Markvov Switching 2nd order moments
res=MSVAR_stderr(res,hdelta)
* res = a results tlist from a Markov switching estimation
* hdelta = a scalar, the increment used to calculate the hessian matrix
* res = the initial results tlist with the following fields updated:
- res('stderr') = the (np x 1) vector of coefficients standard errors
- res('tstat') = the (np x 1) vector of associated t-stats
- res('pvalue') = the (np x 1) vector of associated p-values
- res('covbeta') = the (np x np) variance-covariance matrix of the parameters
- res('corbeta') = the (np x np) correlation matrix of the parameters
- res('ptrans_tstat') = the (M x 1) vector of t-stats for the transition probabilities
- res('beta_id_tstat') = the (1 x n_x*K*M) vector of t-stats for switching parameters
- res('beta_co_tstat') = the (1 x n_z*K) vector of t-stats for non switching parameters
- res('sigma_tstat') = the (M*M_V x M) matrix of t-stats for the variance-covariance matrix of the residuals
- res('ptrans_pvalue') = the (M x M) matrix of t-stats for transition probabilities
- res('beta_id_pvalue') = the (1 x n_x*K*M) vector of t-stats for switching parameters
- res('beta_co_pvalue') = the (1 x n_z*K) vector of t-stats for non switching parameters
- res('sigma_pvalue') = the (M*M_V x M) matrix of t-stats for the variance-covariance matrix of the residuals
load(GROCERDIR+'\macros\grocer\db\us_revu.dat') bounds('1967m4','2004m2') nb_states=2 switch_var=2 var_opt=3 r=ms_vares('cte',3,'100*(log(us_revu)-lagts(2,log(us_revu)))',nb_states,switch_var,var_opt,'prt=initial;final','transf=stud') r=MSVAR_stderr(r,1e-3) // In this example, the second order moments are re-estimated using a larger increment than the one used to estimate the ms_var model (1e-5). | ![]() | ![]() |