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Forecasting aggregates using panels of nonlinear time series

Dennis Fok, Dick van Dijk () and Philip Hans Franses

No EI 2004-44, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

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.

Keywords: business cycle; data aggregation; multi-level models; nonlinearity; panel of time series (search for similar items in EconPapers)
JEL-codes: C23 C51 C53 E32 (search for similar items in EconPapers)
Date: 2004-11-05
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