This study aims to examine the causal impact of COVID-19 stringency measures on U.S. housing markets, focusing on house price returns. By analyzing the entire pandemic period, it provides a comprehensive assessment of government interventions’ effects on regional housing dynamics.
Using the Oxford Stringency Index, this study applies a causal framework with difference-in-differences, propensity score matching and generalized propensity score techniques on data from 51 U.S. states (2020–2022), controlling for income, unemployment, political tendency and COVID-19 cases.
Results reveal a nonlinear, inverse U-shaped relationship between stringency measures and house price returns. Moderate restrictions supported housing markets, while excessive stringency had adverse effects. House price returns rise from 2.787% at the 25th percentile to 4.253% at the 75th percentile of policy stringency but decline to 0.696% at the 99th percentile. These findings underscore the impact of government interventions on real estate markets during crises.
Focusing on U.S. data may limit the generalizability of findings to other countries.
Stringency policies aim to protect lives, but their application varies by state due to differing public beliefs. Understanding their impact on housing markets allows states to take preemptive measures. Data-driven policies help real estate stakeholders anticipate market shifts and adapt strategies during crises.
Public health policies can inadvertently affect housing demand. This study highlights the need for equitable policy frameworks to mitigate unintended consequences during crises.
Unlike prior research on specific periods or regions, this study applies advanced causal inference to comprehensively assess COVID-19 stringency measures’ impact on U.S. housing markets throughout the pandemic.
