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Evaluating panel data forecasts under independent realization

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  • Greenaway-McGrevy, Ryan

Abstract

Independent realization is a commonly used shortcut for deriving forecast properties. It is also an unrealistic assumption in many empirical applications. In this paper we consider the effect of the assumption when deriving the properties of panel data forecasts. To do so, we derive and compare the asymptotic forecast loss of a set of vector autoregressions (VARs) under both independent and same-sample realization. We show that adopting the independent realization assumption can result in an overstatement of forecast loss when common forms of parameterized heterogeneity (such as fixed effects) are included in the VAR. Because these parameters are often used in dynamic panel forecasting applications, our results imply that the independent realization shortcut should only be used with caution when working with panel data.

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  • Greenaway-McGrevy, Ryan, 2015. "Evaluating panel data forecasts under independent realization," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 108-125.
    • Handle: RePEc:eee:jmvana:v:136:y:2015:i:c:p:108-125
    DOI: 10.1016/j.jmva.2015.01.004
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