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
Citation
AKGUN, Oguzhan; PIROTTE, Alain; URGA, Giovanni; and YANG, Zhenlin.
Equal predictive ability tests based on panel data with applications to OECD and IMF forecasts. (2024). International Journal of Forecasting. 40, (1), 202-228.
Available at: https://ink.library.smu.edu.sg/soe_research/2674
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.ijforecast.2023.02.001