ecmFit#

Purpose#

Calculate and return parameter estimates for an error correction model.

Format#

vmo = ecmFit(y, p[, vmc])#
vmo = ecmFit(dataset, formula, p[, vmc])
Parameters:

  • y (Nx1 vector) – data.

  • dataset (string) – name of data set or null string.

  • formula (string) – formula string of the model. E.g. “y ~ X1 + X2” ‘y’ is the name of dependent variable, ‘X1’ and ‘X2’ are names of independent variables; E.g. “y ~ .” , ‘.’ means including all variables except dependent variable ‘y’;

  • p (scalar) – order of AR process.

  • vmc (struct) –

    Optional input, an instance of a varmamtControl structure. The following members of vmc are referenced within this routine:

    vmc.rho

    scalar, number of cointegrating relations. Set to -1 to have GAUSS estimate this value. Default = 0.

    vmc.indEquations

    KxL matrix of zeros and ones. Used to set zero restrictions on the x variables to be estimated. Used only if the number of equations, vmc.L, is greater than one. Elements set to one indicate the coefficients to be estimated. If vmc.L = 1, all coefficients will be estimated. If vmc.L > 1 and vmc.indEquations is set to a missing value (the default), all coefficients will be estimated.

    vmc.lags

    scalar, number of lags over which ACF and Diagnostics are calculated. Default = 12.

    vmc.start

    Instance of a PV structure containing starting values. See VES-Starting Values for an example.

    vmc.nodet

    scalar. Set vmc.nodet = 1 to suppress the constant term from the fitted regression and include it in the co-integrating regression; otherwise, set vmc.nodet = 0. Default = 0.

    vmc.nwtrunc

    scalar, the number of autocorrelations to use in calculating the Newey-West correction. If vmc.nwtrunc = 0, GAUSS will use a truncation lag given by Newey and West, vmc.nwtrunc \(= 4(T/100)^{2/9}\).

    vmc.ctl

    An instance of an sqpsolvemtControl structure.

    vmc.ctl.covType

    scalar, if 2, QML standard errors are computed, if 0, none; otherwise Wald-type.

    vmc.ctl.printIters

    scalar, iteration information printed every vmc.ctl.printIters-th iteration.

    See documentation for sqpsolvemtControl for further information regarding members of this structure.

    vmc.olsqtol

    scalar, the tolerance used in determining if diagonal elements are approaching zero in olsqrmt. Default = 1e-14.

    vmc.output

    scalar, if nonzero, results are printed to screen. Default = 1.

    vmc.row

    scalar. Specifies how many rows of the dataset are to be read per iteration of the read loop. By default, the number of rows to be read is calculated by ecmFit.

    vmc.scale

    scalar or an Lx1 vector, scales for the time series. If scalar, all series are multiplied by the value. If an Lx1 vector, each series is multiplied by the corresponding element of vmc.scale. Default = 4/standard deviation (found to be best by experimentation).

    vmc.setConstraints

    scalar, set to a nonzero value to impose stationarity and invertibility by constraining roots of the AR and MA characteristic equations to be outside the unit circle. Set to zero to estimate an unconstrained model. Default = 1.

Returns:

vmo (struct) – An instance of a varmamtOut structure containing the following members:

Example#

new;
cls;
library tsmt;

// Load data
fname = getGAUSSHome("pkgs/tsmt/examples/ecmmt.csv");
y = csvReadM(fname, 1, 2);

y = vmdiffmt(y, 1);

// Declare varmamt control structure
struct varmamtControl vmc;

// Initialize control structure with default values
vmc = varmamtControlCreate;

// No contraints
vmc.setConstraints = 0;

// Set up start values
phi = { 0.05 -0.05, 0 0.01, 0.1 -0.07, 0.05 -0.04 };
vmc.start = pvcreate();
vmc.start = pvPacki(vmc.start,areshape(phi, 2|2|2), "phi", 1);
vmc.start = pvPacksi(vmc.start, xpnd(15.9521|14.2525|15.9908), "vc", 3);

// Call ecmFit
struct varmamtOut vout;
vout = ecmFit(y , 1, vmc);

Remarks#

Errors are assumed to be distributed \(N(0, Q)\).

Library#

tsmt

Source#

varmamt.src

See also

Functions varmaFit()

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