Pesaran, M. H., Pick, A., Timmermann, A.
Forecasting with panel data: estimation uncertainty versus parameter heterogeneity
CWPE2219
Abstract: We provide a comprehensive examination of the predictive accuracy of panel forecasting methods based on individual, pooling, fixed effects, and Bayesian estimation, and propose optimal weights for forecast combination schemes. We consider linear panel data models, allowing for weakly exogenous regressors and correlated heterogeneity. We quantify the gains from exploiting panel data and demonstrate how forecasting performance depends on the degree of parameter heterogeneity, whether such heterogeneity is correlated with the regressors, the goodness of fit of the model, and the cross-sectional (N) and time (T) dimensions. Monte Carlo simulations and empirical applications to house prices and CPI inflation show that forecast combination and Bayesian forecasting methods perform best overall and rarely produce the least accurate forecasts for individual series.
Keywords: Forecasting, Panel data, Heterogeneity, Pooled estimation; Forecast combination
JEL Codes: C33 C53
Author links: M. Hashem Pesaran
PDF: https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe2219.pdf 
Open Access Link: https://doi.org/10.17863/CAM.83982
