This paper revisits ination forecasting using reduced form Phillips curve forecasts, i.e., inflation forecasts using activity and expectations variables. We propose a Phillips curve-type model that results from averaging across different regression specifications selected from a set of potential...

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by...

We study the synchronization of real and nominal variables across four different regions of the world, Asia, Europe, North and South America, covering 32 different countries. Employing a FAVAR framework, we distinguish between global and regional demand and supply shocks and document the...

Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using ¯nancial and macroeconomic time series....

There are two main approaches to modelling monetary policy; simple instrument rules and optimal policy. We propose an alternative that combines the two by extending the loss function with a term penalizing deviations from a simple rule. We analyze the properties of the modified loss function by...

We investigate the importance of employing a valid model for monetary policy analysis. Specifically, we investigate the economic significance of differences in specification and empirical validity of models. We consider three alternative econometric models of wage and price inflation in Norway....

Real Business Cycle (RBC) and Dynamic Stochastic General Equilibrium (DSGE) methods have become essential components of the macroeconomist’s toolkit. This literature review stresses recently developed techniques for computation and inference, providing a supplement to the Romer (2006)...

We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary...

We propose a novel Bayesian model combination approach where the combination weights depend on the past forecasting performance of the individual models entering the combination through a utility-based objective function. We use this approach in the context of stock return predictability and...

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...