bh6lrtest            package:urca            R Documentation(latin1)

_L_i_k_e_l_i_h_o_o_d _r_a_t_i_o _t_e_s_t _f_o_r _r_e_s_t_r_i_c_t_i_o_n_s _u_n_d_e_r _p_a_r_t_l_y _k_n_o_w_n _b_e_t_a _i_n
_a _s_u_b_s_p_a_c_e

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

     This function estimates a restricted VAR, where some restrictions
     are placed on r1 cointegrating relations which are chosen in the
     space of the matrix H. The test statistic is distributed as chi^2
     with (p-s-r2)r1 degrees of freedom, with s equal to the number of
     columns of *H*, r1 the number of cointegrating relations in the
     first partition and r2 the number of cointegrating relations in
     the second partition which will be estimated without any
     restrictions.

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

     bh6lrtest(z, H, r, r1, conv.val = 0.0001, max.iter = 50)

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

       z: An object of class 'ca.jo'.

       H: The (p times s) matrix containing the known cointegration
          relations.

       r: The count of cointegrating relationships; 
           inferred from 'summary(ca.jo-object)'.

      r1: The count of cointegrating relationships in the first
          partition of the cointegration space; 

conv.val: The convergence value of the algorithm. (see details); 

max.iter: The maximal number of iterations.

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

     Please note, that the following ordering of the dimensions should
     be obeyed: r1 <=q s <=q p - r2. A two-step algorithm is used to
     determine the eigen values of the restricted model. Convergence is
     achieved if the quadratic norm of the eigen values is smaller than
     'conv.val'.

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

     An object of class 'cajo.test'.

_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.

     Johansen, S. and Juselius, K. (1992), Testing structural
     hypotheses in a multivariate cointegration analysis of the PPP and
     the UIP for UK, _Journal of Econometrics_, *53*, 211-244.

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

     'ca.jo', 'alrtest', 'ablrtest', 'blrtest', 'bh5lrtest',
     'cajo.test-class', 'ca.jo-class' and 'urca-class'.

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

     data(UKpppuip)
     attach(UKpppuip)
     dat1 <- cbind(p1, p2, e12, i1, i2)
     dat2 <- cbind(doilp0, doilp1)
     H1 <- ca.jo(dat1, type='trace', K=2, season=4, dumvar=dat2)
     H6 <- matrix(c(1,0,0,0,0, 0,1,0,0,0, 0,0,1,0,0), c(5,3))
     bh6lrtest(z=H1, H=H6, r=2, r1=1, conv.val=0.0001, max.iter=50)

