How Did the Interest Rate Affect the Housing Prices - Dissertation Example

Part A - How did the interest rate affect the housing prices? Interest rates are defined as the interest paid to the lender for lending the money or in other terms it is the effective cost of borrowing money from lender. These rates are set by premier financial institutes of any country. For example in the UK, the base rate (repo rate) is set by the Monetary Policy Committee and the Bank of England while in the United States; the Federal Reserve sets the same Interest rates are set up after looking into several macroeconomic perspectives that affects the economy of a country. These rates determine the volume of economic activities within the different sectors of the economy Let’s take the example of housing market and understand what the impact of interest rates is over the housing market. In general perspective, the interest rates varies indirectly with housing prices. Any rise in the interest rates makes the market unattractive for the buyer buying the house and therefore demand falls which ultimately leads to falling house prices. On the other hand, any increase in interest rates will increase the monthly payments on a variable mortgage over the house Interest rates and housing prices Interest rate affects the value of income-producing real estate mostly as compared to any investment parameter/factor in the economy. Due to such greater degree of impact of interest rates on an individuals ability to purchase housing properties many people incorrectly assume that the only deciding factor in real estate valuation is the mortgage rate. However, mortgage rates are only one interest-related factor that influence the property values In developing countries US and UK, the rising interest rates have a big impact over the housing prices. Few years ago, the world has witnessed the global economic turmoil due to the high failures in relation to sub prime mortgages. This means that many homeowners have got a mortgage by borrowing a greater portion of their disposable income The relation between interest rates and housing prices is stronger at lower real interest rates, but even at low real rates, when time trend is included, prices seem to rise by x% as interest rates fall by much lower at y% point. The most common reason with regard to rising housing prices is the availability of easy credit, which took the form of high loan-to-value ratios, low interest rates and permissive approvals. These variables certainly affect housing prices Some of the exceptions to the case i.e. cases where the rising interest rates may not cause fall in house prices: Due to time lags: Suppose, someone have a house but any rise in interest rates is unlikely to make him/her sell the house, unless it becomes very serious. Generally a rise in interest rates will not reduce demand straight away Due to confidence: Suppose if the confidence level over the market is high, people may continue to spend money and respond to rising interest rates. This would lead to a fall in the savings ratio while the demand for housing doesn’t fall Due to real interest rates: The affordability of housing is majorly affected by the real interest rates. Suppose, if the interest rates are 9% but the inflation is 8%, the real interest rate is only 1%. In other terms, though the interest rates seem high, but in practices the real cost of borrowing is low Due to Other factors: Many a times, it depends on basic supply and demand analysis as well. Suppose, if there are severe supply constraints (like in the Great Britain) house prices may continue to rise, even though interest rates are higher Many a times some of the small developers and second-hand house owners may first reduce housing prices: Any increase in the down payment for the first house would also lead to increase in bank interest rates. This would lead to rise in the down payment pressure and interest costs on buyers Interest rates and impact on capital flows over housing market Since interest rates affects the capital flows, the demand and the supply for capital and investors required rates of ROI, interest rates drives property prices in a variety of ways. To understand how government-influenced interest rates, capital flows and financing rates affect property values, one should have a basic understanding of the income approach to real estate values. Although real estate values are influenced by the supply and demand for properties in a given locale and the replacement cost of developing new properties, the income approach is the most common valuation technique for investors. The income approach provided by appraisers of commercial properties and by underwriters and investors of real estate-backed investments is very similar to the discounted cash flow analysis conducted on equity and bond investments As for real estate, the changes in interbank lending rates either add or reduce the amount of capital available for investment. The amount of capital and the cost of capital affect demand, but also supply capital available for real estate purchases and development. For example, when capital availability is tight, providers of capital tend to lend less as a percentage of intrinsic value, or not as far up the "capital stack". This means that loans are done at lower loan to value ratios, thus reducing leveraged cash flows and property values These changes in capital flows can also have a direct impact on the supply and demand dynamics for property. The cost of capital and capital availability affect supply by providing additional capital for property development, and also affect the population of potential purchasers chasing deals. These two factors work together to determine property values Discount rates: The impact of rate of interests on housing price values can be seen in the derivation of discount or capitalization rates. The discount rate equals an investors total return requirements while capitalization rate can be viewed as an investors required dividend rate. Although risk premiums vary as a result of supply and demand and other risk factors in the market, discount rates will vary due to changes in the interest rates that make them up. When the required returns on the substitute or competing investments increase, the value of the real estate fall and vice versa In Nutshell: Many of the retail investors across geographies primarily homeowners, concentrate on changing mortgage rates because they have a direct influence on real estate prices. However, interest rates also affect the availability of capital and the demand for investment. These capital flows influence the supply and demand for property and, as a result, they affect property prices. In addition, interest rates also affect returns on substitute investments, and prices change to stay in line with the inherent risk in real estate investments. These fluctuations in required rates of return for real estate also differ during periods of destabilization in the credit markets. As investors forecasts variability in future rates or any increase in risk, risk premiums gets widen, which ultimately puts increased adverse pressure on property prices Multiple regression between housing prices and related factors Some of the economic fundamentals that underline the strong demand for houses are rapid economic growth, rising income levels, increasing employment and lower interest rates. These are being reinforced by accelerating net immigration, and are interacting with a relatively limited supply response in the short run, which has inevitably led to a driving up of house prices Here, it’s a hypothetical example of housing prices in a city Specification Dependent Variable Y: In order to obtain real house prices, nominal figures are adjusted using the CPI Index, with 1989 as the base year (1989 = 100). The approach used to calculate house prices is based entirely on lending agency activity First Independent Variable: Here, Completion in the market is chosen as the first independent variable. The level of house completions in the city has been declining. One would assume that with the level of house completions falling and demand rising that house prices would also rise. As a result of this, it can be expected that there exists an inverse correlation between house completions and the dependent variable, house prices Second Independent Variable : Mortgage rates is the second independent variable as they represent the recent trend in interest rates Third Independent Variable : The level of employment is the third explanatory variable, which has been chosen as a proxy for economic growth Omitted Variables: The independent variables that are omitted include net immigration, investment demand, the level of residentially zoned land and the length of the planning process. However, an attempt is placed to capture the effects of the independent variables impacting on “Y” which are not explained by Line of Best Fit From the estimates, a following line is constructed based on the following multiple regression models: Where: = Variation in observed explanatory variable, = Intercept Coefficient, = Explained Variation and = Unexplained Variable (attempt to capture omitted variables) The Least Square Model will yield a relationship between the variables by estimating the size and the sign of The Regression and Evaluation Using the Econometrics computer package “Microfit”, the line of best fit was as follows: = –147155.3 –3.6207 + 1935.4 + 168.3052 Independent Variable Coefficient T – statistic Probability Constant M –147155.3 –4.9576 0 –3.6207 –1.1144 .283 1935.4 1.7750 .096 168.3052 7.6435 0 Correlation Co-efficient The Correlation Co-efficient, R², is a measure of the relationship between ,. It takes on values of between 1, for a perfect fit, and 0, which indicates that there is no relationship between the dependent and independent variables. In this analysis, a correlation is found between the variables to be quite high at 87% (R² = .86989) Observing the high correlation of all the variables it would appear as if the model has very high explanatory powers. However, it is important to evaluate what the individual explanatory powers of on Y are, in case multicollinearity was undermining the high R² value. Let’s, return to the issue of multicollinearity Y Regressed on Independent Variable Coefficient T – statistic Probability Constant M 72850.1 4.5466 0 –3.9127 –. 91750 .372 R² = .047181 Y Regressed on Independent Variable Coefficient T – statistic Probability Constant M 86452.5 7.3855 0 –2399.5 –2.4668 .025 R² = .26359 Y Regressed on Independent Variable Coefficient T – statistic Probability Constant M –100001.8 –5.9072 0 135.8257 9.3899 0 R² = .83836 These individual results indicate that the independent variable, the level of employment, is having a more significant effect on Y variable, house prices, than the other two independent variables, house completions and mortgage rates Source Used for Dataset: http://www.tcd.ie/Economics/SER/ Possible Multicollinearity Multicollinearity is always a possibility in multiple regressions. It refers to the existence of more than one exact linear relationship among some or all of the explanatory variables of a regression model. The standard check for multicollinearity is to regress on and, and on. In this analysis multicollinearity is a possibility as the sign of variable changed from the multiple to the single regression. When regression of on is done, it is found that R² to be 0.63274. This is quite high for the two variables. The R² value for regressed on was 0.092794, which indicates a very low collinearity between these two variables. For regressed on, R² turned out to be 0.45776, which again indicates a moderate degree of co linearity between and. From these results, it can be concluded that the high R² value from regressed on , coupled with the changing sign, indicates significant multicollinearity between these two variables the existence of multicollinearity between and will result in these independent variables having very large variances and covariances, which makes precise estimation more difficult Result Analysis The line of best fit was as follows: = –147155.3 –3.6207 + 1935.4 + 168.3052 The and variables, undoubtedly have their anticipated negative correlation and positive correlation with house prices. However, the variable, mortgage rates, has a positive correlation in the multiple regressions, which proves that as mortgage rates increase, house prices will increase T-Statistic The t-statistic measures the ratio of the parameter estimate to the standard error - “an estimate of a parameter is statistically significant if the t-statistic associated with it. Hence, it was appropriate to reject, at a particular significance level, the Hypothesis test”. In the multiple regression case, neither or are statistically significant at the 5% or 10% significance level, therefore it is not possible to reject the null hypothesis that b1 = 0 and b2 = 0. In the simple regression case, is again not statistically significant at the 5% or 10% level, but statistically significant at both of these levels. In relation to, it is statistically significant in both the multiple regression and the simple regression case, at the 5% and 10% levels and even at the 1% level. The aforementioned multicollinearity is the main reason for and not being statistically significant. One of the main signals of multicollinearity is a high R² value, insignificant t-values and a significant F-value F-Statistic The F-test is a measure of the overall significance of the estimated regression model. It indicates whether all the variables in the equation together are significant. It is also a test of the significance of R². The F-statistic for the multiple regressions was 33.4276, with zero probability. Therefore it is statistically significant at the 10%, 5% and even the 1% significance level. This result indicates that house completions, mortgage rates and the employment level as explanatory variables for house prices are together statistically significant. Therefore, any hypothesis that this model has no explanatory power can be rejected, i.e. that = 0, = 0 and = 0. Part B - What drives overseas investors to invest in UK housing market? According to Mayfair Capital Investment, UK housing market is increasingly becoming attractive to the overseas investors. Also, CBRE estimates that almost 82% of all commercial property investors, who’ve put their money into London commercial property in the 3rd quarter of 2009, were foreign. The property consultants in the UK believes that while there has been a marked recovery in investment volumes and an improvement in yields since 2009, it is foreign investors who have dominated the London market, generating most of the new transactions This is not only because of the falling housing prices, which has seen a decline of as much as 45% in 2009, but also because sterling pound fell against the euro, the US dollar, and the yen. Thus, it is the fluctuations of currencies that made American, German, and Japanese investors return on the UK property market. Let us see how sterling pound was fluctuated w.r.t. USD and JPY over the past couple of years: Source: http://byline.timetric.com/2010/12/01/an-exchange-rate-boost-to-the-uk-housing-market/ Source: http://byline.timetric.com/2010/12/01/an-exchange-rate-boost-to-the-uk-housing-market/ Thus, we see that there is a considerable decline in the sterling’s value as compared to USD and JPY currencies. This resulted in making UK housing market more attractive to the foreign investors. As a result of this, a number of opportunity funds have been created recently, with an aim to invest into UK property over the coming years. For example, Mayfair Capital joined L&B Realty Advisors, property fund manager located in Dallas, TX, seeking to invest $250 million British property. BNP Paribas Real Estate claimed the opportunity fund it created has £5 billion to invest into UK property, while CBRE German funds hold €7.5 billion of cash to invest into British property. These funds are focused on prime commercial property, which has been hit the most by the economic downturn Some of the biggest deal held in the UK housing market by overseas investors include the £1.1bn sale of 50 per cent of Broadgate in the City by British Land, which was sold to the US private equity group Blackstone in Sep 2009. Also, South Korea’s state pension fund, in effect a sovereign wealth fund, paid £772m for HSBC’s Docklands headquarters in Oct 2009 “Overseas investors have been attracted to the London office market in increasing numbers during 2009 due to the sharp fall in capital values since 2007 and the weakness of sterling. An additional factor is that some foreign buyers are not constrained by debt, which has also worked to their advantage.” - Kevin McCauley, CB Richard Ellis’s head of central London research. Along with the weakening of sterling pound against USD and other currencies, another major driver for overseas investment in the UK’s housing market is the mature and stable legal system. As a result of this, the investors feel confident to get good return on their investments. According to Andrew Smith, Real Estate partner, the investment was mainly came from the Far and Middle East, and from Eastern Europe. Andrew said: "We’re seeing a lot of interest and investment from Singapore, Hong Kong, China and India, as well as from the Middle East and countries like Kazahstan. One contributing factor is that, unlike many other countries, our legal system is sound and fixed, protecting buyers. On top of that, property in the UK is seen as a substantial asset, akin to the likes of gold and we also have a recognized need for new, affordable housing, so the demand exists.” Further, according to 2011 research from property agent Jones Lang LaSalle, Asian investors are increasingly focusing on investing in the UK housing market, with an expected investment of over £52 billion. According to the latest industry reports, overseas investment in the UK housing market was nearly $13.9 billion in the first nine months of year 2010. The investment came primarily from the following investors: The sovereign wealth fund in Qatar – they purchased Harrods for £1.5 billion (or $2.5billion) Yet another sovereign wealth fund in Qatar – they agreed on paying over £448 million ($692 million) for a section of the booming retail section in London, namely Regent Street JPMorgan – invested £495 million ($740 million) into a building that became its new headquarters in central London Dutch and Canadian Retirement Funds spent £872 million ($1.3 billion) in order to purchase a section of the Westfield Stratford City mall. This prestigious sector is located directly next to the site for the 2012 Olympics Further, in 2010, London’s West End commercial property market has seen a high level of activity, particularly from foreign investor, with several landmark sales in the office and retail markets. For example, the year reported sale of Land Securities Park House development to a Qatari-backed investor for circa £250 million. However, there has been certain issue which has resulted in hindering the growth of the UK’s housing market. Firstly, with the onslaught of economic recession, banks in the UK were resistant to lend money, thus making the development in the UK’s property market more difficult and expensive. Also, land availability has been an issue in the UK’s market as the owners of potential development land became reluctant to put their land on the market when developers faces such a hard time of raising funds through conventional means References "How do Interest Rates affect the Housing Market. " Finance Blog. 24 June 2007. Web. 17 Apr 2011. http://www.mortgageguideuk.co.uk/blog/housing/how-do-interest-rates-affect-the-housing-market/ "Interest Rates vs. Home Prices." Seattle Bubble(2008):Web. 16 Apr 2011. http://seattlebubble.com/blog/2008/07/16/interest-rates-vs-home-prices/ Stammers, Robert. 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