Logistic_Estimation {EWS}  R Documentation 
This function provides methods for estimating the four dichotomous models as in Kauppi & Saikkonen (2008). Based on a logit approach, models are estimated in a univariate or a balanced panel framework as in Candelon, Dumitrescu and Hurlin (2014). This estimation has been used in recent papers such in Ben Naceur, Candelon and Lajaunie (2019) and Hasse and Lajaunie (2020).
Logistic_Estimation(Dicho_Y, Exp_X, Intercept, Nb_Id, Lag, type_model)
Dicho_Y 
Vector of the binary time series. 
Exp_X 
Vector or Matrix of explanatory time series. 
Intercept 
Boolean value: TRUE for an estimation with intercept, and FALSE otherwise. 
Nb_Id 
Number of individuals studied for a panel approach. Nb_Id=1 in the univariate case. 
Lag 
Number of lags used for the estimation. 
type_model 
Model number: 1, 2, 3 or 4. > 1 for the static model:
> 2 for the dynamic model with lag binary variable:
> 3 for the dynamic model with lag index variable:
> 4 for the dynamic model with both lag binary variable and lag index variable:

A list with:
Estimation 
a dataframe containing the coefficients of the logitic estimation, the Standard Error for each coefficient, the Zscore and the associated critical probability 
AIC 
a numeric vector containing the Akaike information criterion 
BIC 
a numeric vector containing the Bayesian information criterion 
R2 
a numeric vector containing the Pseudo R Square 
index 
a numeric vector containing the estimated index 
prob 
a numeric vector containing the estimated probabilities 
LogLik 
a numeric vector containing the Log likelihood value of the estimation 
VCM 
a numeric matrix of the Variance Covariance of the estimation 
For the panel estimation, data must be stacked one after the other for each country or for each individual.
JeanBaptiste Hasse and Quentin Lajaunie
Candelon, Bertrand, ElenaIvona Dumitrescu, and Christophe Hurlin. "Currency crisis early warning systems: Why they should be dynamic." International Journal of Forecasting 30.4 (2014): 10161029.
Hasse, JeanBaptiste, Lajaunie Quentin. "Does the Yield Curve Signal Recessions? New Evidence from an International Panel Data Analysis." (2020)
Kauppi, Heikki, and Pentti Saikkonen. "Predicting US recessions with dynamic binary response models." The Review of Economics and Statistics 90.4 (2008): 777791.
Naceur, Sami Ben, Bertrand Candelon, and Quentin Lajaunie. "Taming financial development to reduce crises." Emerging Markets Review 40 (2019): 100618.
# NOT RUN {
# Import data
data("data_USA")
# Data process
Var_Y < as.vector(data_USA$NBER)
Var_X < as.vector(data_USA$Spread)
# Estimate the logit regression
results < Logistic_Estimation(Dicho_Y = Var_Y, Exp_X = Var_X, Intercept = TRUE,
Nb_Id = 1, Lag = 1, type_model = 1)
# print results
results
# }