Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Rental yields are widely used by investors, central bankers, researchers, and policy makers to assess and detect disorders in housing markets. This paper proposes a framework to measure rental yields across the distribution, time and space thus providing a comprehensive picture of housing markets. The two-step procedure based on hedonic quantile regression and propensity score matching is designed to fundamentally control for differences in house characteristics. The methodology is applied to micro-data on house transactions and asking rents in Sydney, Australia, between 2004 and 2014. The paper finds large temporal and spatial variation in rental yields, decreasing yields when moving from the low end of the distribution to the top end, and systematically larger yields when restricting the analysis to houses bought-to-let.