cajorls             package:urca             R Documentation(latin1)

_O_L_S _r_e_g_r_e_s_s_i_o_n _o_f _V_E_C_M

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

     This function returns the OLS regressions of a restricted VECM,
     _i.e._ it returns a list object with elements of class `lm'
     containing the restricted VECM and a matrix object with the
     normalised cointegrating relationships. The user can provide a
     certain number of which equation in the VECM should be estimated
     and reported, or if '"reg.number = NULL"' each equation in the
     VECM will be estimated and its results are reported. Furthermore,
     the cointegratioon rank has to be supplied too.

_U_s_a_g_e:

     cajorls(z, r = 1, reg.number = NULL)

_A_r_g_u_m_e_n_t_s:

       z: An object of class 'ca.jo' or 'cajo.test'.

       r: An integer, signifiying the cointegration rank.

reg.number: The number of the equation in the VECM that should be
          estimated or if set to 'NULL' (the default), all equations
          within the VECM are estimated.

_D_e_t_a_i_l_s:

     The cointegration space is normalised as *beta*_c =
     *beta*(S'*beta*)^{-1}, with S' = (I_r, 0).

_V_a_l_u_e:

     Returns a list object with elements of class 'lm' for the
     restricted VECM and a matrix object with the normalised
     cointegrating vectors.

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

     Bernhard Pfaff

_R_e_f_e_r_e_n_c_e_s:

     Johansen, S. (1995), _Likelihood-Based Inference in Cointegrated
     Vector Autoregressive Models_, Oxford University Press, Oxford.

     Ltkepohl, H. (2006), _New Introduction to Multiple Time Series
     Analysis_, Springer, New York.

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

     'ca.jo', 'cajools', 'lm', 'ca.jo-class' and 'urca-class'.

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

     data(finland)
     sjf <- finland
     sjf.vecm <- ca.jo(sjf, ecdet = "none", type = "eigen", K = 2,
     spec = "longrun", season = 4)
     sjf.vecm.rls <- cajorls(sjf.vecm, r = 2)
     summary(sjf.vecm.rls$rlm)
     sjf.vecm.rls$beta

