The PANEL Procedure

MODEL Statement

  • MODEL <"string"> response = regressors </ options>;

The MODEL statement specifies the regression model, the error structure that is assumed for the regression residuals, and the estimation technique to be used. The response variable (response) on the left side of the equal sign is regressed on the independent variables (regressors), which are listed after the equal sign. You can specify any number of MODEL statements. For each MODEL statement, you can specify only one response.

You can label models. Model labels are used in the printed output to identify the results for different models. If you do not specify a label, the model is referred to by numerical order wherever necessary. You can label the models in two ways:

First, you can prefix the MODEL statement by a label followed by a colon. For example:

label: MODEL …;

Second, you can add a quoted string after the MODEL keyword. For example:

MODEL "label" …;

Quoted-string labels are preferable because they allow spaces and special characters and because these labels are case-sensitive. If you specify both types of label, PROC PANEL uses the quoted string.

The MODEL statement supports a multitude of options, some more specific than others. Table 27.1 summarizes the options available in the MODEL statement. These are subsequently discussed in detail in the order in which they are presented in the table.

Table 27.1: Summary of MODEL Statement Options

Option

Description

Estimation Technique Options

AMACURDY

fits a one-way model by using the Amemiya-MaCurdy estimator

BTWNG

fits the between-groups model

BTWNT

fits the between-time-periods model

DASILVA

fits a moving average model by using the Da Silva method

FDONE

fits a one-way model by using first differences

FDONETIME

fits a one-way model for time effects by using first differences

FDTWO

fits a two-way model by using first differences

FIXONE

fits a one-way fixed-effects model

FIXONETIME

fits a one-way fixed-effects model for time effects

FIXTWO

fits a two-way fixed effects model

GMM1

fits a dynamic-panel model by using the one-step generalized method of moments (GMM)

GMM2

fits a dynamic-panel model by using two-step GMM

HTAYLOR

fits a one-way model by using the Hausman-Taylor estimator

ITGMM

fits a dynamic-panel model by using iterated GMM

PARKS

fits an autoregressive model by using the Parks method

POOLED

fits the pooled regression model

RANONE

fits a one-way random-effects model

RANTWO

fits a two-way random-effects model

Estimation Control Options

M=

specifies the moving average order

NOESTIM

limits estimation to only transforming the data

NOINT

suppresses the intercept

SINGULAR=

specifies a matrix inverse singularity criterion

VCOMP=

specifies the type of variance component estimation for random-effects estimation

Dynamic Panel Estimation Control Options

ARTEST=

specifies the maximum order of the auto regression (AR) test

ATOL=

specifies the convergence criterion of iterated GMM, with respect to the weighting matrix

BANDOPT=

specifies which neighboring observations to use as instruments, whether TRAILING, CENTERED, or LEADING

BIASCORRECTED

requests bias-corrected variances for two-step GMM

BTOL=

specifies the convergence criterion of iterated GMM, with respect to the parameter matrix

GINV=

specifies the type of generalized matrix inverse

MAXBAND=

specifies the moment condition bandwidth

MAXITER=

specifies the maximum iterations for iterative GMM

NODIFFS

estimates without moment conditions from the difference equations

NOLEVELS

estimates without moment conditions from the level equations

ROBUST

specifies the robust covariance matrix

TIME

includes time dummy variables in the model

Alternative Variances Options

CLUSTER

corrects covariance for intracluster correlation

HAC(options)

specifies a heteroscedasticity- and autocorrelation-consistent (HAC) covariance

HCCME=

specifies a heteroscedasticity-corrected covariance matrix estimator (HCCME)

NEWEYWEST(options)

specifies the Newey-West covariance, a special case of the HAC covariance

Unit Root Test Options

UROOTTEST(test-options)

requests one or more panel data unit root and stationarity tests; specify test-options ALL through LLC within this option

STATIONARITY(test-options)

synonym for UROOTTEST

ALL

requests that all unit root tests be performed

BREITUNG(options)

specifies Breitung’s tests that are robust to cross-sectional dependence

COMBINATION(options)

specifies one or more unit root tests that combine over all cross sections

FISHER(options)

synonym for COMBINATION

HADRI(options)

specifies Hadri’s (2000) stationarity test

HT

specifies the Harris and Tzavalis (1999) panel unit root test

IPS(options)

specifies the Im, Pesaran, and Shin (2003) panel unit root test

LLC(options)

specifies the Levin, Lin, and Chu (2002) panel unit root test

Model Specification Test Options

BFN

requests the $R_\rho $ statistic for serial correlation under fixed effects

BL91

requests the Baltagi and Li (1991) Lagrange multiplier (LM) test for serial correlation and random effects

BL95

requests the Baltagi and Li (1995) LM test for first-order correlation under fixed effects

BP

requests the Breusch-Pagan one-way test for random effects

BP2

requests the Breusch-Pagan two-way test for random effects

BSY

requests the Bera, Sosa Escudero, and Yoon modified Rao’s score test

BW

requests the Berenblut-Webb statistic for serial correlation under fixed effects

CDTEST(options)

requests a battery of cross-sectional dependence tests.

DW

requests the Durbin-Watson statistic for serial correlation under fixed effects

GHM

requests the Gourieroux, Holly, and Monfort test for two-way random effects

HONDA

requests the Honda one-way test for random effects

HONDA2

requests the Honda two-way test for random effects

KW

requests the King and Wu two-way test for random effects

POOLTEST

requests poolability tests for one-way fixed effects and pooled models

WOOLDRIDGE02

requests the Wooldridge (2002) test for unobserved effects.

Printed Output Options

CORR

prints the parameter correlation matrix

CORRB

synonym for CORR

COVB

prints the parameter covariance matrix

ITPRINT

prints the iteration history

NOPRINT

suppress normally printed output

PHI

prints the $\Phi $ covariance matrix for the Parks method

PRINTFIXED

estimates and prints the fixed effects

RHO

prints the autocorrelation coefficients for the Parks method

VAR

synonym for COVB


You can specify the following options in the MODEL statement after a slash (/).

Estimation Technique Options

These options specify the assumed error structure and estimation method. You can specify more than one option, in which case the analysis is repeated for each. The default is RANTWO (two-way random effects).

All estimation methods are detailed in the section Details: PANEL Procedure and its subsections.

AMACURDY

requests Amemiya-MaCurdy estimation for a model that has correlated individual (cross-sectional) effects. This option requires that you specify the CORRELATED= option in the INSTRUMENTS statement.

BTWNG

estimates a between-groups model.

BTWNT

estimates a between-time-periods model.

DASILVA

estimates the model by using the Da Silva method, which assumes a mixed variance-component moving average model for the error structure.

FDONE

estimates a one-way model by using first-differenced methods.

FDONETIME

estimates a one-way model that corresponds to time effects by using first-differenced methods.

FDTWO

estimates a two-way model by using first-differenced methods.

FIXONE

estimates a one-way fixed-effects model that corresponds to cross-sectional effects only.

FIXONETIME

estimates a one-way fixed-effects model that corresponds to time effects only.

FIXTWO

estimates a two-way fixed-effects model.

GMM1

estimates the model in a single step by using the dynamic panel estimator method, which allows for autoregressive processes. This option requires you to specify the INSTRUMENTS statement.

GMM2

estimates the model in two steps by using the dynamic panel estimator method. The first step forms an estimator for the weighting matrix that is used in the second step. This option requires you to specify the INSTRUMENTS statement.

HTAYLOR

requests Hausman-Taylor estimation for a model that has correlated individual (cross-sectional) effects. This option requires you to specify the CORRELATED= option in the INSTRUMENTS statement.

ITGMM

estimates the model by using the dynamic panel estimator method, but requests that PROC PANEL keep updating the weighting matrix until either the parameter vector converges or the weighting matrix converges. This option requires you to specify the INSTRUMENTS statement.

PARKS

estimates the model by using the Parks method, which assumes a first-order autoregressive model for the error structure.

POOLED

estimates a pooled (OLS) model.

RANONE

estimates a one-way random-effects model.

RANTWO

estimates a two-way random-effects model.

Estimation Control Options

These options define parameters that control the estimation and can be specific to the chosen technique (for example, how to estimate variance components in a random-effects model).

M=number

specifies the order of the moving average process in the Da Silva method. The value of number must be less than T-1, where T is the number of time periods. By default, M=1.

NOESTIM

limits the estimation of a FIXONE, FIXONETIME, or RANONE model to the generation of the transformed series. This option is intended for use with an OUTTRANS= data set.

NOINT

suppresses the intercept parameter from the model.

SINGULAR=number

specifies a singularity criterion for the inversion of the matrix. The default depends on the precision of the computer system.

VCOMP=FB | NL | WH | WK

specifies the type of variance component estimate to use. You can specify the following values:

FB

uses the Fuller and Battese method.

NL

uses the Nerlove method.

WH

uses the Wallace and Hussain method.

WK

uses the Wansbeek and Kapteyn method.

By default, VCOMP=FB for balanced data and VCOMP=WK for unbalanced data. For more information, see the sections One-Way Random-Effects Model and Two-Way Random-Effects Model.

Dynamic Panel Estimation Control Options

These control options are specific to dynamic panels, where the estimation technique is specified as GMM1, GMM2, or ITGMM. For more information, see the section Dynamic Panel Estimators.

ARTEST=integer

specifies the maximum order of the test for the presence of auto regression (AR) effects in the residual in the dynamic panel model. The value of integer must be between 1 and the T-3 inclusive, where T is the number of time periods.

ATOL=number

specifies the convergence criterion for the iterated generalized method of moments (GMM) when convergence of the method is determined by convergence in the weighting matrix. The convergence criterion (number) must be positive. If you do not specify this option, then the BTOL= option (or its default) is used.

BANDOPT=CENTERED | LEADING | TRAILING

specifies which observations are included in the instrument list when the MAXBAND= option is specified. You can specify the following values:

CENTERED

uses both leading and trailing observations.

LEADING

uses only leading observations.

TRAILING

uses only trailing observations.

This option should be used only for exogenous instruments. By default, BANDOPT=TRAILING.

BIASCORRECTED

requests that the bias-corrected covariance matrix of the two-step dynamic panel estimator be computed. When you specify this option, the ROBUST option is disabled for the two-step GMM estimator.

BTOL=number

specifies the convergence criterion for iterated GMM when convergence of the method is determined by convergence in the parameter matrix. The convergence criterion (number) must be positive. The default is BTOL=1E–8.

GINV= G2 | G4

specifies what type of generalized inverse to use. You can specify the following values:

G2

uses the G2 generalized inverse.

G4

uses the G4 generalized inverse.

The G4 inverse is generally more stable, but numerically intensive. By default, GINV=G2.

MAXBAND=integer

specifies the maximum number of time periods (per instrumental variable) that are allowed into the moment condition. The acceptable range for integer is 1 to $T-1$, where T is the number of time periods. If BANDOPT=LEADING or CENTERED, then the default value of MAXBAND is 2. If BANDOPT=TRAILING, then the default value of MAXBAND is 1. If no BANDOPT option is specified (such as when no exogenous instruments are used), then the default value of MAXBAND is 1.

MAXITER=integer

specifies the maximum number of iterations for the ITGMM option. By default, MAXITER=200.

NODIFFS

estimates the dynamic panel model without moment conditions from the difference equations.

NOLEVELS

estimates the dynamic panel model without moment conditions from the level equations.

ROBUST

uses the robust weighting matrix in the calculation of the covariance matrix of the single-step, two-step, and iterated GMM dynamic panel estimators.

TIME

estimates the model by using the dynamic panel estimator method but includes time dummy variables to model any time effects in the data.

Alternative Variances Options

These options specify variance estimation other than conventional model-based variance estimation. They include the robust, cluster robust, HAC, HCCME, and Newey-West techniques.

CLUSTER

specifies the cluster correction for the covariance matrix. You can specify this option when you specify HCCME=0, 1, 2, or 3.

HAC <(options) >

specifies the heteroscedasticity- and autocorrelation-consistent (HAC) covariance matrix estimator. This option is not available for between models and cannot be combined with the HCCME option.

For more information, see the section Heteroscedasticity- and Autocorrelation-Consistent Covariance Matrices.

You can specify the following options within parentheses and separated by spaces:

BANDWIDTH=number | method

specifies the fixed bandwidth value or bandwidth selection method to be used in the kernel function. You can specify either a fixed value (number) or one of the methods shown after number.

number

specifies a fixed value of the bandwidth parameter.

ANDREWS91 | ANDREWS

specifies the Andrews (1991) bandwidth selection method.

NEWEYWEST94<(C=number)>
NW94 <(C=number)>

specifies the Newey and West (1994) bandwidth selection method. You can also specify C=number for the calculation of lag selection parameter; the default is C=12.

SAMPLESIZE<(options)>
SS<(options)>

calculates the bandwidth according to the following equation based on the sample size

\[ b=\gamma T^{r} + c \]

where b is the bandwidth parameter; T is the sample size; and $\gamma $, r, and c are values specified by the following options within parentheses and separated by commas.

GAMMA=number

specifies the coefficient $\gamma $ in the equation. By default, GAMMA=0.75.

RATE=number

specifies the growth rate r in the equation. By default, RATE=0.3333.

CONSTANT=number

specifies the constant c in the equation. By default, CONSTANT=0.5.

INT

specifies that the bandwidth parameter must be integer; that is, $b=\left\lfloor {\gamma T^{r} + c}\right\rfloor $, where $\left\lfloor {x}\right\rfloor $ denotes the largest integer less than or equal to x.

By default, BANDWIDTH=ANDREWS91.

KERNEL=BARTLETT | PARZEN | QS | TH | TRUNCATED

specifies the type of kernel function. You can specify the following values:

BARTLETT

specifies the Bartlett kernel function.

PARZEN

specifies the Parzen kernel function.

QS

specifies the quadratic spectral kernel function.

TH

specifies the Tukey-Hanning kernel function.

TRUNCATED

specifies the truncated kernel function.

By default, KERNEL=TRUNCATED.

KERNELLB=number

specifies the lower bound of the kernel weight value. Any kernel weight less than number is regarded as 0, which accelerates the calculation in large samples, especially for the quadratic spectral kernel function. By default, KERNELLB=0.

PREWHITENING

requires prewhitening in the covariance calculation.

ADJUSTDF

requires adjustment of degrees of freedom in the covariance calculation.

HCCME= NO | number

specifies the type of HCCME covariance matrix. You can specify one of the following:

NO

does not correct the covariance matrix.

number

specifies the type of covariance adjustment. The value of number can be any integer from 0 to 4, inclusive.

For more information, see the section Heteroscedasticity-Corrected Covariance Matrices. By default, HCCME=NO.

NEWEYWEST<(options)>

specifies the well-known Newey-West estimator, a special HAC estimator that uses (1) the Bartlett kernel, (2) a bandwidth that is determined by the equation based on the sample size, $b=\left\lfloor {\gamma T^{r} + c}\right\rfloor $, and (3) no adjustment for degrees of freedom and no prewhitening. By default, the bandwidth parameter for Newey-West estimator is $\left\lfloor {0.75T^{0.3333}+0.5}\right\rfloor $, as shown in equation (15.17) in Stock and Watson (2002). You can specify the following options in parentheses and separated by commas:

GAMMA= number

specifies the coefficient $\gamma $ in the equation. By default, GAMMA=0.75.

RATE= number

specifies the growth rate r in the equation. By default, RATE=0.3333.

CONSTANT= number

specifies the constant c in the equation. By default, CONSTANT=0.5.

To specify a Newey-West bandwidth directly (and not as a function of time-series length), set GAMMA=0 and CONSTANT=b, where b is the bandwidth you want. For example, the two variance specifications in the following statements are equivalent:

   proc panel data=A;
      id i t;
      model y = x1 x2 x3 / ranone hac(kernel = bartlett bandwidth = 3);
      model y = x1 x2 x3 / ranone neweywest(gamma = 0, constant = 3);
   run;

Unit Root Test Options

These options request unit root tests on the dependent variable. You begin with the UROOTTEST (or its synonym STATIONARITY) option and specify everything else within parentheses after the UROOTTEST (or SINGULARITY) keyword. The BREITUNG, COMBINATION, HADRI, HT, IPS, and LLC tests are available, and you can request them all by specifying the ALL option.

UROOTTEST(test1<(test-options), test2<(test-options)>…> <options>)
STATIONARITY(test1<(test-options), test2<(test-options)>…> <options>)

specifies tests of stationarity or unit root for panel data, and specifies options for each test. These tests apply only to the dependent variable. Six tests are available: BREITUNG, COMBINATION (or FISHER), HADRI, HT, IPS, and LLC. You can specify one or more of these tests, separated by commas. You can also request all tests by specifying UROOTEST(ALL) or STATIONARITY(ALL). If you specify one or more test-options (separated by spaces) inside the parentheses after a particular test, they apply only to that test. If you specify one or more options separated by spaces after you specify the tests, they apply to all the tests. If you specify both test-options and options, the test-options override the options.

You can specify the following tests and test-options:

BREITUNG<(test-options) >

performs Breitung’s unbiased test, t test, and generalized least squares (GLS) t test that are robust to cross-sectional dependence. The tests are described in Breitung and Meyer (1994); Breitung (2000); Breitung and Das (2005). You can specify one or more of the following test-options within parentheses and separated by spaces:

DETAIL

requests that intermediate results (lag order) be printed.

LAG=type | value

specifies the method to choose the lag order for the augmented Dickey-Fuller (ADF) regressions. You can specify a value or one of the types that are shown after value.

value

specifies the lag order. If the lag order is too big to run linear regression (value > $T-k$, where T is the number of time periods and k is the number of parameters), then the lag order is set to $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller.

GS

selects the order of lags by Hall’s (1994) sequential testing method, from the most general model (maximum lags) to lower order of lag terms.

SG

selects the order of lags by Hall’s (1994) sequential testing method, from no lag term to maximum allowed lags.

AIC

selects the order of lags by Akaike’s information criterion (AIC).

SBC
SIC
SBIC

selects the order of lags by the Bayesian information criterion (Schwarz criterion).

HQIC

selects the order of lags by the Hannan-Quinn information criterion.

MAIC

selects the order of lags by the modified AIC that is proposed by Ng and Perron (2001).

By default, LAG=MAIC.

MAXLAG=value

specifies the maximum lag order that the model allows. The default value is $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $. If value is larger than 0 and larger than $T-k$, then the maximum lag order is set to be the default value of $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller. This option is ignored if you specify LAG=value.

COMBINATION < (test-options) >
FISHER < (test-options) >

specifies combination tests that are proposed by Choi (2001); Maddala and Wu (1999). Fisher’s test, as proposed by Maddala and Wu (1999), is a special case of combination tests. You can specify one or more of the following test-options within parentheses and separated by spaces:

TEST=ADF | PP

selects the time series unit root test for combination tests (Fisher’s test). You can specify the following values:

ADF

specifies the augmented Dickey-Fuller (ADF) test. The BANDWIDTH and KERNEL options are ignored because they do not pertain to ADF tests.

PP

specifies the Phillips and Perron (1988) unit root test. The LAG and MAXLAG options are ignored because they do not pertain to PP tests.

By default, TEST=PP.

KERNEL=BARTLETT | PARZEN | QS | TH | TRUNCATED

specifies the type of kernel function. You can specify the following values:

BARTLETT

specifies the Bartlett kernel function.

PARZEN

specifies the Parzen kernel function.

QS

specifies the quadratic spectral kernel function.

TH

specifies the Tukey-Hanning kernel function.

TRUNCATED

specifies the truncated kernel function.

By default, KERNEL=QS.

BANDWIDTH=ANDREWS | number

specifies the bandwidth for the kernel. You can specify one of the following:

ANDREWS

selects the bandwidth by the Andrews method.

number

sets the bandwidth to number, which must be nonnegative.

By default, BANDWIDTH=ANDREWS.

DETAIL

requests that intermediate results (lag order and long-run variance for each cross section) be printed.

LAG=type | value

specifies the method to choose the lag order for the augmented Dickey-Fuller (ADF) regressions. You can specify a value or one of the types that are shown after value.

value

specifies the lag order. If the lag order is too big to run linear regression (value > $T-k$, where T is the number of time periods and k is the number of parameters), then the lag order is set to $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller.

GS

selects the order of lags by Hall’s (1994) sequential testing method, from the most general model (maximum lags) to lower order of lag terms.

SG

selects the order of lags by Hall’s (1994) sequential testing method, from no lag term to maximum allowed lags.

AIC

selects the order of lags by Akaike’s information criterion (AIC).

SBC
SIC
SBIC

selects the order of lags by the Bayesian information criterion (Schwarz criterion).

HQIC

selects the order of lags by the Hannan-Quinn information criterion.

MAIC

selects the order of lags by the modified AIC that is proposed by Ng and Perron (2001).

By default, LAG=MAIC.

MAXLAG=value

specifies the maximum lag order that the model allows. The default value is $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $. If value is larger than 0 and larger than $T-k$, then the maximum lag order is set to be the default value of $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller. This option is ignored if you specify LAG=value.

HADRI < (test-options) >

specifies Hadri’s (2000) panel stationarity test. You can specify the following test-options:

DETAIL

requests that intermediate results (lag order and long-run variance for each cross section) be printed.

KERNEL=BARTLETT | PARZEN | QS | TH | TRUNCATED

specifies the type of kernel function. You can specify the following values:

BARTLETT

specifies the Bartlett kernel function.

PARZEN

specifies the Parzen kernel function.

QS

specifies the quadratic spectral kernel function.

TH

specifies the Tukey-Hanning kernel function.

TRUNCATED

specifies the truncated kernel function.

By default, KERNEL=QS.

BANDWIDTH=ANDREWS | number

specifies the bandwidth for the kernel. You can specify one of the following:

ANDREWS

selects the bandwidth by the Andrews method.

number

sets the bandwidth to number, which must be nonnegative.

By default, BANDWIDTH=ANDREWS.

HT

specifies the Harris and Tzavalis (1999) panel unit root test. No options are available for this test.

IPS < (test-options) >

specifies the Im, Pesaran, and Shin (2003) panel unit root test. You can specify one or more of the following test-options within parentheses and separated by spaces:

DETAIL

requests that intermediate results (lag order) be printed.

LAG=type | value

specifies the method to choose the lag order for the augmented Dickey-Fuller (ADF) regressions. You can specify a value or one of the types that are shown after value.

value

specifies the lag order. If the lag order is too big to run linear regression (value > $T-k$, where T is the number of time periods and k is the number of parameters), then the lag order is set to $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller.

GS

selects the order of lags by Hall’s (1994) sequential testing method, from the most general model (maximum lags) to lower order of lag terms.

SG

selects the order of lags by Hall’s (1994) sequential testing method, from no lag term to maximum allowed lags.

AIC

selects the order of lags by Akaike’s information criterion (AIC).

SBC
SIC
SBIC

selects the order of lags by the Bayesian information criterion (Schwarz criterion).

HQIC

selects the order of lags by the Hannan-Quinn information criterion.

MAIC

selects the order of lags by the modified AIC that is proposed by Ng and Perron (2001).

By default, LAG=MAIC.

MAXLAG=value

specifies the maximum lag order that the model allows. The default value is $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $. If value is larger than 0 and larger than $T-k$, then the maximum lag order is set to be the default value of $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller. This option is ignored if you specify LAG=value.

LLC < (test-options) >

specifies the Levin, Lin, and Chu (2002) panel unit root test. You can specify one or more of the following test-options within parentheses and separated by spaces:

DETAIL

requests that intermediate results (lag order and long-run variance for each cross section) be printed.

KERNEL=BARTLETT | PARZEN | QS | TH | TRUNCATED

specifies the type of kernel function. You can specify the following values:

BARTLETT

specifies the Bartlett kernel function.

PARZEN

specifies the Parzen kernel function.

QS

specifies the quadratic spectral kernel function.

TH

specifies the Tukey-Hanning kernel function.

TRUNCATED

specifies the truncated kernel function.

By default, KERNEL=QS.

BANDWIDTH=ANDREWS | number

specifies the bandwidth for the kernel. You can specify one of the following:

ANDREWS

selects the bandwidth by the Andrews method.

number

sets the bandwidth to number, which must be nonnegative. By default, BANDWIDTH=ANDREWS.

LAG=type | value

specifies the method to choose the lag order for the augmented Dickey-Fuller (ADF) regressions. You can specify a value or one of the types that are shown after value.

value

specifies the lag order. If the lag order is too big to run linear regression (value > $T-k$, where T is the number of time periods and k is the number of parameters), then the lag order is set to $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller.

GS

selects the order of lags by Hall’s (1994) sequential testing method, from the most general model (maximum lags) to lower order of lag terms.

SG

selects the order of lags by Hall’s (1994) sequential testing method, from no lag term to maximum allowed lags.

AIC

selects the order of lags by Akaike’s information criterion (AIC).

SBC
SIC
SBIC

selects the order of lags by the Bayesian information criterion (Schwarz criterion).

HQIC

selects the order of lags by the Hannan-Quinn information criterion.

MAIC

selects the order of lags by the modified AIC that is proposed by Ng and Perron (2001).

By default, LAG=MAIC.

MAXLAG=value

specifies the maximum lag order that the model allows. The default value is $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $. If value is larger than 0 and larger than $T-k$, then the maximum lag order is set to be the default value of $\left\lfloor {12(T/100)^{1/4}}\right\rfloor $ or $T-k-1$, whichever is smaller. This option is ignored if you specify LAG=value.

Consider the following example, which requests two tests (LLC and BREITUNG) on the dependent variable:

   proc panel data=A;
      id i t;
      model y = x1 x2 x3 / unitroot(llc(kernel = parzen lag = aic),
                                    breitung(lag = gs)
                                    maxlag = 2
                                    kernel = bartlett);
   run;

For the LLC test, the lag order is selected by AIC with maximum lag order 2 and the kernel is specified as Parzen (overriding Bartlett). For the BREITUNG test, the lag order is GS with a maximum lag order 2. The KERNEL option is ignored by BREITUNG because it is not relevant to that test.

Model Specification Test Options

These options request model specification tests, such as a test for poolability in one-way models. These tests depend on the model specifications of dependent and independent variables, but not on the estimation technique that is used to fit the model. For example, a one-way test for random effects does not require you to fit a random effects model, or even a one-way model for that matter. The model fits that are required for the selected tests are performed internally.

BFN

requests the R$_{\rho }$ statistic for serial correlation under cross-sectional fixed effects.

BL91

requests the Baltagi and Li (1991) joint Lagrange multiplier (LM) test for serial correlation and random cross-sectional effects.

BL95

requests the Baltagi and Li (1995) LM test for first-order correlation under fixed effects.

BP

requests the Breusch-Pagan one-way test for random effects.

BP2

requests the Breusch-Pagan two-way test for random effects.

BSY

requests the Bera, Sosa Escudero, and Yoon modified Rao’s score test for random cross-sectional effects or serial correlation or both.

BW

requests the Berenblut-Webb statistic for serial correlation under cross-sectional fixed effects.

CDTEST <(P=value) >

requests cross-sectional dependence tests. These include the Breusch and Pagan (1980) LM test, the scaled version of the Breusch and Pagan (1980) test, and the Pesaran (2004) CD test. When you specify P=value, the CD test for local cross-sectional dependence is performed with the order $\Argument{value}$, where $\Argument{value}$ is an integer greater than 0.

DW

requests the Durbin-Watson statistic for serial correlation under cross-sectional fixed effects.

GHM

requests the Gourieroux, Holly, and Monfort two-way test for random effects.

HONDA

requests the Honda one-way test for random effects.

HONDA2

requests the Honda two-way test for random effects.

KW

requests the King and Wu two-way test for random effects.

POOLTEST

requests poolability tests for one-way fixed effects and pooled models.

WOOLDRIDGE02

requests the Wooldridge (2002) test for the presence of unobserved effects.

Printed Output Options

These options alter how results are presented.

CORRB
CORR

prints the matrix of estimated correlations between the parameter estimates.

COVB
VAR

prints the matrix of estimated covariances between the parameter estimates.

ITPRINT

prints out the iteration history of the parameter and transformed sum of squared errors.

NOPRINT

suppresses the normal printed output.

PHI

prints the ${\Phi }$ matrix of estimated covariances of the observations for the Parks method. The PHI option is relevant only when the PARKS option is specified. For more information, see the section Parks Method (Autoregressive Model).

PRINTFIXED

estimates and prints the fixed effects in models where they would normally be absorbed within the estimation.

RHO

prints the estimated autocorrelation coefficients for the Parks method.