Determinants of residential house prices in Australia By
Determinants of residential house prices in Australia By Sudharshan Reddy Paramati Dr Rakesh Gupta Prof Eduardo Roca Department of Accounting, Finance & Economics, Griffith Business School, Griffith University, Nathan Campus, Brisbane, Queensland, Australia 4111
Objective of the Study The objective of this study is to investigate the potential determinants of residential house prices in Australia by taking into account of consumer confidence index, household loans & advances, FDI and GFC.
Motivation The significant amount of literature argues that there is a strong evidence of linkage between residential house prices and macroeconomic fundamentals. However, the macroeconomic factors that determine the residential house prices varies from country to country and time to time. We therefore aim to understand the factors that are contributing for rising residential house prices in Australia.
Motivation Housing is a special type of asset that has a dual role as a consumption and an investment good. Therefore, it is an interest for every individual to have their own house as it is serving them for multiple purposes. The rise of residential house prices in Australia is becoming a growing concern among the individuals and policy makers.
Motivation It is claimed that Australians are the richest people in the world due to their extensive ownership of properties (Credit Suisse, 2014). The fifth annual study by the Swiss bank of global wealth trends found the median Australian adult was worth more than $US 225, 000 ($258, 000) in June, well ahead of the second wealthiest population on this measure, the Belgians, at $US 173, 000. They were followed by the Italians, French and British, all at around $US 110, 000. Only 6 per cent of Australians have wealth below $US 10, 000, compared with 29 per cent in the United States and 70 per cent for the world as a whole.
Motivation Household wealth in Australia is heavily skewed to "real assets" – essentially property – which average $US 319, 700 per household, or 60 per cent of gross assets. This is the second highest in the world after Norway. Real estate is the primary asset of Australian households. Australians have $5. 6 trillion tied up in the property market. In comparison with superannuation funds are worth about $1. 8 trillion and the share market is about $1. 6 trillion. Australians are one of the top in the World in terms of residential mortgages. This motivates us to examine the factors that are driving house prices in Australia.
Motivation This analysis is important for the policy makers’ standpoint as well as individuals. This will help them to understand the potential factors that are determining the residential house prices in Australia.
Literature Review Australian perspective: Bourassa and Hendershott (1995) found that Australian capital city real house prices are driven by the real wage income and the growth in population. Tu (2000) also showed that the real weekly earnings, nominal mortgage rates, unemployment rates and housing construction activities are the key factors affecting the Australian housing market.
Literature Review Australian perspective: Abelson et al. (2005) also offered the evidence of unemployment rate, mortgage rate, equity prices and the housing stock are negatively related to Australian house prices, while positive relationships are demonstrated for the disposable income and Consumer Price Index (CPI) in the long run. Stubbs (2005) also described that interest rate is the prime concern of property investors in Australia, implying that it is the main factor in driving the housing prices.
Literature Review Regional Australian perspective: Luo et al. (2007) examined the causality linkages between Victorian residential price and macroeconomic variables. They found that the housing price in Victoria is Granger caused by the mortgage rate, weekly earning and unemployment rate. However, the sub period analysis also reveals that the relationships are instable and varied from time to time. Karantonis and Ge (2007) focuses on the Sydney housing market and demonstrated that the real household income, dwelling completions, speculative investment and real interest rate are the driving forces of housing price in Sydney.
Research Gap: Previous studies have explored the impact of macroeconomic factors on housing prices in Australia and failed to address the impact of consumer confidence index, FDI, household loans and GFC on house prices. Therefore, in this study we aim to address the impact of consumer confidence index, FDI, household loans & advances and GFC along with macroeconomic fundamentals on house prices in Australia. To the best of our knowledge, this is the first study to address all of these issues.
Research Question What factors determine the residential house prices in Australia
Nature of Data and Sample Size Sample size: 3 rd Quarter of 2003 to 4 th Quarter of 2013. All the required data has been collected from Bloomberg. All the variables are seasonally adjusted to overcome from seasonal fluctuations All the variables are converted into natural logarithms before the commencement of analysis
Methodology Descriptive Statistics Unit Root Tests ADF PP Unconditional Correlations Pearson’s Correlation FMOLS To overcome from the presence of endogeneity in the regressors and to account for serial correlation, we apply Fully Modified Ordinary Least Square (FMOLS) method which is proposed by Philip and Hansen (1990).
2003 Q 3 2003 Q 4 2004 Q 1 2004 Q 2 2004 Q 3 2004 Q 4 2005 Q 1 2005 Q 2 2005 Q 3 2005 Q 4 2006 Q 1 2006 Q 2 2006 Q 3 2006 Q 4 2007 Q 1 2007 Q 2 2007 Q 3 2007 Q 4 2008 Q 1 2008 Q 2 2008 Q 3 2008 Q 4 2009 Q 1 2009 Q 2 2009 Q 3 2009 Q 4 2010 Q 1 2010 Q 2 2010 Q 3 2010 Q 4 2011 Q 1 2011 Q 2 2011 Q 3 2011 Q 4 2012 Q 1 2012 Q 2 2012 Q 3 2012 Q 4 2013 Q 1 2013 Q 2 2013 Q 3 2013 Q 4 Performance of indicators over the time 2, 50 2, 00 1, 50 1, 00 0, 50 0, 00 RHPI FDI loans per capita CCI REER
Long-run Relationship (FMOLS) Variables Model 1 Coefficient t Statistic Model 2 Prob. Coefficient t Statistic Model 3 Prob. Coefficient t Statistic Prob. Per Capita Income 0. 724 3. 389*** 0. 002 0. 753 3. 521*** 0. 001 1. 097 5. 330*** 0. 000 Consumer Confidence 0. 194 3. 188*** 0. 003 0. 213 3. 767*** 0. 001 0. 298 5. 697*** 0. 000 FDI 0. 003 0. 457 0. 651 0. 003 0. 449 0. 657 0. 003 0. 436 0. 666 Lending Rates 0. 484 6. 332*** 0. 000 0. 435 8. 605*** 0. 000 0. 296 6. 845*** 0. 000 Loans 0. 173 2. 633** 0. 013 0. 175 2. 641** 0. 013 0. 297 4. 990*** 0. 000 Inflation 0. 102 5. 626*** 0. 000 0. 099 5. 501*** 0. 000 0. 062 3. 701*** 0. 001 GFC 0. 036 2. 062** 0. 048 0. 047 3. 443*** 0. 002 0. 018 1. 419 0. 165 REER 0. 375 4. 776*** 0. 000 0. 357 4. 655*** 0. 000 Unemployment 0. 072 0. 854 0. 400 C 5. 360 2. 815*** 0. 008 6. 211 3. 709*** 0. 001 9. 713 6. 235*** 0. 000 R squared 0. 966 0. 952
Long-run Relationship (FMOLS) Variables Model 4 Coefficient t Statistic Model 5 Prob. Coefficient t Statistic Model 6 Prob. Coefficient t Statistic Prob. Consumer Confidence FDI 0. 165 2. 752** 0. 010 0. 215 4. 672*** 0. 000 0. 191 3. 075*** 0. 004 0. 005 0. 775 0. 444 0. 005 1. 074 0. 291 0. 003 0. 403 0. 690 Lending Rates 0. 365 4. 075*** 0. 000 0. 266 4. 977*** 0. 000 0. 247 3. 010*** 0. 005 Loans & Advances Inflation 0. 212 3. 401*** 0. 002 0. 181 3. 446*** 0. 002 0. 203 2. 943*** 0. 006 0. 092 4. 717*** 0. 000 0. 072 4. 429*** 0. 000 0. 078 3. 598*** 0. 001 GFC 0. 027 1. 444 0. 159 0. 033 2. 764*** 0. 009 0. 059 3. 802*** 0. 001 REER 0. 290 3. 170*** 0. 003 0. 216 2. 979*** 0. 006 0. 246 2. 423** 0. 021 Unemployment 0. 104 1. 192 0. 242 GDP 0. 655 3. 295*** 0. 003 1. 183 5. 375*** 0. 000 1. 317 3. 307*** 0. 002 12. 293 3. 429*** 0. 002 Employment Population C R squared 15. 847 3. 188*** 0. 969 0. 003 9. 852 5. 628*** 0. 976 0. 000 0. 969
Results FMOLS: Positive impact: Per capita income, consumer confidence index, loans, employment, population, inflation, GFC, REERs, and GDP have the positive impact on house prices and are statistically significant. Negative impact: Both lending rates and unemployment have negative impact on the residential house prices and are statistically significant.
Results FMOLS: No impact: FDI inflows have no impact on house prices in Australia
Conclusion Our empirical results show that the residential house prices are positively and significantly driven by per capita income, consumer confidence index, household loans and advances, inflation, employment, GDP, REERs, and population. Further, results indicate that lending rates and unemployment are negatively and significantly affecting residential house prices. Our analysis also reveals that the inflow of FDI has no impact on residential house prices. These results suggest that among all the factors; per capita income, consumer confidence, household loans and REERs have substantial impact on residential house prices.
Conclusion Our findings are consistent with previous studies e. g. Abelson et al. (2005). Who argues that unemployment rate and mortgage rate have negatively impact on Australian house prices, while disposable income and inflation have positive impact in the long run. However, our study is significantly different from previous studies as we take into account of consumer confidence index, household loans and advances, FDI and GFC.
Contributions To the best of our knowledge this is the first study to examine the determinants of residential house prices in Australia by taking into account of consumer confidence index, household loans & advances, FDI and GFC. Findings of this study have important policy and practical implications. For the policy makers standpoint it would be clear to know what factors are driving the house prices and could allow them to monitor house prices by controlling the factors which are driving. Similarly, it would also help the individuals to understand the driving factors and can take appropriate decisions by observing the factors which are influencing the house prices in Australia.
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