GIRF_Proba_CI {EWS}

Confidence Intervals for the Probability - GIRF Analysis

Description

From the results of the Simulation_GIRF function, this function calculates the values of the upper and lower bounds of the confidence intervals, as well as the average of the different response functions for the probability.

Usage

GIRF_Proba_CI(results_simul_GIRF, CI_bounds, n_simul, horizon_forecast)

Arguments

results_simul_GIRF

Matrix containing results of the Simulation_GIRF function.

CI_bounds

Numeric variable between 0 and 1 for the size of the confidence intervals.

n_simul

Numeric variable equal to the total number of replications.

horizon_forecast

Numeric variable corresponding to the horizon target for the GIRF analysis.

Value

A list with:

horizon

Numeric vector containing the horizon targer.

Simulation_CI_proba_shock

a matrix containing the set of simulations of probabilities with shock belonging to the confidence interval.

Simulation_CI_proba

a matrix containing the set of simulations of probabilities belonging to the confidence interval.

CI_proba_shock

a matrix containing three columns: the lower bound of the CI, the average of the IRFs, and the upper bound of the CI for the probabilities with shock.

CI_proba

a matrix containing three columns: the lower bound of the CI, the average of the IRFs, and the upper bound of the CI for the probabilities.

Author(s)

Jean-Baptiste Hasse and Quentin Lajaunie

References

Lajaunie, Quentin. Generalized Impulse Response Function for Dichotomous Models. No. 2852. Orleans Economics Laboratory/Laboratoire d'Economie d'Orleans (LEO), University of Orleans, 2021.

Examples

# NOT RUN {

# Import data
data("data_USA")

# Data process
Var_Y <- as.vector(data_USA$NBER)
Var_X <- as.vector(data_USA$Spread)

# Simulation for the GIRF analysis
results_simulation <- Simul_GIRF(Var_Y, Var_X, TRUE, 1, 1, 2, 0.95, 3, "AM")

# Confidence intervals for the index
results <- GIRF_Proba_CI(results_simulation, 0.95, 2, 3)

# print results
results

#}