The AUTOREG Procedure

Functional Summary

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

Table 8.1: AUTOREG Functional Summary

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
Requests that the procedure produce graphics via the Output Delivery System	AUTOREG	PLOTS=
Write predictions, residuals, and confidence limits to an output data set	OUTPUT	OUT=
Declaring the Role of Variables
Specify BY-group processing	BY
Specify classification variables	CLASS
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	MODEL	DW=
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 the tests for the absence of ARCH effects	MODEL	ARCHTEST=
Print BDS tests for independence	MODEL	BDS=
Print rank version of von Neumann ratio test for independence	MODEL	VNRRANK=
Print runs test for independence	MODEL	RUNS=
Print the turning point test for independence	MODEL	TP=
Print the Lagrange multiplier test	HETERO	TEST=LM
Print Bai-Perron tests for multiple structural changes	MODEL	BP=
Print the Chow test for structural change	MODEL	CHOW=
Print the predictive Chow test for structural change	MODEL	PCHOW=
Suppress printed output	MODEL	NOPRINT
Print partial autocorrelations	MODEL	PARTIAL
Print Ramsey’s RESET test	MODEL	RESET
Print Phillips-Perron tests for stationarity or unit roots	MODEL	STATIONARITY=(PHILLIPS=)
Print Augmented Dickey-Fuller tests for stationarity or unit roots	MODEL	STATIONARITY=(ADF=)
Print ERS tests for stationarity or unit roots	MODEL	STATIONARITY=(ERS=)
Print KPSS tests or Shin tests for stationarity or cointegration	MODEL	STATIONARITY=(KPSS=)
Print Ng-Perron tests for stationarity or unit roots	MODEL	STATIONARITY=(NP=)
Print tests of linear hypotheses	TEST
Specify the test statistics to use	TEST	TYPE=
Print the uncentered regression ${\mi {R} ^{2}}$	MODEL	URSQ
Options to Control the Optimization Process
Specify the optimization options	NLOPTIONS	see Chapter 6: Nonlinear Optimization Methods,
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=( ${\ldots }$ ,TYPE=)
Specify various forms of the GARCH-M model	MODEL	GARCH=( ${\ldots }$ ,MEAN=)
Suppress GARCH intercept parameter	MODEL	GARCH=( ${\ldots }$ ,NOINT)
Specify the trust region method	MODEL	GARCH=( ${\ldots }$ ,TR)
Estimate the GARCH model for the conditional t distribution	MODEL	GARCH=( ${\ldots }$ ) DIST=
Estimate the start-up values for the conditional variance equation	MODEL	GARCH=( ${\ldots }$ ,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 in 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=
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	TRANSFORM=
Output upper confidence limit	OUTPUT	UCL=
Output upper confidence limit for structural predicted values	OUTPUT	UCLM=