This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

This paper investigates the accuracy of forecasts from four DSGE models for inflation, output growth and the federal funds rate using a real-time dataset synchronized with the Fed’s Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as...

Diagnosing foehn winds from weather station data downwind of topographic obstacles requires distinguishing them from other downslope winds, particularly nocturnal ones driven by radiative cooling. We present an automatic classification scheme to obtain reproducible results that include...