This paper evaluates the model risk of models used for forecasting systemic and market risk. Model risk, which is the potential for different models to provide inconsistent outcomes, is shown to be increasing with and caused by market uncertainty. During calm periods, the underlying risk...

Epidemics are often modeled using non-linear dynamical systems observed through partial and noisy data. In this paper, we consider stochastic extensions in order to capture unknown influences (changing behaviors, public interventions, seasonal effects, etc.). These models assign diffusion...

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...

Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such...

We use tests for multiple breaks at unknown points in the sample, and the Stock-Watson (1996, 1998) time-varying parameters median-unbiased estimation methodology, to investigate changes in the equilibrium rate of growth of labor productivity–both per hour and per worker–in the United...

In many economic applications involving comparisons of multivariate distributions, supermodularity of an objective function is a natural property for capturing a preference for greater interdependence. One multivariate distribution dominates another according to the `supermodular stochastic...

In this paper, we propose to identify the dependence structure existing between the returns of equity and commodity futures and its evolution through the past 20 years. The key point is that we do not do not impose the dependence structure but let the data select it. To do so, we model the...