Panel Forecasting with Asymmetric Grouping

Didier Nibbering and Richard Paap

No EI-2019-30, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

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

Keywords: Panel data; forecasting; parameter heterogeneity (search for similar items in EconPapers)
Pages: 38
Date: 2019-09-01
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:119521

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