Energy commodities and US housing: Long-run Price and volatility integration with comparative evidence from non-energy markets

This study investigates long-run price and volatility integration between U.S. regional housing markets and both energy and non-energy commodities. The analysis applies Fourier-augmented Toda-Yamamoto models to examine price transmission and Fourier-augmented causality-in-variance tests to assess volatility spillovers, conditioning commodity indexes on region-specific heating degree days to preserve long-run information while capturing smooth structural changes. After controlling for macroeconomic factors and weather-driven demand, the results show that oil remains integrated with housing prices and that oil-related volatility exhibits widespread, often bidirectional spillovers with housing markets-highlighting the central role of oil as both an input cost and a macro-financial barometer. In contrast, natural gas and coal display little evidence of persistent integration once weather demand and gradual shifts are accounted for, and their volatility spillovers are limited and region-specific. The non-energy results provide a comparative benchmark: industrial metals generate long-run integration in construction-intensive regions, agriculture primarily contributes through volatility associated with household-budget and income channels, and precious metals transmit state-contingent volatility consistent with safe-haven and portfolio behavior. Overall, persistent integration is strongest and most durable for oil, whereas other energy and non-energy commodities display more selective and region-specific linkages. These findings underscore the importance of regional policy on heating-fuel choices and the management of petroleum-linked costs, while offering guidance for investors seeking to hedge oil exposure and construction-input risk in rapidly growing housing markets.