The AUTOREG Procedure

Functional Summary

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

Table 9.1: 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 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 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 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 Phillips-Perron tests for stationarity or unit roots

MODEL

STATIONARITY=(PHILLIPS=)

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 7: 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=