show-methods          package:urca          R Documentation(latin1)

_M_e_t_h_o_d_s _f_o_r _F_u_n_c_t_i_o_n _s_h_o_w _i_n _P_a_c_k_a_g_e _u_r_c_a

_D_e_s_c_r_i_p_t_i_o_n:

     Displays the outcome of the unit root/cointegration tests.

_M_e_t_h_o_d_s:



     _o_b_j_e_c_t = "_c_a._j_o" Displays the test statistic of the Johansen
          procedure.

     _o_b_j_e_c_t = "_c_a_j_o._t_e_s_t" Displays the test statistic of a restricted
          VAR with respect to *alpha* and/or *beta*.

     _o_b_j_e_c_t = "_c_a._p_o" Displays the test statistic of the Phillips &
          Ouliaris cointegration test.

     _o_b_j_e_c_t = "_u_r._d_f" Displays the test statistic of the Augmented,
          Dickey and Fuller unit root test.

     _o_b_j_e_c_t = "_u_r._e_r_s" Displays the test statistic of the Elliott,
          Rothenberg & Stock unit root test.

     _o_b_j_e_c_t = "_u_r._k_p_s_s" Displays the test statistic of the Kwiatkowski
          _et al._ unit root test.

     _o_b_j_e_c_t = "_u_r._p_p" Displays the test statistic of the Phillips &
          Perron unit root test.

     _o_b_j_e_c_t = "_u_r._d_f" Displays the test statistic of the augmented
          Dickey-Fuller unit root test.

     _o_b_j_e_c_t = "_u_r._s_p" Displays the test statistic of the Schmidt &
          Phillips unit root test.

     _o_b_j_e_c_t = "_u_r._z_a" Displays the test statistic of the Zivot &
          Andrews unit root test.

     _o_b_j_e_c_t = "_s_u_m_u_r_c_a" Displays the summary output.


_A_u_t_h_o_r(_s):

     Bernhard Pfaff

_S_e_e _A_l_s_o:

     'ca.jo-class', 'cajo.test-class', 'ca.po-class', 'ur.ers-class',
     'ur.kpss-class', 'ur.pp-class', 'ur.sp-class', 'ur.df-class' and
     'ur.za-class'.

_E_x_a_m_p_l_e_s:

     data(nporg)
     gnp <- na.omit(nporg[, "gnp.r"])
     gnp.l <- log(gnp)
     #
     ers.gnp <- ur.ers(gnp, type="DF-GLS", model="trend", lag.max=4)
     show(ers.gnp)
     #
     kpss.gnp <- ur.kpss(gnp.l, type="tau", lags="short")
     show(kpss.gnp)
     #
     pp.gnp <- ur.pp(gnp, type="Z-tau", model="trend", lags="short")
     show(pp.gnp)
     #
     df.gnp <- ur.df(gnp, type="trend", lags=4)
     show(df.gnp)
     #
     sp.gnp <- ur.sp(gnp, type="tau", pol.deg=1, signif=0.01)
     show(sp.gnp)
     #
     za.gnp <- ur.za(gnp, model="both", lag=2)
     show(za.gnp)
     #
     data(denmark)
     sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
     sjd.vecm <- ca.jo(sjd, ecdet = "const", type="eigen", K=2, season=4)
     show(sjd.vecm)
     #
     HD0 <- matrix(c(-1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1), c(5,4))
     show(blrtest(sjd.vecm, H=HD0, r=1))

