Economic forecasting in a changing world

This article explains the basis for a theory of economic forecasting developed over the past decade by the authors. The research has resulted in numerous articles in academic journals, two monographs, Forecasting Economic Time Series, 1998, Cambridge University Press, and Forecasting Nonstationary Economic Time Series, 1999, MIT Press, and three edited volumes, Understanding Economic Forecasts, 2001, MIT Press, A Companion to Economic Forecasting, 2002, Blackwells, and the Oxford Bulletin of Economics and Statistics, 2005. The aim here is to provide an accessible, non-technical, account of the main ideas. The interested reader is referred to the monographs for derivations, simulation evidence, and further empirical illustrations, which in turn reference the original articles and related material, and provide bibliographic perspective

Economic Forecasting: Some Lessons from Recent Research

This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent results can be judged. We compare this framework to a previous formulation, which was silent on the very issues of most concern to the forecaster. We describe a number of aspects which it illuminates, and draw out the implications for model selection. Finally, we discuss the areas where research remains needed to clarify empirical findings which lack theoretical explanations.

Pooling of Forecasts

We consider forecasting using a combination, when no model coincides with a non-constant data generation process (DGP). Practical experience suggests that combining forecasts adds value, and can even dominate the best individual device. We show why this can occur when forecasting models are differentially mis-specified, and is likely to occur when the DGP is subject to deterministic shifts. Moreover, averaging may then dominate over estimated weights in the combination. Finally, it cannot be proved that only non-encompassed devices should be retained in the combination. Empirical and Monte Carlo illustrations confirm the analysis.

Economic forecasting: some lessons from recent research

This paper describes some recent advances and contributions to our understanding of economic forecasting. The framework we develop helps explain the findings of forecasting competitions and the prevalence of forecast failure. It constitutes a general theoretical background against which recent results can be judged. We compare this framework to a previous formulation, which was silent on the very issues of most concern to the forecaster. We describe a number of aspects which it illuminates, and draw out the implications for model selection. Finally, we discuss the areas where research remains needed to clarify empirical findings which lack theoretical explanations. JEL Classification: C32

Economic Forecasting: Some Lessons from Recent Research

We describe a general theoretical framework against which recent results in economic forecasting can be judged, including explanations for the findings of forecasting competitions, the prevalence of forecast failure, and the role of causal variables. We compare this framework to a previous formulation which was silent on the very issues of most concern to the forecaster, then describe ten aspects which our approach illuminates, and draw out their implications for model selection. Finally, we discuss ten areas where research is needed to clarify empirical findings that still lack theoretical explanations.

A robust method for measuring the Hubble parameter

We obtain a robust, non-parametric, estimate of the Hubble constant from galaxy linear diameters calibrated using HST Cepheid distances. Our method is independent of the parametric form of the diameter function and the spatial distribution of galaxies and is insensitive to Malmquist bias. We include information on the galaxy rotation velocities; unlike Tully-Fisher, however, we retain a fully non-parametric treatment. We find $H_0=66\pm6$ km/s/Mpc, somewhat larger than previous results using galaxy diameters.Comment: 4 pages, 1 figure, Cosmic Flows Workshop, Victoria B.C. Canada, July 1999, ed. S. Courteau, M. Strauss & J. Willick, ASP conf. serie

How far is it to a sudden future singularity of pressure?

We discuss the constraints coming from current observations of type Ia supernovae on cosmological models which allow sudden future singularities of pressure (with the scale factor and the energy density regular). We show that such a sudden singularity may happen in the very near future (e.g. within ten million years) and its prediction at the present moment of cosmic evolution cannot be distinguished, with current observational data, from the prediction given by the standard quintessence scenario of future evolution. Fortunately, sudden future singularities are characterized by a momentary peak of infinite tidal forces only; there is no geodesic incompletness which means that the evolution of the universe may eventually be continued throughout until another ``more serious'' singularity such as Big-Crunch or Big-Rip.Comment: REVTEX4, 4 pages, 2 figures, references change