Recently, a number of authors have argued that the standard search model cannot generate the observed business-cycle-frequency fluctuations in unemployment and job vacancies, given shocks of a plausible magnitude. We use data on the cost of vacancy creation and cyclicality of wages to identify...

Implied volatility indices should have information about risk parameters, once they are cleansed of the influence of normal volatility dynamics and macroeconomic uncertainty. Building on intuition from the dynamic asset pricing literature, we uncover unobserved risk aversion and fundamental...

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

Consumption risk sharing among U.S. federal states increases in booms and decreases in recessions. We find that small firms' access to credit markets plays an important role in explaining this stylized fact: business cycle fluctuations in aggregate risk sharing are more pronounced in states in...

Using a Bayesian likelihood approach, we estimate a dynamic stochastic general equilibrium model for the US economy using seven macro-economic time series. The model incorporates many types of real and nominal frictions and seven types of structural shocks. We show that this model is able to...

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...

This paper proposes an explanation of the shifts in the volatility of exchange rate returns that relies on standard present value exchange rate models. Agents are uncertain about the true data generating model and deal with the model uncertainty by making inference on the models and their...

We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process and a stochastic conditional return which reflects nonlinear positive feedbacks and continuous updates of the investors' beliefs and sentiments. The conditional expected returns...

The aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts. We produce real time out-of-sample forecasts for inflation, the unemployment rate and the interest rate using a Time-Varying Coefficients VAR with Stochastic...

We develop a discrete-time stochastic volatility option pricing model, which exploits the information contained in high-frequency data. The Realized Volatility (RV) is used as a proxy of the unobservable log-returns volatility. We model its dynamics by a simple but effective (pseudo) long memory...