Comparing forecasting performance with panel data

Ritong Qu

doi:10.1016/j.ijforecast.2023.08.001

Comparing forecasting performance with panel data

2024-07-01

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DOI：10.1016/j.ijforecast.2023.08.001

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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. (c) 2023 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Keywords:

Tests of equal predictive accuracy

Time clusters

Cross-sectional clusters

Term structure of forecast errors

Real GDP growth forecasts

Inflation forecasts

Comparing forecasting performance with panel data

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