Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small and unpredictable. This paper shows that revisions to German national accounts are biased, large and predictable. Moreover, using filtering techniques designed...

This paper proposes a framework to implement regression-based tests of predictive ability in unstable environments, including, in particular, forecast unbiasedness and efficiency tests, commonly referred to as tests of forecast rationality. Our framework is general: it can be applied to...

The forecast combination literature has optimal combination methods, however, empirical studies have shown that the simple average is notoriously difficult to improve upon. This paper introduces a novel way to choose a subset of forecasters who might have specialized knowledge to improve upon...

In this paper, we propose a framework to evaluate the information content of subjective expert density forecasts using micro data from the ECB’s Survey of Professional Forecasters (SPF). A key aspect of our analysis is the use of scoring functions which evaluate the entire predictive...

In this study we construct the R(ecession)-word index for Switzerland. To the best of our knowledge, this has never been done before. We evaluate the extent to which the inclusion of the index contributes to more accurate forecasts of GDP growth compared with a benchmark autoregressive model. We...

This paper proposes forecast optimality tests that can be used in unstable environments. They include tests for forecast unbiasedness, efficiency, encompassing, serial uncorrelation, and, in general, regression-based tests of forecasting ability. The proposed tests are applied to evaluate the...

This paper investigates the predictive accuracy of two alternative forecasting strategies, namely the forecast and information combinations. Theoretically, there should be no role for forecast combinations in a world where information sets can be instantaneously and costlessly combined. However,...

This paper introduces the new Monthly Index of Business Activity (MIBA) model of the Banque de France for forecasting France's GDP. As the previous versions, the model relies exclusively on data from the monthly business survey (EMC) conducted by the Banque de France. However, several major...

In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000), and...

We evaluate various models' relative performance in forecasting future US output growth and inflation on a monthly basis. Our approach takes into account the possibility that the models' relative performance can be varying over time. We show that the models' relative performance has, in fact,...