We use dynamic panel data models to generate density forecasts for daily Covid-19 infections for a panel of countries/regions. At the core of our model is a specification that assumes that the growth rate of active infections can be represented by autoregressive fluctuations around a downward...

Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models,...

A recent literature has developed that combines two prominent empirical approaches to ex ante policy evaluation: randomized controlled trials (RCT) and structural estimation. The RCT provides a "gold-standard'' estimate of a particular treatment, but only of that treatment. Structural estimation...

The paper discusses prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models, and provides a method for constructing prior distributions for a subset of these parameters from beliefs about the moments of the endogenous variables. The empirical application...

Implicit in the drug-approval process is a trade-off between Type I and Type II error. We explore the application of Bayesian decision analysis (BDA) to minimize the expected cost of drug approval, where relative costs are calibrated using U.S. Burden of Disease Study 2010 data. The results for...