How Predictable? Rent Growth and Returns in Sydney and Melbourne Housing Markets

56 Pages Posted: 2 Feb 2017

See all articles by Glenn Otto

Glenn Otto

UNSW Australia Business School, School of Economics

Nigel Stapledon

UNSW Australia Business School, School of Economics

Date Written: January 31, 2017

Abstract

We construct rent-price ratios for houses and units in 82 local government areas in the Sydney and Melbourne markets for the period 1985/86-2015. Using this annual data we employ long-horizon regression techniques and find that rent-price ratios (i.e. rental yields) have predictive content for both future real housing returns and future growth rates of real rents. However rents and returns have greater predictability in Sydney than in Melbourne. Using a variance decomposition for the rent-price ratio implied by the present-value model, we find that variation in rental yields of units in Sydney is almost fully accounted for by expected changes in future rent growth and returns. There appears to be no role for rational bubbles in influencing the prices of Sydney units. In contrast – on average – lesser portions of the variance in rental yields on houses in Sydney (two thirds) and Melbourne (one third) and units in Melbourne (60 percent) is explained by expected future returns and rents. Evidently there is scope for (stochastic) rational bubbles to have affected these markets. Our results point to an important difference between the behaviour of residential housing markets and stock markets. In the stock market, current changes in dividend-price ratios do not appear to reflect important variations in future dividend growth. Our results for Sydney and Melbourne suggest that current changes in rent-price ratios do signal future changes in rent growth.

Keywords: Rent-Price Ratio, Housing Returns, Rent Growth, Long Horizon Regression

JEL Classification: C22, G17, R31

Suggested Citation

Otto, Glenn and Stapledon, Nigel, How Predictable? Rent Growth and Returns in Sydney and Melbourne Housing Markets (January 31, 2017). UNSW Business School Research Paper No. 2017-01. Available at SSRN: https://ssrn.com/abstract=2910110 or http://dx.doi.org/10.2139/ssrn.2910110

Glenn Otto (Contact Author)

UNSW Australia Business School, School of Economics ( email )

High Street
Sydney, NSW 2052
Australia

Nigel Stapledon

UNSW Australia Business School, School of Economics ( email )

High Street
Sydney, NSW 2052
Australia

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