House Prices from Magazines, Realtors, and the Land Registry

2018

Using the aggregate and disaggregate dataset of various types of housing loan, this study examines the dynamic relationship between residential property prices, housing loan, construction output, and interest rate. Focusing on the aggregate data, it is noted that housing loan, construction output, and interest rate have significant and positive elasticities towards house prices in both short and longterm. The aggregate loan model indicates that about nine quarters or two years are required for full adjustment of house prices after experiencing a shock. Across the loan categories, first, the empirical analysis indicates that there is still a strong demand and potential opportunities for affordable properties. Second, homebuyers who purchase high-end properties will still borrow. Third, there is a significant and positive impact of interest rate on house prices in both shortand long-run, however, albeit a low percentage. The results of the error correction model imply the house prices...

BIS Papers, 2012

Overview and background Professor Timothy Riddiough, colleagues from the BIS, IMF, central banks, regulatory agencies and academia, ladies and gentlemen. Good morning. Welcome to this workshop. We received more than 60 papers from many countries, with submissions from central banks, public agencies, supranational organisations, and academic institutions. I would like to thank everyone for their support. The very good response reflects the strong interest in this growing and important area of research. Property market volatility poses financial stability challenges The theme of this workshop is property markets and financial stability. Maintaining stability in property markets has been challenging for authorities across Asia in the last few years. Between 2005 and 2008, property prices in Asian economies rose rapidly. This reversed during the Global Financial Crisis, as the downturn affected incomes, confidence and the availability of financing. However, as the Asian economies rebounded, so did property prices, reaching record levels in a number of countries. Property markets are prone to cycles, in part because supply is inelastic in the short term. This cyclical behaviour is exacerbated by several factors. First, property is both a consumption good and an investment good. While rising prices would normally mean lower consumption, expectations of further price increases could induce more investment demand. Price momentum may escalate as valuations are usually set with reference to the latest transacted prices. Second, housing markets tend to be highly leveraged. Most homebuyers borrow to finance their purchases, sometimes up to 80% or 90% of the value of the property. And because mortgage loans are collateralised and have historically low default rates, banks are prepared to lend at high loan-to-value ratios. In a rising market, banks are willing to lend more as the value of the collateral increases. Easier credit may contribute to further increases in house prices. But this feedback loop quickly reverses when prices are falling. Lenders tighten underwriting standards. Existing housing loans with small equity buffers may slip into negative equity and some borrowers may be forced to sell. This puts further downward pressure on prices. Third, housing generally accounts for a significant proportion of households' balance sheets and banks' loan portfolios. In Singapore, property forms almost 50% of household assets while housing loans account for three quarters of total household debt. They also make up about 17% of bank lending to non-bank borrowers. As a result, adverse developments in housing markets can have a material impact on household wealth and the health of the banking system. This could then dampen household demand and banks' ability to supply credit, and in turn economic growth. Further, construction accounts for as much as 10% of

2014

We use the Johansen co-integration test and the Vector Error Correction Model (VECM) to analyze data on housing loan, housing price, interest rate and GDP from 19911Q to 20102Q to particularly ascertain the extent to which housing loan affects house prices in Singapore. The results show the existence of a long run co-integration among housing loan, house price, interest rate and GDP. Furthermore, housing loan is found to be positively correlated with house price and GDP but negatively correlated with interest rate in the long run. There seems to be no correlation between housing loan and house price in the short run. Moreover, a change in housing loan per se does not affect house price, neither does a change in house price per se affect housing loan in the short run. Thus, while there is long run equilibrium among housing loan, house price, interest rate and GDP, the causality direction between housing loan and house price is somewhat obscure. This implies that targeting housing loa...

2014

The increase in household debts in Malaysia which has escalated to about 86% of total GDP is deemed to be at worrying stage as it may in turn trigger another financial crisis. Thus, the aim of this study is to examine the increase in household debts and its relation to GDP, interest rate and house price via time series techniques. Data collected from Datastream and monthly statistical bulletin span from 1999 to 2014 on quarterly basis. The results show that there is a cointegrating long run relation between household debt, house prices, GDP and interest rate. The analysis indicates that although household debts could not be influenced by the changes in GDP, lending rate and house price in the short run, it could be affected by house price movement in the long run. As there is a positive significant relationship between house price and household debts, it implies that, in the long run horizon, the increase in household debts is due to the increase in house price. Although both GDP and lending rate are found to be endogenous, we still believe that the movement in lending rate and GDP (as a proxy to income) may affect the household debts. Thus, extra care shall be taken by the policy maker for any decision to increase the lending rate in particular as the lending rate is deemed to be one of the macroeconomic policy instruments which may have significant influence on household income. As the lending rate is deemed endogenous, the policy maker should strengthen prudential measure in order to curb the increase in household debts. Shortening the loan tenure, tightening credit policy by implementing responsible and selective lending, higher debt service ratio, strengthening the risk management of banking institutions are amongst the measures that might facilitate the policy maker to combat the rising household debts. Additionally, as the result found that the house price is the main indicator that affects the household debt in the long horizon, the policy maker should take an initiative to control the property price in order to mitigate any bubble in asset price.

MATEC Web of Conferences, 2016

Housing finance is one of the factors that contribute in the overall economy growth of the country. The purpose of this paper is to analyse the relationship of housing finance variable and the macroeconomic variables in Malaysia. By adopting time series technique of Vector Auto regression (VAR) and Impulse Response to determine the dynamic relationship between the macroeconomic and housing finance variable. The cointegration result shows that there exists a long run relationship between the macroeconomic variable and housing finance variable. The finding from impulse response function indicates that Gross Domestic Product (GDP) response positively to the Primary Mortgage Market (PMM), which shows that during the good economy there are more housing loan extends by the banking institution. Meanwhile, interest rate response negatively to Secondary Mortgage Market (SMM), which implies that during the financial crisis, more housing loan sold to the Secondary Mortgage Market as one of the measure by the government to increase liquidity in banking institutions. As a conclusion, there is presence of relationship between the variable which change in one variable will affect the other variable in the long run.

observed property prices are assembled from an unobservable 'real' property price linked to macroeconomic conditions and the interest rate environment, and a noisy component given by market sentiment. Between January 1993 and July 2007 all IPD index logarithmic returns were positive. This long series of positive returns created an illusion among investors. It implied that they did not give proper consideration to macroeconomic evidence. That changed fundamentally in 2008. During the subprime crisis investor behavior changed from illusion to disillusion and the market prices occasionally fell well below the level indicated by fundamental economic considerations. IPD property derivatives can, according to the author, be used for risk management purposes. Investors have access to Eurex futures that can be utilized to hedge out property risk and avoid the consequences of price crashes. Giovanni Dell'Ariccia and Deniz Igan, IMF Research have authored chapter 3: "Dealing with real estate booms". Until the global financial crisis, the main policy tenet in dealing with a real estate boom was one of 'benign neglect'. It was considered better to wait for the bust and pick up the pieces than to attempt to prevent the boom. The crisis challenged this view. But preventive policy action is difficult to implement. The authors conclude that policy efforts should focus on booms that are financed through credit and where leveraged institutions are directly involved. Macroprudential tools (such as limits on loan-to-value ratios) are the best candidates to deal with real estate booms as they can be aimed directly at curbing leverage and strengthening the financial sector. Cycles are a common feature of real estate markets. Stylized facts suggest that the longer and higher prices go up, the more they will come down. Housing cycles are closely intertwined with credit and business cycles. Peaks and troughs are not far from each other. There are significant differences across countries. Legal and institutional structures matter. In order to improve policy options, the quality of empirical data should be heightened. Real estate is an important storage of wealth in the economy. Monetary policy is a blunt instrument for the task at hand. It is difficult to use fiscal tools. So, macroprudential regulation in the form of higher capital requirements, dynamic provisioning and limits on loan-to-value and debtto-income ratios are the most promising options.

The main purpose of this study is to measure the relationship between macroeconomic variables and the housing price. This paper examines empirically whether the increasing trend in the Malaysian housing price is related to changes in the gross domestic product (GDP), population, inflations rate, costs of construction, interest rate and real property gains tax (RPGT). The paper is exploratory in nature. The empirical data were collected from Valuation and Property Services Department of the Ministry of Finance Malaysia from 2001 to 2010. The paper provides empirical results that the gross domestic product (GDP), population and RPGT are the key determinants of housing prices. However, changes in housing prices may not necessarily be influenced by the gross domestic products (GDP), population and RPGT in Malaysia. The general finding of this paper strongly suggests that housing bubbles in the Malaysian residential property market are becoming bigger and stronger. The paper is useful for speculators, investors and buyers to know which factors to account for in housing investment decision. This paper can serve as a guide for the government in stabilizing the residential housing price in Malaysia.

center for Financial Institutions Working …, 1999

Journal of the Asia Pacific Economy, 2020

The continued rise in house prices has sparked increasing interest in housing affordability in Malaysia. Middle-income-earning buyers, who fear that house prices may increase to a level beyond their future financial capacity, took on excessive leverage and overextended their current financial capacity. This increases their probability of default, which is unfavourable to the banking industry providing these mortgages. This study examined the impact of rising house prices on housing affordability in three urban regions in Malaysia and found that house prices in these cities, especially landed houses, were unaffordable for middleincome-earners. This study also examined the impact of a collateral valuation loss to the banking system from the potential decline in house prices, by employing a solvency stress test. The study found that the banking system remained fairly capitalised to survive a mild single-risk factor financial shock of the equivalent of house price declines in the 1997 Asian Financial Crisis.

In Indonesia, the annual residential property credit growth rates have been observed of between 30% and 40% in 2011. This raises the question as to whether this strong credit growth is likely to result in a credit boom that would be detrimental to the economy. Or can it be explained by a catching-up process that is normal for countries with a low level of financial intermediation? With a view to answering this question, we use complementary approaches, based on both deviations from long-term trends and econometric regressions. In the first approach, we consider current credit growth in relation to its long-term trend. A "credit expansion" is termed a "credit boom" if the credit growth exceeds its long-term trend by above a confidence interval. Calculations show that there appears to have been a credit boom in the credit for upper class housing. This statistical approach is useful in that it compares recent and historical developments, but it does not take economic fundamentals into account. In the second approach, which seems to be more appropriate, we assess the "normal"level of credit with regard to fundamentals. The results show that the credit growth remains below equilibrium levels estimated for the majority of sub sectors. This appears to indicate that a catching-up process is underway. However, the catching-up has already occurred in upper class housing sector. In this respect, recent credit growth largely also exceeds estimates in the case of upper class housing which suggests a credit boom.