Housing Boom and Headline Inflation: Insights from Machine Learning

Housing Boom and Headline Inflation: Insights from Machine Learning
READ MORE...
Volume/Issue: Volume 2022 Issue 151
Publication date: July 2022
ISBN: 9798400218095
$20.00
Add to Cart by clicking price of the language and format you'd like to purchase
Available Languages and Formats
English
Prices in red indicate formats that are not yet available but are forthcoming.
Topics covered in this book

This title contains information about the following subjects. Click on a subject if you would like to see other titles with the same subjects.

Inflation , Economics- Macroeconomics , Economics / General , Housing Price Inflation , Rent , Owner-Occupied Housing , Machine Learning , Forecast , machine-learning model , machine learning method , housing boom , D , forecasting result , Inflation , Housing prices , Housing , Consumer price indexes , Global , Europe , Australia and New Zealand , North America , Caribbean , VAR model

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.