ms_forecast — forecast from a Markvov Switching regression model
res=ms_forecast(rms,hprev,exo_com,exo_idio)
rms = a tlist result from a ms switching estimation
hprev = the prevision period which can be either
* a [n1 n2] constant vector where n1 and n2 are the lead over the last period of the estimation (n1<=0 means that the forecast begins within the estimation period)
* a n constant which is equivalent to [1 n] (forecast begins just after the estimation period)
* a [n1 n2] string vector where n1 and n2 are the time periods for forecasting (a posibility open only if the MS regression has been performed with ts)
* a n string which is equivalent to [1 n] (forecast begins just after the estimation period)
exo_com = the data on the forecast horizon for the non switching exogenous variables that can be:
* a (H x n_x) matrix with H the number of forecasts and n_x the number of non switching exogenous variables
* a list of ts available over the forecasting horizon
* a list of (H x 1) vectors and ts available over the forecasting horizon
* a (H x n_x) string matrix of names (note: when the ms tlist results comes from a ms-mean or a var estimation, the variables are useless and can therefore be omitted)
exo_idio = the data on the forecast horizon for the switching exogenous variables that can be:
* a (H x n_z) matrix with H the number of forecasts and n_z the number of switching exogenous variables
* a list of ts available over the forecasting horizon
* a list of (H x 1) vectors and ts available over the forecasting horizon
* a (H x n_x) string matrix of names (note: when the ms tlist results comes from a ms-mean or a var estimation, the variables are useless and can therefore be omitted)
r = a results tlist with:
- res('meth') = 'msf'
- res('r_ms') = the tlist results from the MS estimation
- res('pstates') = the (H x nb_states) matrix of the probabilities of the respective states over the forecasting horizon
- res('prev_states') = the matrix of forecast of the endogenous variables accross the states
- res('prev') = the matrix of forecast of the endogenous variables
- res('hprev') = the forecast period
bounds('1984m2','2003m1'); r=ms_mean(['delts(log(construc))';'delts(log(ipi))';'delts(log(helpwanted))';'delts(log(revu))'],3,1,1,'transf=stud','datation=datation_bb') rf=ms_forecast(r,10) f=ms_forecast(r,'2003m11') rf=ms_forecast(r,['2003m2' ; '2003m11']) // All these examples provide a forecast from 2003m2 to 2003m11 of the ms-mean example provided in function ms_mean (second example is also in function ms_mean_d).