This study aims to examine whether the newly constructed price conflict index (PCI) has predictive value for housing price volatility across the 50 US states and Washington D.C. This study would determine whether price conflict significantly predicts volatility after controlling for market momentum and state-level economic conditions, to test whether a PCI-augmented model improves out-of-sample forecasting accuracy relative to standard benchmarks and to identify the transmission channels driving this relationship, and inform investors, policymakers and other stakeholders about housing market risk.
This study uses quarterly panel data from 1976 to 2023 across all 50 US states and Washington D.C. A newly constructed PCI is used as a predictor of housing price volatility, with models controlling for historical market momentum and state-level economic conditions. Predictive performance is evaluated using out-of-sample forecasting tests across semiannual, annual and biennial horizons, benchmarked against baseline models. Panel regression analysis is then applied to confirm the nationwide significance of the PCI–volatility relationship and to identify the primary transmission channels linking price conflict to housing volatility.
PCI significantly and positively predicts housing price volatility across most US states, even after controlling for historical market momentum and state-level economic conditions. Out-of-sample tests show that PCI-augmented models outperform standard benchmarks across semiannual, annual and biennial forecast horizons. Panel regressions confirm a robust, statistically significant nationwide relationship between price conflict and housing price volatility. Wages and energy prices emerge as the primary transmission channels through which price conflict influences volatility. Finally, the results indicate that PCI is a meaningful and consistent leading indicator of housing market instability across diverse state-level conditions.
This study introduces a novel PCI as a forward-looking indicator of housing price volatility, linking public discourse to housing market instability. Its value lies in improving out-of-sample forecasting across multiple horizons and holding robustly across nearly all US states, which offers investors and policymakers a practical early-warning tool for housing market risk.
