coint_ghansen
==============================================

Purpose
----------------

Computes the tests for the null of no cointegration against the alternative of cointegration with a structural break in the mean.

Format
----------------
.. function:: { ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model[, bwl, ic, pmax, varm, trimm])
    :noindexentry:

    :param y: Dependent variable.
    :type y: Nx1 matrix

    :param x: Independent variable.
    :type x: NxK matrix

    :param model: Model to be implemented.

        =========== ==============
        1           Level shift (C)
        2           Level shift with trend (C/T)
        3           Regime shift (C/S)
        4           Regime and trend shift
        =========== ==============

    :type model: Scalar

    :param bwl: Optional, bandwidth length for long-run variance computation. Default = round(4 * (T/100)^(2/9)).
    :type bwl:  Scalar

    :param ic: Optional, the information criterion used for choosing lags. Default = 3.

        =========== ======================
        1           Akaike.
        2           Schwarz.
        3           t-stat significance
        =========== ======================

    :type ic: Scalar

    :param pmax: Optional, maximum number of lags for :math:`\Delta y` in ADF test. Default = 8.
    :type pmax: Scalar

    :param varm: Optional, long-run consistent variance estimation method. Default = 1.

        =========== ======================================================
        1           iid.
        2           Bartlett.
        3           Quadratic Spectral (QS).
        4           SPC with Bartlett (Sul, Phillips & Choi, 2005)
        5           SPC with QS
        6           Kurozumi with Bartlett
        7           Kurozumi with QS
        =========== ======================================================

    :type varm: Scalar

    :param trimm: Optional, trimming rate. Default = 0.10.
    :type trimm: Scalar

    :return ADFmin: ADF test statistic
    :rtype ADFmin: Scalar

    :return TBadf: Break point using OLS.
    :rtype TBadf: Scalar

    :return Zamin: Za test statistic
    :rtype Zamin: Scalar

    :return TBza: Break point for using Za statistic.
    :rtype TBza: Scalar

    :return Ztmin: Zt test statistic
    :rtype Ztmin: Scalar

    :return TB_zt: Break point using Zt statistic.
    :rtype TB_zt: Scalar

    :return cvADFZt: 1%, 5%, 10% critical values for ADF and Zt test statistics.
    :rtype cvADFZt: Scalar

    :return cvZa:  1%, 5%, 10% critical values for Za test statistics.
    :rtype cvZa: Scalar


Examples
--------

::

  new;
  cls;
  library tspdlib;

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

  // Define y and x matrix
  y = data[., 1];
  x = data[., 2:cols(data)];

  // Level shift
  model = 1;

  // Call test
  { ADF_min, TBadf, Zt_min, TBzt, Za_min, TBza, cvADFZt, cvZa } = coint_ghansen(y, x, model);


Source
------

coint_ghansen.src

.. seealso:: Functions :func:`coint_cissanso`, :func:`coint_egranger`, :func:`coint_hatemij`, :func:`coint_maki`