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Forecasting with Panel Data

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type , Research , Preprint 01 Jan 2006 United Kingdom, United States Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

Authors: Badi H. Baltagi; Badi H. Baltagi;

doi: 10.2139/ssrn.1815319 , 10.1002/for.1047 , 10.2139/ssrn.2785252

handle: 10419/19654 , 2381/13787

Forecasting with Panel Data

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Abstract

AbstractThis paper gives a brief survey of forecasting with panel data. It begins with a simple error component regression model and surveys the best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper also surveys how these forecasts have been used in panel data applications, running horse races between heterogeneous and homogeneous panel data models using out‐of‐sample forecasts. Copyright © 2008 John Wiley & Sons, Ltd.

Countries

United Kingdom, United States

Related Organizations

Syracuse University
United States
Institute for the Study of Labor
Germany
University of Leicester
United Kingdom

Keywords

Forecasting,BLUP,Panel Data,Spatial Dependence,Serial Correlation, ddc:330, spatial dependence, forecasting, serial correlation, Panel Data, panel data, Spatial Dependence, heterogeneous panels, Panel, Zeitreihenanalyse, Serial Correlation, Prognoseverfahren, Mathematics, forecasting; BLUP; panel data; spatial dependence; serial correlation; heterogeneous panels., C33, Theorie, Forecasting, BLUP, jel: jel:C33

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	405
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 0.1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%