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 applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and...

Accurate real-time macroeconomic data are essential for policy-making and economic nowcasting. In this paper, I introduce a real-time database for German regional economic accounts (READ-GER). The database contains real-time information for nine macroeconomic aggregates and the 16 German states....

Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore several new forecasting...

Futures markets are a potentially valuable source of information about price expectations. Exploiting this information has proved difficult in practice, because time-varying risk premia often render the futures price a poor measure of the market expectation of the price of the underlying asset....

This paper provides a novel approach to forecasting time series subject to discrete structural breaks. We propose a Bayesian estimation and prediction procedure that allows for the possibility of new breaks over the forecast horizon, taking account of the size and duration of past breaks (if...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

Using a novel dataset that contains qualitative firm survey data on sales forecasts as well as balance-sheet data on realized sales, we document that only major forecast errors are predictable and display autocorrelation. This result is a particular violation of the Full Information Rational...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

We reformulate the Nordhaus test as a friction model where the large number of zero revisions are treated as censored, i.e., unknown values inside a small region of "imperceptibility." Using Blue Chip individual forecasts of U.S. real GDP growth, inflation, and unemployment over 1985-2020, we...