conditional_forecast

conditional_forecast — computes a simulation of a stochastic model conditionally to a specified future path for some endogenous variables.

Synopsis

conditional_forecast [(OPTION [, OPTION...])] VARIABLE_NAME [[,] VARIABLE_NAME...] ;

Options

parameter_set = prior_mode | prior_mean | posterior_mode | posterior_mean | posterior_median

Specify the parameter set to use for the forecasting. No default value, mandatory option.

controlled_varexo = (VARIABLE_NAME [ [,] VARIABLE_NAME ... ] )

Specify the exogenous variables to use as control variables. No default value, mandatory option.

periods = INTEGER

Number of periods of the forecast. Default: 40. periods cannot be less than the number of constrained periods.

replic = INTEGER

Number of simulations. Default: 5000.

conf_sig = DOUBLE

Level of significance for confidence interval. Default: 0.80

Description

conditional_forecast computes forecasts on an estimated model for a given constrained path of some future endogenous variables. This is done, from the reduced form representation of the DSGE model, by finding the structural shocks that are needed to match the restricted paths. This command has to be called after estimation.

Use conditional_forecast_paths to give the list of constrained endogenous, and their constrained future path. Option controlled_varexo is used to specify the structural shocks which will be matched to generate the constrained path.

Use plot_conditional_forecast to graph the results.

Example

var y a
varexo e u;

...

estimation(...);

conditional_forecast_paths;
var y;
periods 1:3, 4:5;
values 2, 5;
var a;
periods 1:5;
values 3;
end;

conditional_forecast(parameter_set = calibration, controlled_varexo = (e, u), replic = 3000);

plot_conditional_forecast(periods = 10) e u;