Evaluating the forecast densities of linear and non-linear models: applications to output growth and unemployment

Michael P. Clements · Jeremy P Smith

153 citations0/0 files storedJournal of Forecasting

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Forecasting Techniques and Applications Monetary Policy and Economic Impact Statistical Methods and Applications

Abstract

In economics density forecasts are rarely available, and as a result attention has traditionally focused on point forecasts of the mean and the use of mean square error statistics to represent the loss function. In this paper we apply recently developed methods of forecast density evaluation to compare model-based density forecasts of US output growth and changes in the unemployment rate. Since one of the models is non-linear and characterized by a changing error variance, density evaluation may offer greater discrimination than evaluation based on the first moment. Copyright © 2000 John Wiley & Sons, Ltd.

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1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle 1996Impulse response analysis in nonlinear multivariate models 1998Evaluating Interval Forecasts 1996Inference When a Nuisance Parameter Is Not Identified Under the Null Hypothesis 1998Evaluating Density Forecasts with Applications to Financial Risk Management 1996Asymptotic Inference about Predictive Ability 1981On Market Timing and Investment Performance. II. Statistical Procedures for Evaluating Forecasting Skills 1992A Simple Nonparametric Test of Predictive Performance

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