Publication Type

Journal Article

Version

submittedVersion

Publication Date

1-2024

Abstract

We propose two types of equal predictive ability (EPA) tests with panels to compare the predictions made by two forecasters. The first type, S-statistics, focuses on the overall EPA hypothesis, which states that the EPA holds, on average, over all panel units and over time. The second type, C-statistics, focuses on the clustered EPA hypothesis where the EPA holds jointly for a fixed number of clusters of panel units. The asymptotic properties of the proposed tests are evaluated under weak and strong cross-sectional dependence. An extensive Monte Carlo simulation shows that the proposed tests have very good finite sample properties, even with little information about the cross-sectional dependence in the data. The proposed framework is applied to compare the economic growth forecasts of the OECD and the IMF, and to evaluate the performance of the consumer price inflation forecasts of the IMF.

Keywords

Cross-sectional dependence, Forecast evaluation, Hypothesis testing

Discipline

Econometrics | Economic Theory

Research Areas

Economic Theory

Publication

International Journal of Forecasting

Volume

40

Issue

1

First Page

202

Last Page

228

ISSN

0169-2070

Identifier

10.1016/j.ijforecast.2023.02.001

Publisher

Elsevier

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1016/j.ijforecast.2023.02.001

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