How far can we forecast? Statistical tests of the predictive content

Arbeitspapier

Forecasts are useless whenever the forecast error variance fails to be smaller than the unconditional variance of the target variable. This paper develops tests for the null hypothesis that forecasts become uninformative beyond some limiting forecast horizon h. Following Diebold and Mariano (DM, 1995) we propose a test based on the comparison of the mean-squared error of the forecast and the sample variance. We show that the resulting test does not possess a limiting normal distribution and suggest two simple modifications of the DM-type test with different limiting null distributions. Furthermore, a forecast encompassing test is developed that tends to better control the size of the test. In our empirical analysis, we apply our tests to macroeconomic forecasts from the survey of Consensus Economics. Our results suggest that forecasts of macroeconomic key variables are barely informative beyond 2-4 quarters ahead.

Object Details

• ISBN: 978-3-95729-437-1
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Bundesbank Discussion Paper ; No. 07/2018

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Forecasting Models; Simulation Methods
• Subject: Hypothesis Testing ; Predictive Accuracy ; Informativeness

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Breitung, Jörg ; Knüppel, Malte
• Event: Veröffentlichung
• (who): Deutsche Bundesbank
• (where): Frankfurt a. M.
• (when): 2018

Further information

• Handle: http://hdl.handle.net/10419/178500
• Last update: 10.03.2025, 11:41 AM CET