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

Equal Predictive Ability Tests Based on Panel Data with Applications to OECD and IMF Forecasts