Nowcasting GDP Growth for Small Open Economies with a Mixed-Frequency Structural Model

Ruey Yau, C. James Hueng

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a mixed-frequency small open economy structural model, in which the structure comes from a New Keynesian dynamic stochastic general equilibrium (DSGE) model. An aggregation rule is proposed to link the latent aggregator to the observed quarterly output growth via aggregation. The resulting state-space model is estimated by the Kalman filter and the estimated current aggregator is used to nowcast the quarterly GDP growth. Taiwanese data from January 1998 to December 2015 are used to illustrate how to implement the technique. The DSGE-based mixed-frequency model outperforms the reduced-form mixed-frequency model and the MIDAS model on nowcasting Taiwan’s quarterly GDP growth.

Original languageEnglish
Pages (from-to)177-198
Number of pages22
JournalComputational Economics
Volume54
Issue number1
DOIs
StatePublished - 15 Jun 2019

Keywords

  • DSGE model
  • Kalman filter
  • Mixed frequency
  • Nowcasting

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