In this study we construct a measure of macroeconomic uncertainty from several observable economic indicators for the euro area. Indicator variables are based on financial market data, such as medium-term returns, loss and volatility measures but also come from surveys that capture business and...

This paper studies a nonlinear one-factor term structure model in discrete time. The single factor is the short-term interest rate, which is modeled as a self-exciting threshold autoregressive (SETAR) process. Our specification allows for shifts in the intercept and the variance. The process is...

We estimate time-varying expected excess returns on the US stock market from 1983 to 2008 using a model that jointly captures the arbitrage-free dynamics of stock returns and nominal bond yields. The model nests the class of affine term structure (of interest rates) models. Stock returns and...

We forecast recession probabilities for the United States, Germany and Japan. The predictions are based on the widely-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a ‘ProbVAR’. At any point in time, the ProbVAR allows to...

We estimate time-varying expected excess returns on the US stock market from 1983 to 2008 using a model that jointly captures the arbitrage-free dynamics of stock returns and nominal bond yields. The model nests the class of affine term structure (of interest rates) models. Stock returns and...

This paper studies a nonlinear one-factor term structure model in discrete time. The single factor is the short-term interest rate, which is modeled as a self-exciting threshold autoregressive (SETAR) process. Our specification allows for shifts in the intercept and the variance. The process is...

We forecast recession probabilities for the United States, Germany and Japan. The predictions are based on the widely-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a 'ProbVAR'. At any point in time, the ProbVAR allows to generate...

We propose a classical approach to estimate factor-augmented vector autoregressive (FAVAR) models with time variation in the factor loadings, in the factor dynamics, and in the variance-covariance matrix of innovations. When the time-varying FAVAR is estimated using a large quarterly dataset of...