Australian Housing Market Booms: Fundamentals or Speculation?*

Abstract

This paper investigates the presence of housing bubbles in Australia at the national, capital city and local government area (LGA) levels. We control for housing market demand and supply fundamentals using the technique of Shi (2017), and employ the recursive evolving method proposed by Phillips et al. (2015a,b) for the detection of explosive bubbles. While the national‐level analysis suggests a short‐lived bubble episode (2017Q3) over the entire sample period from 1999 to 2017, the results from the capital‐city‐level data reveal substantial heterogeneity across cities, with only short‐lived and isolated bubbles identified for Sydney and Melbourne during the recent rapid housing price expansions from 2013 to 2017. The LGA‐level analysis suggests that only a small percentage of LGA housing markets are identified to be speculative in Sydney and Melbourne from 2013 to 2017.

Diagnosing housing fever with an econometric thermometer

“…Our findings are compared with those reported in the recent work of Shi et al. (2020, SRW), which computed the fundamental component using the structural procedure on the same data set. The two approaches disagree on the bubble periods.…”

“…It is standard in the literature (e.g., Campbell et al., 2009; Shi, 2017; Sun & Tsang, 2013) to assume that the log gross return to housing equals the sum of the real interest rate ($$i_{t}$$) and a time‐varying risk premium ($$\varphi _{t}$$), that is, $$$$\begin{equation} \gamma _{t}=i_{t}+\varphi _{t}. \end{equation}$$$$The risk premium is further assumed to take the simple form $$$$\begin{equation} \varphi _{t}=\varphi +\varepsilon _{t}, \end{equation}$$$$where $$\varphi$$ is the long‐run risk premium and the zero mean error term $$\varepsilon _{t}$$ captures short‐term fluctuations brought by either market fundamentals or bubbles (Shi, 2017; Shi et al., 2020). Under these two assumptions, the fundamental component $$F_{t}$$ can be written as $$$$\begin{equation} F_{t}=c+\mathcal {R}_{t}-\mathcal {I}_{t}-\mathcal {U}_{t}, \end{equation}$$$$where …”

“…where 𝜑 is the long-run risk premium and the zero mean error term 𝜀 𝑡 captures short-term fluctuations brought by either market fundamentals or bubbles (Shi, 2017;Shi et al, 2020). Under these two assumptions, the fundamental component 𝐹 𝑡 can be written as…”

Government-Made House Price Bubbles? Austerity, Homeownership, Rental, and Credit Liberalization Policies and the “Irrational Exuberance” on Housing Markets

“…Most existing econometric studies locate speculative boom periods in the early 2000s, when capital gains taxes were reformed (Shi et al, 2016;Abelson and Chung, 2005), and again in the mid-2010s (Shi et al, 2020), also driven by mortgage and unemployment rates (Wang et al, 2019), with bubble likelihood higher in the capital cities. The Australian case is special in that, fueled by financial liberalization (Ryan-Collins and Murray, 2023), neither the Global Financial Crisis nor the post-COVID-19 interest-rate shock have brought national price trends down.…”

Diagnosing Housing Fever with an Econometric Thermometer

“…where ϕ is the long-run risk premium and the zero mean error term ε t captures short-term fluctuations brought by either market fundamentals or bubbles (Shi, 2017;Shi et al, 2020). Under these two assumptions, the fundamental component F t can be written as…”