In this paper we use U.S. real-time vintage data and produce combined density nowcasts for quarterly GDP growth from a system of three commonly used model classes. The density nowcasts are combined in two steps. First, a wide selection of individual models within each model class are combined...

In this paper we document real rate behavior. We do this by looking across a wide variety of constructed real rate series. These series are obtained by using a number of different methodologies for estimating expected inflation, using several different price series, and looking over different...

This paper shows how to compute the h-step-ahead predictive likelihood for any subset of the observed variables in parametric discrete time series models estimated with Bayesian methods. The subset of variables may vary across forecast horizons and the problem thereby covers marginal and joint...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large...

In recent times DSGE models came more and more into the focus of forecasters and showed promising forecast performances for the short term. We contribute to the existing literature by analyzing the forecast power of a DSGE model including endogenous growth for the medium run. Instead of only...

Density forecast combinations are examined in real-time using the log score to compare five methods: fixed weights, static and dynamic prediction pools, as well as Bayesian and dynamic model averaging. Since real-time data involves one vintage per time period and are subject to revisions, the...

We present a new composite leading indicator of economic activity in mainland China, estimated using a dynamic factor model. Our leading indicator is constructed from three series: exports, a real estate climate index, and the Shanghai Stock Exchange index. These series are found to share a...

We examine the accuracy of survey-based expectations of the Chilean exchange rate relative to the US dollar. Our out-of-sample analysis reveals that survey-based forecasts outperform the Driftless Random Walk (DRW) in terms of Mean Squared Prediction Error at several forecasting horizons. This...

We review several methods to define and forecast classical business cycle turning points in Norway. In the paper we compare the Bry - Boschan rule (BB) with a Markov Switching model (MS), using alternative vintages of Norwegian Gross Domestic Product (GDP) as the business cycle indicator. The...