House price synchronization across the US states: The role of structural oil shocks

Abstract

This paper analyzes the impact of disentangled oil shocks on the synchronization in housing price movements across all the US states plus DC. Using a Bayesian dynamic factor model, the house price movements are decomposed into national, regional, and state-specific factors. We then study the impact of oil-specific supply and demand, inventory accumulation, and global demand shocks on the national factor using linear and nonlinear local projection methods. The impulse response analyses suggest that oil-specific supply and consumption demand shocks are most important in driving the national factor. Moreover, as observed from the regime-specific local projection model, these two shocks are found to have a relatively stronger impact in a bearish rather than a bullish national housing market. Our results have important policy implications.

On the Link between House Prices and House Permits: Asymmetric Evidence from 51 States of the United States of America

“…Such heterogeneity is prominent not only in terms of consumption smoothing behavior, but also with regards to housing return predictability. Sheng et al (2021) also uses state level data to assess the impact of oil shocks on the synchronization in housing price movements across all the US states plus Washington DC. They find that "oil-specific supply and consumption demand shocks are most important in driving the national factor.…”

The non-linear response of US state-level tradable and non-tradable inflation to oil shocks: The role of oil-dependence

“…The oil independent Texas and Utah would respond differently to oil shocks compared to more oil-dependent states and Alaska, which produces substantially more oil than consumed. Several studies support this rationale in studying the impact of oil shocks on real housing returns (Sheng et al, 2021; and consumption at the state level in the US.…”

Do expansionary and contractionary monetary policy have a symmetric impact on housing permits across the USA?

“…1. Similarly, Gupta et al (2021) explore the role of uncertainty in predicting the synchronization of house prices across the states in the USA. Sheng et al (2021) study the impact of oil shocks on the synchronization in housing price movements across all the US states plus DC. Researchers also use vector autoregression or cointegration models with a spatial dimension in a panel setup to explore housing market dynamics in the USA at the state level (Miller and Peng, 2006; Holly et al , 2010; Kuethe and Pede, 2011; Zhu et al , 2018).…”