Panel Forecasting with Asymmetric Grouping

The estimator relies on the observation that the bias-variance trade-off in potentially heterogeneous panel data may be different across individuals. Hence, the group of individuals used for parameter estimation that is optimal in terms of forecast accuracy, may be different for each individual. For a specific individual, cross-validation is used to determine the optimal individual-specific grouping. A simulated annealing algorithm deals with the combinatorial problem of group selection in large cross sections. A Monte Carlo study and two applications demonstrate the promising performance of our new estimator.

Participation

If you would like to participate in the seminar, please send an email to the secretariat of Econometrics, eb-secr@ese.eur.nl