sbur_gls#

Purpose#

Computes the unit root stratistics with structural breaks in a GLS-detrended framework.

Format#

sbOut = sbur_gls(y, model[, sburCtl])#
Parameters:

  • y (Tx1 vector) – Time series with the variable to be analysed.

  • model (Scalar) – Model to be implemented.

  • nbreak (Scalar) – Optional, number of breaks to consider (up to 5). Default = 5.

  • sburCtl –

    Optional, an instance of the sburControl structure, containing the following members:

    sburCtl.knownBreaks

    scalar, specifies if breaks are known or unknown. 0 for known breaks, 1 for unknown breaks. Default = 1.

    sburCtl.breakDate

    vector, holds an known breaks dates. Default = none specified.

    sburCtl.numberBreaks

    scalar, when the structural breaks are unknown, this scalar indicates the number of structural breaks that is assumed. Note that, at the moment, the procedure is designed for up to m <= 5 structural breaks.

    sburCtl.penalty

    scalar, indicates the penalty function that defines the information criteria that is used to determine the number of lags used to estimate the long-run variance. penalty = 0 for maic, and penalty = 1 for bic. Default = 0.

    sburCtl.kmax

    scalar, denotes the maximum number of lags that is used to estimate the long-run variance. Default = 4.

    sburCtl.kmin

    scalar, denotes the minimum number of lags that is used to estimate the long-run variance. Default = 0.

    sburCtl.estimation

    scalar, specifying the estimation method. 0 indicates brute force estimation, 1, uses the dynamic algorithm. Default = 0;

    sburCtl.prewhit

    scalar, Set to 1 if want to apply AR(1) prewhitening prior to estimating the long run covariance matrix. Default = 0.

    sburCtl.maxIters

    scalar, if dynamic algorithm is used, this indicates the maximum number of iterations. Default = 100;

Returns:

sbOut –

An instance of the sburOut structure, containing the following members:

sbOut.pt

scalar, the value for the Pt unit root test.

sbOut.mpt

scalar, the value for the MPT unit root test.

sbOut.adf

scalar, the value for the ADF unit root test.

sbOut.za

scalar, the value for the ZA unit root test.

sbOut.mza

scalar, the value for the MZA unit root test.

sbOut.msb

scalar, the value for the MSB unit root test.

sbOut.mzt

scalar, the value for the MZT unit root test.

sbOut.min_tb

Vector, the estimated break points.

sbOut.cbar

scalar, the value of the c_bar parameter that is used in the quasi GLS-detrending.
rtype sbOut:

struct

Examples#

library tspdlib;

// Load data
data = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_examples.csv", "Y + date($Date, '%b-%y')");

/*
** This section sets parameters
** for testing.
*/
// Set up control structure
struct sburControl sburCtl;
sburCtl = sburControlCreate();

// Number of breaks
sburCtl.numberBreaks = 2;

// Model to use
model = 3;

/*
** Estimation method
** when = 1 we use the algorithm,
** and = 0 brut force
*/
sburCtl.estimation = 1;
sburCtl.maxIters = 20;

// Output structure
struct sburOut sbOut;
sbOut = sbur_gls(data[., "Y"], model, sburCtl);

Source#

sbur.src

See also

Functions dfgls(), kpss_1break(), kpss_2breaks(), kpss_1break(), adf_1break(), adf_2breaks()

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