cips ============================================== Purpose ---------------- Computes a panel data unit root test in the presence of cross-section dependence. Format ---------------- .. function:: { Ncadf, Nmcadf, Nlags, pcadf, pmcadf } = CIPS(y, model[, pmax, ic]) :noindexentry: :param y: Wide panel data set to be tested. :type y: TxN matrix :param model: Model to be implemented. =========== ====================== 0 None. 1 Constant. 2 Constant and trend. =========== ====================== :type model: Scalar :param pmax: Optional, the maximum number of lags for :math:`\Delta y`. Default = 8. :type pmax: Scalar :param ic: Optional, the information criterion used for choosing lags. Default = 3. =========== ============== 1 Akaike. 2 Schwarz. 3 t-stat significance. =========== ============== :type ic: Scalar :return Ncadf: CADF statistics for each cross-section. :rtype Ncadf: Nx1 Vector :return Nmcadf: Modified CADF statistics for each cross-section. :rtype Nmcadf: Nx1 Vector :return Nlags: Number of lags selected by specified information criterion for each cross-section. :rtype Nlags: Nx1 Vector :return pcadf: Panel CIPS statistic :rtype pcadf: Scalar :return pmcadf: Modified panel CIPS statistic :rtype pmcadf: Scalar Examples -------- :: library tspdlib; // CADF and Modified CADF tests /* ** Using the defaults ** for maximum number of lags ** and information criterions, */ // Set up model model = 1; { Ncadf, Nlm, Nmcadf, Nlags, pcadf, pmcadf } = cips(y, model); Source ------ pd_cips.src