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Term Structure Learning and Inflation Predictability: A Dynamic Approach

conference contribution
posted on 2023-09-25, 13:35 authored by Fei- (Phoebe) GaoFei- (Phoebe) Gao, Desi ArisandiDesi Arisandi, TzeHoung Lee

This paper examines the efficacy of nominal yield curve term structure on inflation predictability incorporating economic variables expressed in the form of the Quantity Theory of Money. We document a positive predictability of the term structure in predicting the current reported inflation rate (Nowcast) and one-month ahead (Forecast) reported inflation rate in the US from 2018 to 2022. However, this level of predictability is not constant across different inflation regimes. The significant predictors in the low inflation regimes deviate to those in the high inflation regimes, suggesting that economic indicators should be considered dynamically. Lastly, we made use of nonparametric method (K-Nearest Neighbors) for predicting extreme inflation regimes in consideration of their pattern recognition ability at higher dimensions, as well as ability to handle nonlinearity.

History

Journal/Conference/Book title

Asian Finance Association 2023 Annual Meeting, 26-27 June 2023, University of Economics Ho Chi Minh City (UEH University), Vietnam

Publication date

2023-06-26

Version

  • Published

Corresponding author

phoebe.gao@singaporetech.edu.sg

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