Comparing forecasting performance with panel data

Ritong Qu, Allan Timmermann and Yinchu Zhu

International Journal of Forecasting, 2024, vol. 40, issue 3, 918-941

Abstract: We develop new methods for testing equal predictive accuracy for panels of forecasts, exploiting information in both the time-series and cross-sectional dimensions of the data. We examine general tests of equal forecasting performance averaged across all time periods and individual units, along with tests that focus on subsets of time or clusters of units. Properties of our tests are demonstrated through Monte Carlo simulations and in an empirical application that compares International Monetary Fund forecasts of country-level real gross domestic product growth and inflation to private-sector survey forecasts and forecasts from a simple time-series model.

Keywords: Tests of equal predictive accuracy; Time clusters; Cross-sectional clusters; Term structure of forecast errors; Real GDP growth forecasts; Inflation forecasts (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:40:y:2024:i:3:p:918-941

DOI: 10.1016/j.ijforecast.2023.08.001

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