System

System of equations for estimation.

System Declaration

system declare system object.

Declare a system object by entering the keyword system, followed by a name:

system mysys

To fill a system, open the system and edit the specification view, or use append. Note that systems are not used for simulation. See
“Model”.

System Methods

3sls three-stage least squares.

arch estimate generalized autoregressive conditional heteroskedasticity (GARCH) models.

fiml full information maximum likelihood.

gmm generalized method of moments.

ls ordinary least squares.

sur seemingly unrelated regression.

tsls two-stage least squares.

wls weighted least squares.

wtsls weighted two-stage least squares.

System Views

cellipse confidence ellipses for coefficient restrictions.

coefcov coefficient covariance matrix.

correl display graphs or tables of residual autocorrelations and cross-correlations.

derivs derivatives of the system equations.

display display table, graph, or spool in object window.

endog table or graph of endogenous variables.

estcov display the covariance matrix used in estimation.

garch conditional variance/covariance of (G)ARCH estimation.

grads examine the gradients of the objective function.

jbera multivariate residual normality test.

label label information for the system object.

output table of estimation results.

qstats multivariate residual autocorrelation Portmanteau tests.

representations text showing specification of the system.

residcor residual correlation matrix.

residcov residual covariance matrix.

resids residual graphs or spreadsheets.

results table of estimation results.

spec text representation of system specification.

wald Wald coefficient restriction test.

System Procs

append add a line of text to the system specification.

autospec automatically create system specification text.

clearhist clear the contents of the history attribute.

clearremarks clear the contents of the remarks attribute.

copy creates a copy of the system.

displayname set display name.

makeendog make group of endogenous series.

makegarch generate conditional variance series.

makeloglike create and save log likelihood contribution from system (ARCH estimation).

makemodel create a model from the estimated system.

makeresids make series containing residuals from system.

olepush push updates to OLE linked objects in open applications.

setattr set the value of an object attribute.

updatecoefs update coefficient vector(s) from system.

System Data Members

Scalar Values (individual equation data)

@coefcov(i, j) covariance of coefficients i and j.

@coefs(i) coefficient i.

@dw(k) Durbin-Watson statistic for equation k.

@eqncoef(k) number of estimated coefficients in equation k.

@eqregobs(k) number of observations in equation k.

@meandep(k) mean of the dependent variable in equation k.

@r2(k) R-squared statistic for equation k.

@rbar2(k) adjusted R-squared statistic for equation k.

@sddep(k) standard deviation of dependent variable in equation k.

@se(k) standard error of the regression in equation k.

@ssr(k) sum of squared residuals in equation k.

@stderrs(i) standard error for coefficient i.

@tstats(i) t-statistic or z-statistic for coefficient i.

c(i) i-th element of default coefficient vector for system (if applicable).

Scalar Values (system level data)

@aic Akaike information criterion for the system (if applicable).

@detresid determinant of the residual covariance matrix.

@hq Hannan-Quinn information criterion for the system (if applicable).

@jstat J-statistic — value of the GMM objective function (for GMM estimation).

@linecount scalar containing the number of lines in the System object.

@logl value of the log likelihood function for the system (if applicable).

@ncoefs total number of estimated coefficients in system.

@neqn number of equations.

@regobs number of observations in the sample range used for estimation (“@regobs” will differ from “@eqregobs” if the unbalanced sample is non-overlapping).

@schwarz Schwarz information criterion for the system (if applicable).

@totalobs sum of “@eqregobs” from each equation.

Vectors and Matrices

@coefcov covariance matrix for coefficients of equation.

@coefs coefficient vector.

@estcov (sym) residual covariance matrix used in estimation (see
System::estcov).

@pvals vector containing the coefficient probability values.

@residcov (sym) covariance matrix of the residuals.

@stderrs vector of standard errors for coefficients.

@tstats vector of t-statistic or z-statistic values for coefficients.

String values

@attr("arg") string containing the value of the arg attribute, where the argument is specified as a quoted string.

@command full command line form of the estimation command. Note this is a combination of @method and @options.

@description string containing the System object’s description (if available).

@detailedtype returns a string with the object type: “SYSTEM”.

@displayname returns the System’s display name. If the System has no display name set, the name is returned.

@line(i) returns a string containing the i-th line of the System object.

@method command line form of estimation method type (“ARCH”, “LS”, etc....).

@name returns the System’s name.

@options command line form of estimation options.

@remarks string containing the system object’s remarks (if available).

@smpl sample used for estimation.

@svector returns an Svector where each element is a line of the System object.

@svectornb same as @svector, with blank lines removed.

@type returns a string with the object type: “SYSTEM”.

@updatetime returns a string representation of the time and date at which the System was last updated.

System Examples

To estimate a system using GMM and to create residual series for the estimated system:

sys1.gmm(i,m=7,c=.01,b=v)

sys1.makeresids consres incres saveres

To test coefficients using a Wald test:

sys1.wald c(1)=c(4)

To save the coefficient covariance matrix:

sym covs=sys1.@coefcov