This study investigates the macroeconomic resilience of the Moroccan economy using a comprehensive analysis of key indicators and policy variables. Utilising data from sources such as the World Bank, we examined GDP per capita, government debt, government final expenditure, agriculture and...

We propose measures of financial market stress for forty-six countries and regions across the world. Our measures indicate that worldwide financial market stresses rose significantly in March following the widespread economic shutdowns in the wake of the COVID-19 pandemic. However, hardly...

We analyze a model for N different measurements of a persistent latent time series when measurement errors are mean-reverting, which implies a common trend among measurements. We study the consequences of overdifferencing, finding potentially large biases in maximum likelihood estimators of the...

We model the United States macroeconomic and financial sectors using a formal and unified econometric model. Through shrinkage, our Bayesian VAR provides a flexible framework for modeling the dynamics of thirty-one variables, many of which are tracked by the Federal Reserve. We show how the...

We propose a nonparametric Bayesian approach for conducting inference on probabilistic surveys. We use this approach to study whether U.S. Survey of Professional Forecasters density projections for output growth and inflation are consistent with the noisy rational expectations hypothesis. We...

We exploit the information in the successive vintages of gross domestic expenditure (GDE) and gross domestic income (GDI) from the current comprehensive revision to obtain an improved, timely measure of U.S. aggregate output by exploiting cointegration between the different measures and taking...

We document the real-time forecasting performance for output and inflation of the New York Fed dynamic stochastic general equilibrium (DSGE) model since 2011. We find the DSGE's accuracy to be comparable to that of private forecasters before Covid, but somewhat worse thereafter.

We provide a toolkit for efficient online estimation of heterogeneous agent (HA) New Keynesian (NK) models based on Sequential Monte Carlo methods. We use this toolkit to compare the out-of-sample forecasting accuracy of a prominent HANK model, Bayer et al. (2022), to that of the representative...

We modify the Laubach-Williams and Holston-Laubach-Williams models of the natural rate of interest to account for time-varying volatility and a persistent COVID supply shock during the pandemic. Resulting estimates of the natural rate of interest in the United States, Canada, and the Euro Area...

We study estimation and inference in panel data regression models when the regressors of interest are macro shocks, which speaks to a large empirical literature that targets impulse responses via local projections. Our results hold under general dynamics and are uniformly valid over the degree...