The differential effects of exchange rate fluctuations on local housing price growth: evidence from Australia

ABSTRACT

We investigate whether real exchange rate fluctuations contribute to the fluctuations in housing prices differently across local housing markets through the differential compositions of immigrants. We first develop a new measure of the immigrant-weighted local real exchange rate, which varies across areas and over time within Australia. Using this measure and a fixed-effect instrumental variables approach, we find that the growth in local real exchange rate positively affects housing price growth. This positive relationship is mainly driven by urban metropolitan areas.

KEYWORDS:

• housing prices
• exchange rate
• immigration

JEL:

• F31
• F22
• R31

ACKNOWLEDGEMENTS

We thank the two anonymous reviewers and editor for their constructive comments. We are also grateful to Juyoung Cheong, Qingyuan Du, Claudio Labanca, Russell Smyth and the seminar participants at Monash University for helpful comments and suggestions. We thank Lisa Chan, Arek Chouzadjian and Laure Pavaday for preliminary data work that eventually led to this paper. This paper uses data supplied by the Securities Industry Research Centre of Asia–Pacific (SIRCA) on behalf of RP Data.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. According to the Australian Bureau of Statistics (2016), over half of permanent migrants in Australia are homeowners (about 1 million people), and there are 8.8 million occupied private dwellings (https://profile.id.com.au/australia/population). Thus, permanent migrants own at least 11% of all occupied private dwellings in Australia.

2. Slightly more than half of all immigrants came from 10 countries: England (2.9%), China (2.7%), India (2.6%), New Zealand (2.2%), Philippines (1.2%), Vietnam (1%), South Africa (0.8%), Italy (0.7%), Malaysia (0.7%) and Sri Lanka (0.6%). Roughly 21% of residential property owners in Australia are immigrants (Baxter & McDonald, 2004).

3. Due to the fact that some LGA boundaries change between census years, we construct and use an LGA classification that allows us to follow LGAs consistently over time. The raw data have 625 LGAs available in 1991, 671 LGAs in the period 1996–2001 and 544 LGAs in the period 2006–16.

4. We focus on census years because ABS community profiles are only available at quinquennial frequency. As the Penn World Table data are available at an annual frequency and our LRER measure can be constructed at an annual frequency, we also estimate reduced-form specifications using annual frequency data and find a significant positive relationship between the LRER fluctuation and housing price growth. The results are shown in Table A1 in Appendix A in the supplemental data online.

5. We include in our analysis the 29 countries of origin that are consistently reported across census years. We omit those grouped under the other category in the construction of the weights.

6. Table A2 in Appendix A in the supplemental data online finds no significant effects of LRER on local macro-variables, such as unemployment rate and average individual income. The results indicate that these macro-variables are not likely the channels through which LRER affects housing price growth.

 

Additional information

Funding

Liang Choon Wang received funding support from the Department of Economics at Monash University [research support fund number 1758054].