Journal of Business Cycle Research

, Volume 14, Issue 1, pp 127–141 | Cite as

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

Research Paper

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 

JEL Classification

C38 C53 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of LeipzigLeipzigGermany
  2. 2.CESifoMunichGermany

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