Structural modeling and forecasting using a cluster of dynamic factor models

Christian Glocker and Serguei Kaniovski

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a modeling approach involving a series of small-scale dynamic factor models. They are connected to each other within a cluster, whose linkages are derived from Granger-causality tests. This approach merges the benefits of large-scale macroeconomic and small-scale factor models, rendering our Cluster of Dynamic Factor Models (CDFM) useful for model-consistent nowcasting and forecasting on a larger scale. While the CDFM has a simple structure and is easy to replicate, its forecasts are more precise than those of a wide range of competing models and those of professional forecasters. Moreover, the CDFM allows forecasters to introduce their own judgment and hence produce conditional forecasts.

Keywords: Forecasting; Dynamic factor model; Granger causality; Structural modeling (search for similar items in EconPapers)
JEL-codes: C22 C53 C55 E37 (search for similar items in EconPapers)
Date: 2020-07
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-mac and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:101874

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