Template-Type: ReDIF-Paper 1.0
Author-Name: Fok, D.
Author-Name-Last: Fok
Author-Name-First: Dennis
Author-Name: van Dijk, D.J.C.
Author-Name-Last: van Dijk
Author-Name-First: Dick
Author-Person: pva27
Author-Name: Franses, Ph.H.B.F.
Author-Name-Last: Franses
Author-Name-First: Philip Hans
Author-Person: pfr226
Title: Forecasting aggregates using panels of nonlinear time series
Abstract: Macroeconomic time series such as total unemployment or total industrial production concern data which are aggregated across regions, sectors, or age categories. In this paper we examine if forecasts for these aggregates can be improved by considering panel models for the disaggregate series. As many macroeconomic variables have nonlinear properties, we specifically focus on panels of nonlinear time series. We discuss the representation of such models, parameter estimation and a method to generate forecasts. We illustrate the usefulness of our approach for simulated data and for the US coincident index, making use of state-specific component series.
Creation-Date: 2004-11-05
File-URL: https://repub.eur.nl/pub/1797/ei200444.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2004-44
Classification-JEL: C23, C51, C53, E32
Keywords: business cycle, data aggregation, multi-level models, nonlinearity, panel of time series
Handle: RePEc:ems:eureir:1797