Government agencies and other national and international institutions are asked to perform forecasts over the medium term. In particular, the EU Stability and Growth Pact contains the obligation to formulate stability programmes over four years, covering a general economic outlook as well as the...

This paper uses a panel VAR (PVAR) approach to estimating, analysing and forecasting price dynamics in four different sectors - industry, services, construction, and agriculture - across the four largest euro area economies - Germany, France, Italy and Spain - and the euro area as a whole. By...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...

We reassess the predictability of U.S. recessions at horizons from three months to two years ahead for a large number of previously proposed leading-indicator variables. We employ an efficient probit estimator for partially missing data and assess relative model performance based on the receiver...

This paper discusses how the forecast accuracy of a Bayesian vector autoregression(BVAR) is affected by introducing the zero lower bound on the federal funds rate. As abenchmark I adopt a common BVAR specification, including 18 variables, estimatedshrinkage, and no nonlinearity. Then I entertain...

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes - Bayesian (static) model averaging and dynamic model averaging - so...

Emerging-market economies have become increasingly important in driving global GDP growth over the past 10 to 15 years. This has made timely and accurate assessment of current and future economic activity in emerging markets important for policy-makers not only in these countries but also in...

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a...

A Bayesian nonparametric predictive model is introduced to construct time-varying weighted combinations of a large set of predictive densities. A clustering mechanism allocates these densities into a smaller number of mutually exclusive subsets. Using properties of Aitchinson's geometry of the...

In this paper we study what professional forecasters actually explain. We use spectral analysis and state space modeling to decompose economic time series into a trend, a business-cycle, and an irregular component. To examine which components are captured by professional forecasters we regress...