.
@min(x) minimum of the values in x.
@max(x) maximum of the values in x.
@d(x) First difference, equals x – x(-1)
@dlog(x) First difference of the logarithm
@exp(x) exponential, ex
@log(x) Natural logarithm
@cor(x; y) the correlation between x and y.
@cov(x; y) the covariance between x and y (division by
N).
@stdevp(x) square root of the population variance
@stdevs(x) square root of the unbiased sample variance.
Note this is the same calculation as @stdev
@sum(x) the sum of x
@trend trend variable.
@iff(s; x; y) returns x if condition s is true; otherwise
returns y. Note this is the same as @recode.
Statistical Distribution Functions: There are four
functions associated with each distribution. The first character of each function name identifies the type of function:

Function Type: Beginning of Name:
Cumulative distribution (CDF) @c
Density or probability
Quantile (inverse CDF)
Random number generator
@d
@q
@r

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The remainder of the function name identifies the distribution, e.g. chisq, fdist, tdist, norm, unif, . . .
Examples:
@runif(1,10) . . . random number from uniform distribution between 1 and 10; @cfdist(x,v1,v1) . . . cumulated Fdistribution for x with v1 nominator degrees of freedom
and v2 denominator df; @dchisq(x,v) . . . density for χ2
distribution for x with v df.

Programming:
Structures
Commands & Control

’ (single apostrophe) comment character, instructs
EViews to ignore all text following the apostrophe
until the end of the line;
(underscore), continuation character, allows { used as
last (!) character of a line { to continue a command
on the next line;
! starting character of control variable (numeric!), e.g.
!pi = 3.14
% starting character of string variable (enclosed in double
quotes), e.g. %name = “Herbert Stocker”
%0 { %9 program arguments, special string variables that
are passed to a program when the program is run.
fg for replacement variables; e.g. from %x = “GDP” and
equation eq1.ls f%xg c f%xg(-1) EViews produces equation eq1.ls GDP.ls c GDP(-1).
if statement in a program The if statement marks
the beginning of a condition and commands to be
executed if the statement is true. The statement
must be terminated with the beginning of an ELSE clause, or an ENDIF.
if [condition] then
[commands to be executed if condition is true]
else
[commands to be executed if condition is false]
endif
for loop in a program The FOR loop allows you to
repeat a set of commands for different values of a
control or string variable.
for counter=start to end [step stepsize]
[ commands ]
next
e.g. for numerical variables:
for !i = 1 to 15
series scalexf!ig = xf!ig/!i
next
For string variables:
for %y gdp gnp ndp nnp
equation f%ygtrend.ls %y c f%yg(-1) @trend
next
open opens a program file, or text (ASCII) file.
run executes a program.
exit exit the EViews program.
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