Housing Boom and Headline Inflation : Insights from Machine Learning /

Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-risin...

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Bibliographic Details
Main Author: Liu, Yang
Other Authors: Yang, Di, Zhao, Yunhui
Format: Journal
Language:English
Published: Washington, D.C. : International Monetary Fund, 2022.
Series:IMF Working Papers; Working Paper ; No. 2022/151
Subjects:
Online Access:Full text available on IMF
Description
Summary:Inflation has been rising during the pandemic against supply chain disruptions and a multi-year boom in global owner-occupied house prices. We present some stylized facts pointing to house prices as a leading indicator of headline inflation in the U.S. and eight other major economies with fast-rising house prices. We then apply machine learning methods to forecast inflation in two housing components (rent and owner-occupied housing cost) of the headline inflation and draw tentative inferences about inflationary impact. Our results suggest that for most of these countries, the housing components could have a relatively large and sustained contribution to headline inflation, as inflation is just starting to reflect the higher house prices. Methodologically, for the vast majority of countries we analyze, machine-learning models outperform the VAR model, suggesting some potential value for incorporating such models into inflation forecasting.
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Physical Description:1 online resource (45 pages)
Format:Mode of access: Internet
ISSN:1018-5941
Access:Electronic access restricted to authorized BRAC University faculty, staff and students