Market Sensitivities and Growth Differentials Across Australian Housing Markets

TL;DR

This paper develops a three-factor model to analyze regional Australian housing market growth, distinguishing between national trends, resource-driven cycles, and amenity-driven cycles, providing insights into growth differentials and their stability.

Contribution

It introduces a novel three-factor level model that decomposes regional house price growth into national, resource-driven, and amenity-driven components, enabling better interpretation of regional growth dynamics.

Findings

Market betas are stable across major economic shocks.

Mining and Lifestyle spreads are stationary and widen forecast uncertainty.

Regional growth patterns are explained by their sensitivities to national and cyclical factors.

Abstract

Australian house prices have risen strongly since the mid-1990s, but growth has been highly uneven across regions. Raw growth figures obscure whether these differences reflect persistent structural trends or cyclical fluctuations. We address this by estimating a three-factor model in levels for regional repeat-sales log price indexes over 1995-2024. The model decomposes each regional index into a national Market factor, two stationary spreads (Mining and Lifestyle) that capture mean-reverting geographic cycles, and a city-specific residual. The Mining spread, proxied by a Perth-Sydney index differential, reflects resource-driven oscillations in relative performance; the Lifestyle spread captures amenity-driven coastal and regional cycles. The Market loading isolates each region's fundamental sensitivity, beta, to national growth, so that a city's growth under an assumed national change is calculated from its beta once mean-reverting spreads are netted out. Comparing realised paths to these factor-implied trajectories indicates when a city is historically elevated or depressed, and attributes the gap to Mining or Lifestyle spreads. Expanding-window ARIMAX estimation reveals that Market betas are stable across major shocks (the mining boom, the Global Financial Crisis, and COVID-19), while Mining and Lifestyle behave as stationary spreads that widen forecast funnels without overturning the cross-sectional ranking implied by beta. Melbourne amplifies national growth, Sydney tracks the national trend closely, and regional areas dampen it. The framework thus provides a simple, factor-based tool for interpreting regional growth differentials and their persistence.