Functional Summary

The AUTOREG Procedure

Functional Summary

The statements and options used with the AUTOREG procedure are summarized in the following table:

Description Statement Option

Data Set Options

specify the input data set AUTOREG DATA=

write parameter estimates to an output data set AUTOREG OUTEST=

include covariances in the OUTEST= data set AUTOREG COVOUT

write predictions, residuals, and confidence limits to an output data set OUTPUT OUT=

Declaring the Role of Variables

specify BY-group processing BY

Printing Control Options

request all printing options MODEL ALL

print transformed coefficients MODEL COEF

print correlation matrix of the estimates MODEL CORRB

print covariance matrix of the estimates MODEL COVB

print DW statistics up to order j MODEL DW=j

print marginal probability of the generalized Durbin-Watson test statistics for large sample sizes MODEL DWPROB

print the p-values for the Durbin-Watson test be computed using a linearized approximation of the design matrix MODEL LDW

print inverse of Toeplitz matrix MODEL GINV

print the Godfrey LM serial correlation test MODEL GODFREY=

print details at each iteration step MODEL ITPRINT

print the Durbin t statistic MODEL LAGDEP

print the Durbin h statistic MODEL LAGDEP=

print the log likelihood value of the regression model MODEL LOGLIKL

print the Jarque-Bera normality test MODEL NORMAL

print tests for ARCH process MODEL ARCHTEST

print the Lagrange multiplier test HETERO TEST=LM

print the Chow test MODEL CHOW=

print the predictive Chow test MODEL PCHOW=

suppress printed output MODEL NOPRINT

print partial autocorrelations MODEL PARTIAL

print Ramsey's RESET test MODEL RESET

print tests for stationarity or unit roots MODEL STATIONARITY=(PHILLIPS=)

print tests of linear hypotheses TEST

specify the test statistics to use TEST TYPE=

prints the uncentered regression R² MODEL URSQ

Model Estimation Options

specify the order of autoregressive process MODEL NLAG=

center the dependent variable MODEL CENTER

suppress the intercept parameter MODEL NOINT

remove nonsignificant AR parameters MODEL BACKSTEP

specify significance level for BACKSTEP MODEL SLSTAY=

specify the convergence criterion MODEL CONVERGE=

specify the type of covariance matrix MODEL COVEST=

set the initial values of parameters used by the iterative optimization algorithm MODEL INITIAL=

specify iterative Yule-Walker method MODEL ITER

specify maximum number of iterations MODEL MAXITER=

specify the estimation method MODEL METHOD=

use only first sequence of nonmissing data MODEL NOMISS

specify the optimization technique MODEL OPTMETHOD=

imposes restrictions on the regression estimates RESTRICT

estimate and test heteroscedasticity models HETERO

GARCH Related Options

specify order of GARCH process MODEL GARCH=(Q=,P=)

specify type of GARCH model MODEL GARCH=(...,TYPE=)

specify various forms of the GARCH-M model MODEL GARCH=(...,MEAN=)

suppress GARCH intercept parameter MODEL GARCH=(...,NOINT)

specify the trust region method MODEL GARCH=(...,TR)

estimate the GARCH model for the conditional t-distribution MODEL GARCH=(...) DIST=

estimates the start-up values for the conditional variance equation MODEL GARCH=(...,STARTUP=)

specify the functional form of the heteroscedasticity model HETERO LINK=

specify that the heteroscedasticity model does not include the unit term HETERO NOCONST

impose constraints on the estimated parameters the heteroscedasticity model HETERO COEF=

impose constraints on the estimated standard deviation of the heteroscedasticity model HETERO STD=

output conditional error variance OUTPUT CEV=

output conditional prediction error variance OUTPUT CPEV=

specify the flexible conditional variance form of the GARCH model HETERO

Output Control Options

specify confidence limit size OUTPUT ALPHACLI=

specify confidence limit size for structural predicted values OUTPUT ALPHACLM=

specify the significance level for the upper and lower bounds of the CUSUM and CUSUMSQ statistics OUTPUT ALPHACSM=

specify the name of a variable to contain the values of the Theil's BLUS residuals OUTPUT BLUS=

output the value of the error variance ${ {\sigma}^2_{t}}$ OUTPUT CEV=

output transformed intercept variable OUTPUT CONSTANT=

specify the name of a variable to contain the CUSUM statistics OUTPUT CUSUM=

specify the name of a variable to contain the CUSUMSQ statistics OUTPUT CUSUMSQ=

specify the name of a variable to contain the upper confidence bound for the CUSUM statistic OUTPUT CUSUMUB=

specify the name of a variable to contain the lower confidence bound for the CUSUM statistic OUTPUT CUSUMLB=

specify the name of a variable to contain the upper confidence bound for the CUSUMSQ statistic OUTPUT CUSUMSQUB=

option specify the name of a variable to contain the lower confidence bound for the CUSUMSQ statistic OUTPUT CUSUMSQLB=

output lower confidence limit OUTPUT LCL=

output lower confidence limit for structural predicted values OUTPUT LCLM=

output predicted values OUTPUT P=

output predicted values of structural part OUTPUT PM=

output residuals OUTPUT R=

output residuals from structural predictions OUTPUT RM=

specify the name of a variable to contain the part of the predictive error variance (v_t) OUTPUT RECPEV=

specify the name of a variable to contain recursive residuals OUTPUT RECRES=

output transformed variables OUTPUT comp TRANSFORM=

output upper confidence limit OUTPUT UCL=

output upper confidence limit for structural predicted values OUTPUT UCLM=

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Description	Statement	Option
Data Set Options
specify the input data set	AUTOREG	DATA=
write parameter estimates to an output data set	AUTOREG	OUTEST=
include covariances in the OUTEST= data set	AUTOREG	COVOUT
write predictions, residuals, and confidence limits to an output data set	OUTPUT	OUT=

Declaring the Role of Variables
specify BY-group processing	BY

Printing Control Options
request all printing options	MODEL	ALL
print transformed coefficients	MODEL	COEF
print correlation matrix of the estimates	MODEL	CORRB
print covariance matrix of the estimates	MODEL	COVB
print DW statistics up to order j	MODEL	DW=j
print marginal probability of the generalized Durbin-Watson test statistics for large sample sizes	MODEL	DWPROB
print the p-values for the Durbin-Watson test be computed using a linearized approximation of the design matrix	MODEL	LDW
print inverse of Toeplitz matrix	MODEL	GINV
print the Godfrey LM serial correlation test	MODEL	GODFREY=
print details at each iteration step	MODEL	ITPRINT
print the Durbin t statistic	MODEL	LAGDEP
print the Durbin h statistic	MODEL	LAGDEP=
print the log likelihood value of the regression model	MODEL	LOGLIKL
print the Jarque-Bera normality test	MODEL	NORMAL
print tests for ARCH process	MODEL	ARCHTEST
print the Lagrange multiplier test	HETERO	TEST=LM
print the Chow test	MODEL	CHOW=
print the predictive Chow test	MODEL	PCHOW=
suppress printed output	MODEL	NOPRINT
print partial autocorrelations	MODEL	PARTIAL
print Ramsey's RESET test	MODEL	RESET
print tests for stationarity or unit roots	MODEL	STATIONARITY=(PHILLIPS=)
print tests of linear hypotheses	TEST
specify the test statistics to use	TEST	TYPE=
prints the uncentered regression R²	MODEL	URSQ

Model Estimation Options
specify the order of autoregressive process	MODEL	NLAG=
center the dependent variable	MODEL	CENTER
suppress the intercept parameter	MODEL	NOINT
remove nonsignificant AR parameters	MODEL	BACKSTEP
specify significance level for BACKSTEP	MODEL	SLSTAY=
specify the convergence criterion	MODEL	CONVERGE=
specify the type of covariance matrix	MODEL	COVEST=
set the initial values of parameters used by the iterative optimization algorithm	MODEL	INITIAL=
specify iterative Yule-Walker method	MODEL	ITER
specify maximum number of iterations	MODEL	MAXITER=
specify the estimation method	MODEL	METHOD=
use only first sequence of nonmissing data	MODEL	NOMISS
specify the optimization technique	MODEL	OPTMETHOD=
imposes restrictions on the regression estimates	RESTRICT
estimate and test heteroscedasticity models	HETERO

GARCH Related Options
specify order of GARCH process	MODEL	GARCH=(Q=,P=)
specify type of GARCH model	MODEL	GARCH=(...,TYPE=)
specify various forms of the GARCH-M model	MODEL	GARCH=(...,MEAN=)
suppress GARCH intercept parameter	MODEL	GARCH=(...,NOINT)
specify the trust region method	MODEL	GARCH=(...,TR)
estimate the GARCH model for the conditional t-distribution	MODEL	GARCH=(...) DIST=
estimates the start-up values for the conditional variance equation	MODEL	GARCH=(...,STARTUP=)
specify the functional form of the heteroscedasticity model	HETERO	LINK=
specify that the heteroscedasticity model does not include the unit term	HETERO	NOCONST
impose constraints on the estimated parameters the heteroscedasticity model	HETERO	COEF=
impose constraints on the estimated standard deviation of the heteroscedasticity model	HETERO	STD=
output conditional error variance	OUTPUT	CEV=
output conditional prediction error variance	OUTPUT	CPEV=
specify the flexible conditional variance form of the GARCH model	HETERO


Output Control Options
specify confidence limit size	OUTPUT	ALPHACLI=
specify confidence limit size for structural predicted values	OUTPUT	ALPHACLM=
specify the significance level for the upper and lower bounds of the CUSUM and CUSUMSQ statistics	OUTPUT	ALPHACSM=
specify the name of a variable to contain the values of the Theil's BLUS residuals	OUTPUT	BLUS=
output the value of the error variance ${ {\sigma}^2_{t}}$	OUTPUT	CEV=
output transformed intercept variable	OUTPUT	CONSTANT=
specify the name of a variable to contain the CUSUM statistics	OUTPUT	CUSUM=
specify the name of a variable to contain the CUSUMSQ statistics	OUTPUT	CUSUMSQ=
specify the name of a variable to contain the upper confidence bound for the CUSUM statistic	OUTPUT	CUSUMUB=
specify the name of a variable to contain the lower confidence bound for the CUSUM statistic	OUTPUT	CUSUMLB=
specify the name of a variable to contain the upper confidence bound for the CUSUMSQ statistic	OUTPUT	CUSUMSQUB=
option specify the name of a variable to contain the lower confidence bound for the CUSUMSQ statistic	OUTPUT	CUSUMSQLB=
output lower confidence limit	OUTPUT	LCL=
output lower confidence limit for structural predicted values	OUTPUT	LCLM=
output predicted values	OUTPUT	P=
output predicted values of structural part	OUTPUT	PM=
output residuals	OUTPUT	R=
output residuals from structural predictions	OUTPUT	RM=
specify the name of a variable to contain the part of the predictive error variance (v_t)	OUTPUT	RECPEV=
specify the name of a variable to contain recursive residuals	OUTPUT	RECRES=
output transformed variables	OUTPUT	comp TRANSFORM=
output upper confidence limit	OUTPUT	UCL=
output upper confidence limit for structural predicted values	OUTPUT	UCLM=