Template-Type: ReDIF-Paper 1.0
Author-Name: Nibbering, D.
Author-Name-Last: Nibbering
Author-Name-First: Didier
Author-Name: Paap, R.
Author-Name-Last: Paap
Author-Name-First: Richard
Author-Person: ppa494
Title: Panel Forecasting with Asymmetric Grouping
Abstract: This paper proposes an asymmetric grouping estimator for panel data
 forecasting. The estimator relies on the observation that the bias-
 variance trade-off in potentially heterogeneous panel data may be dif-
 ferent 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, the estimator uses cross-validation to estimate the bias-variance of all individual groupings, and uses the parameter estimates of the optimal grouping to produce the individual-specific forecast. Integer programming and screening methods deal with the combinatorial problem of a large number of individuals. A simulation study and an application to market leverage forecasts of U.S. firms demonstrate the promising performance of our new estimators
Length: 38
Creation-Date: 2019-09-01
File-URL: https://repub.eur.nl/pub/119521/ei2019-30.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI-2019-30
Keywords: Panel data, forecasting, parameter heterogeneity
Handle: RePEc:ems:eureir:119521