Economic Forecasting

Graham Elliott, Allan Timmermann

Journal of Economic Literature · 2008 · 237 citations · 43 references

Concepts

TL;DR

Forecasts guide economic and financial decisions, and their value is judged relative to those decisions; decision theory provides a framework for constructing and evaluating forecasts, helping to navigate the challenges posed by the proliferation of predictors and models, none of which may represent a true underlying process. The study examines how the loss function shapes the forecaster’s objectives. The authors illustrate this by reviewing methods for comparing model pairs and assessing whether the best among many models can outperform a benchmark.

Abstract

Forecasts guide decisions in all areas of economics and finance and their value can only be understood in relation to, and in the context of, such decisions. We discuss the central role of the loss function in helping determine the forecaster's objectives. Decision theory provides a framework for both the construction and evaluation of forecasts. This framework allows an understanding of the challenges that arise from the explosion in the sheer volume of predictor variables under consideration and the forecaster's ability to entertain an endless array of forecasting models and time-varying specifications, none of which may coincide with the “true” model. We show this along with reviewing methods for comparing the forecasting performance of pairs of models or evaluating the ability of the best of many models to beat a benchmark specification.

References

43