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Yang Liu
,
Di Yang
, and
Mr. Yunhui Zhao
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.
Ms. Marialuz Moreno Badia

Abstract

Drawing on an expanded data set covering emerging markets and low-income countries as well as advanced economies, this issue examines the extent and makeup of global debt and asks what role fiscal policy can play in facilitating the adjustment. The analytical framework explicitly models the interlinkages between private and public debt in analyzing the role of fiscal policy in the deleveraging process. Country case studies provide useful insights on what fiscal policy should and should not do to facilitate deleveraging while minimizing the drag on the economy.