Implementing an Approximate Dynamic Factor Model to Nowcast GDP Using Sensitivity Analysis

Pablo Duarte and Bernd Süssmuth ()
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Bernd Süssmuth: University of Leipzig

Journal of Business Cycle Research, 2018, vol. 14, issue 1, No 5, 127-141

Abstract: Abstract Dynamic factor models based on Kalman Filter techniques are frequently used to nowcast GDP. This study deals with the selection of indicators for this practice. We propose a two-tiered mechanism which is shown in a case study to produce more accurate nowcasts than a benchmark stochastic process and a standard model including extreme bounds fragile indicators. Our pseudo-ex-ante forecast nearly measures up to the genuine ex-ante forecast of the European Commission.

Keywords: Dynamic factor; Kalman Filter; Extreme bounds analysis (search for similar items in EconPapers)
JEL-codes: C38 C53 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s41549-018-0026-0

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