Real house prices are directly determined by the willingness of households to pay for (and willingness of builders to supply) a constant-quality house. Changes in the quantity of housing demanded will affect real prices only to the extent that the long-run housing supply schedule is positively sloped (Richard K. Green and Panic H. Hendershott, 1993). In this paper, data from year 2006 to year 2009 are used, it has shown that how different macro-economic factors are affecting the house price of UK. Because of the analysis purpose, all the quarterly data(GDP, Household Consumption Expenditure, Gross National Disposable Income, Gross Savings) has been transformed to monthly by cubic spline interpolation. Data are collected from International Financial Statistics, The Times Index, The Economist Index, Economic Trends (ONOs).
Objective of the report:
The main purpose of this paper is to analyze the changes in house prices over the last three years by identifying factors over the period that have caused the demand and supply curve to shift and predict what is likely to happen to the market over the next year or two.
Discussion on related economic principles, concepts and theories and analysing each of the factors affecting the house prices and concurrently presenting the supporting evidence of the current issues;
Because of the limitation, we have collected monthly data from the first month of 2006 till February 2009, then find out the predicted value or forecasting value of those years through Ordinary Least Square method of Linear regression analysis;
Then determine the percentage of forecasting error for different cases comparing with the actual data of house prices;
Economic Review:
Competitive markets demonstrate how the factors of demand and supply determine the equilibrium prices. The market demand function for house is the statement of the relationship between the quantity demanded and all factors that affect this quantity:
Qx= α1+ α2x2+ α3x3+ α4x4+α5x5+ α6x6 ----------------------------(1),
Where, Qx = Quantity Demanded, X2 = Income, X3 = Related Goods Prices X4 = Tastes or Preferences, X5 = No. Of Buyer X6 = Expectations
Analyze the changes in house prices over the last three years:
Construction of Demand Curve and Supply Curve:
These are the reason for which Demand curve will shift. From the websites of Global Property Guide and UK house price, the following data for price per square meter are collected
sq. M
House Price
45
11,072
80
11,060
120
12,290
200
17,826
Therefore the demand Schedule would be:
Quantity Demanded (House Sq. m.)
Price (House per Sq. M)
45
246
80
138
120
102
200
89
Supply Curve:
Supply function for House is statement of the relationship between the quantity supplied and all factors affecting quantity supplied:
Qx= α1+ α2x2+ α3x3+ α4x4+α5x5 ----------------------------(1)
Where, Qx = Quantity Supplied
X1 = Technology
X2 = Input prices (Cost of other items related to build a house)
X3 = Number of Sellers
X4 = Expectation of prices in future (builder's perspective)
These are the reasons for which supply curve will shift. Thus we find out the equilibrium of the house price.
Estimation:
Demand estimation techniques could classified into two main categories:
Qualitative methods: Marketing research, Consumer interviews and market experiments.
Quantitative methods: Statistical methods and forecasting techniques such as regression analysis, game theory and linear programming.
Regression analysis is a technique that describes the way in which one important economic variable(house price) is related to one of more of other economic variables. When a statistical relation between two economic variables is not known with certainty and must be estimated. The most common means for doing so is to gather and analyze historical data. Time series of data is a periodic sequence of data on an economic variable such as price, cost, income.
Specifying the Form of Regression Model:
The first procedure in this step is to specify variables to be included in the regression model;
Collect accurate data;
Determine the form of the regression model; The broad appeal of linear functions stems from the fact that the OLS technique could be used to estimate the regression model coefficient.
House prices are affected by a combination of supply and demand factors(variables):
Inflation:
Inflation is the sustained increase in the average cost of goods and services. It is measured in an annual percentage rate that shows how much less one dollar will buy this year as opposed to previous years. Demand-pull inflation happens when there is an abundance of money and not enough product or services to meet the demand of that money. Cost-push inflation happens when companies' costs go up and they can't keep their level of profit so they increase their prices and pass it on to the consumer. When the inflation starts to happen, we know that prices go up. This is true in the housing industry too. When inflation gets to the point that the general public can no longer afford to buy a house or anything else they need to survive, then the housing prices start to come down. If you can see inflation happening, then buying a house could be an excellent move. If inflation is at an all time high in real estate, you should wait to buy a house. As inflation affects lives, people need to sell their homes, they will be forced to sell for less than it was previously worth. As less homes are put on the market, the competition for the buyer goes up and the prices are reduced. Since there are not as many buyers who can afford to buy a reduced price house during an inflationary period, the housing market slows down quite a bit. As inflation increases and forces the prices of real estate down, even investors are hesitant to buy. This is because it take too long to sell the homes. If you have the money to hold an investment property for a year or so, than buying during this time is good because prices are low. Real estate is one of the first products to react to a growing economy, so as soon as things start to get better, the prices will start to go up again. However, this scenario will occur when you know there is a fixed rate mortgage to protect you from higher interest rates.
Sustained inflation is essentially a monetary phenomenon. For the price level to continue to rise period after period, it must be accommodated by an expanded money supply.
Causes of Inflation:
Demand-pull inflation is inflation initiated by an increase in aggregate demand.
This inflation can be cut by reducing interest rates, an increase in the quantity of money, an increase in quantity of money, an increase in government expenditures, a tax cut, an increase in exports or an increase in investment stimulated by an increase in expected future profits.
Cost-push, or supply-side, inflation on the other hand is inflation caused by an increase in costs. This situation occur in which output(area or the builder is falling) is falling at the same time that prices are rising(like we can see it in 2009 and afterwards).
Cost shocks are bad news for policy makers. The only way to counter the output loss is by having the price level increase even more than it would without the policy action(Carl Case, Ray Fair, 2002). This happens just at the end of 2009 as the inflation started to increase after falling down till 1 percent in the mid of the same year.
If the Government tries to prevent crowding out by keeping the interest rate unchanged like April 2008 till September and October of the same year and also in the mid of the last year, it will increase the money supply like it happens in late September 2008 and late 2009 more than 400 percentage change in M4 from the month it has actually started and consequences of this is D curve will shift farther and farther to the right. The result is a sustained inflation, perhaps hyperinflation and this result in increase in the price of the house.
Money Supply, M4: M4 is any monetary aggregate is a kind of cash and money (that are derived from money), but are different in liquidity degree. Monetary aggregates are calculated on the basis of the world's money supply amount. Consequently, any rate's increase leads automatically to the rise of inflation. This indicator is measured either in percents or directly in money's amount that are denominated in national currency.
M4 = M1 + the most part of bank deposits of private sector + deposits of money market instruments; the aggregate M4 characterizes the liquidity of private sector.
It is M4 that is considered to be the most interesting for the British pound, because the currency reacts greatly to any changes in this aggregate more than in the other monetary aggregates (Source: Forex Trading Currency)
Interest rates:
The demand for most goods declines when the cost of complementary goods rise. Therefore, one would expect the market price of housing to decrease because of weakened demand as the cost of mortgage financing increases(Jack C. Harris, 1989). However, in our monthly data for the year 2006 till the mid of 2007, we have noticed that home prices rose rapidly at that time when mortgage interest rates soared. After 2007, although interest rates further decline to less than 1 percent yet house price has appreciated. Various explanations of the rise emphasize the role of supply restrictions from government regulation, demand stimulus via government incentives, and expansionary monetary and fiscal policy. Here, for the purchasing of durable goods, we should ignore the nominal costs and take into consider the real cost of the buyer. The real cost of housing includes the effects of prospective appreciation returns and tax benefits. During the period of price appreciation, the real cost was declining, making housing actually less expensive. Therefore, housing consumers were responding to declining real costs rather than rising nominal costs. From the investment standpoint, a rising price is often a positive indicator of an asset's attraction in the market.
So initially, an increase in Interest rate causes the demand curve and supply curve to shift left.
Interest rates affect the cost of paying for a mortgage. Interest rates are very important as mortgage repayments are usually the biggest part of a homeowner's monthly spending. People on fixed rate mortgages will be insulated from fluctuating rates for 2-10 years. Therefore changes in interest rates can have a time lag of up to 18 months before their full effect is noted on demand for housing (Source: UK House Price). So, in the long run expected increase in interest rate will cause the demand curve to shift right. However it is ambiguous or difficult to determine what will happen to supply curve.
Technology:
Buyers are highly sensitive to interest rates that is why reduction in this factor and developments in the financial markets (e.g. new mortgage products, the structure of mortgage products: floating or fixed), will dramatically increase willingness to buy houses. Different tax rates, subsidies, and demographic developments further complicate the picture.
Economic Growth / Real income / GDP:
Rising incomes enable people to spend more on buying a house. Therefore rising incomes enable house prices to rise. However, the ratio of house prices to income can vary considerably. For example, between 1995 and 2007, the ratio of house prices to incomes have increased significantly. If the economy goes into a recession and unemployment rises, the demand for buying houses would fall significantly.(Source: Nationwide, UK House Price)
An increase in Income, Wealth, Population will shift the demand curve to the right.
Some major trends emerge:
•Strong economic growth tends to spur demand for housing
•Low interest rates encourage buyers
•Floating rate mortgage market structures are associated with volatile housing markets
•Cycles are important, because buyers are influenced by recent price movements
•The Bank of England set base rates and these usually affect all commercial rates. However, sometimes the Bank of England cut interest rates, but, commercial banks don't pass these cuts onto consumers. In the first half of 2008, the Bank of England cut rates by 0.5% from 5.5 to 5.0%, but the cost of mortgages is still rising.
Consumer confidence:
During times of high consumer confidence, people are more willing to take out risky mortgages to be able to buy a house.(Source: UK house Price)
Availability of Financing:
With the deregulation of the banking sector, a rise in the number of mortgage products is observed. Products such as interest only, self certification mortgages and mortgages up to 6 times income have enabled people to get more mortgages, thereby increasing demand for housing. However, during the credit crunch of 2008, the number of mortgage products on offer fell due to a shortage of finance in the money markets.
An increase in the availability of mortgage finance shift the demand and supply curve to shift right.(Source: UK House Price)
Demographic factors
There has been a rising number of households in the UK. The number of households can rise faster than the population if the average family size decline and there are more single people living alone.
Demand for housing in the UK has been increasing for various reasons such as:
â- an increase in divorce rates
â- an increase in net immigration from Eastern Europe.
â- Increase in life expectancy and more old single people
â- Children leaving home early
â- Less marriage
(Source: UK House Price)
Speculation
An increasing number of property investors buy houses to try and make both capital gains and income from renting. This buy to let investor is typically more volatile, they will buy when house prices are rising and sell when the market appears to turn. This makes house prices more volatile because speculators will buy in a boom and sell in a bust.(Source: UK House Price). For this report, this factor is encountered with the past stock price index.
Wealth.
It is also becoming more common for parents to lend children a deposit to help get their first house. That is why house price to income ratio is really high.
Unemployment
Low unemployment is often associated with rising demand for houses.
Supply side Factors
In the short run supply of housing is fixed because it takes time to build houses. Therefore in the short run demand affects prices more than supply. However if the supply of housing is inelastic then an increase in demand will lead to a big increase in price. (Source: UK House Price)
Long Run Supply
In the long Run the supply of housing is affected by many factors:
Availability Government permission. This is difficult to obtain in rural areas. The more the restrictions the supply curve will shift more to the left.
Opportunity cost for builders e.g. for this paper we have included Short run T-bill. Increase in cost will shift the supply curve to the left and thus price will increase and quantity will also decrease if there is no change in demand curve. Because of bad quality the House may have dumped. Thus price will increase and quantity will decrease.
An increase in the cost of building new houses will shift supply to the left. In the UK, it is argued there is a significant shortage of housing is this explains why house prices have risen much faster than inflation and earnings. However, in the US, the supply of housing increased in the period upto 2008 and therefore, the excess supply and falling demand led to a big fall in demand. However, it is important to note that house prices can still fall, even if there is a shortage of supply. In 1992, house prices in London fell over 20%, even though we can say supply is inelastic. A shortage of supply just means they will be on average higher. It doesn't mean they are incapable of falling.(Source: UK House Price)
Historical Data of all the variables are given below:
Results of the Analyzing of the model:
By conducting a regression analysis, we found out that coefficient of variation of the model is less than 10%. Therefore the model would be useful for prediction purpose. Moreover from the ANOVA table, F-Test statistics is 237.615 which is significant at 1% significance level. Therefore, null hypothesis that all the coefficient value is zero is rejected as P-value is significant. There is at least one independent variable has relationship with the dependent variable which can be used as predictor to predict the price.
P-value suggests that Inflation rate, Consumer Price Index, Unemployment rate, Household Consumption Expenditure, Gross National Disposable Income are significant in the model at any level of significance that is an increase or decrease in these factors lead the change in the House Price in a significant way than all other factors in the model.
P-value suggests that Gross Savings, Average Monthly wages, and Stock Price Index are significant in the model at 5% level of significance.
P-value suggests that Treasury Bill Rates are significant in the model at 10% level of significance.
P-value suggests that Lending rates, Export and Import Prices, Industrial production, Aggregate Money Supply(M4) and GDP are not significant in the model at any level of significance.
Model's R-Square = 0.993865416, implies that 99.38% of the variability can be explained by the model that is the model can predict the House price to a great extent. But as it is observed that more the variables are added in the model R-square gives more value. So the better indicator would be adjusted R-square which is 98.9% that is pretty much similar to the unadjusted one.
Forecasting Error:
We already have some more collection of Actual Price from the month March 2009 till January 2010, which will be used to find out the Forecasting error.
Now, Forecasting the House Price for 1 year ahead:
(Chart1 in the appendix)
Conclusion:
House prices in the UK began recovering in early 2009, after two years' pause. By Q3 2009 the average price of UK houses was only 3% down from a year earlier (-4.4% in real terms). The quick (and surprising) recovery of house prices has mainly been due to low interest rates, but also to lack of supply, as many homeowners have taken their properties off the market, to wait for improved conditions.
It is unclear whether the recovery will continue in autumn and winter, when the housing market typically slows. The economy is likely to contract by as much as 4.4% during 2009. There is rising unemployment, and credit conditions are tight.
The big hope is that construction spending for the 2012 London Olympics may help propel the economy and the housing market to recovery. Government has spent massively to boost economy In late 2008, to help the housing market, the government suspended stamp duty on houses costing less than £175,000 (extended for three months until December 31, 2009). In One year from 2010 to 2011, the house price will increase by 2.07% with forecasting error of 0.059% and it happens due to a significant change in the variables Inflation rate, Consumer Price Index, Unemployment rate, Household Consumption Expenditure, Gross National Disposable Income.
BIBLIOGRAPHY
Jack C. Harris (1989)"The Effects of Real Rates of Interest on Housing Prices", Journal of Real estate Finance and Economics, 2:47-60
Cagan, Phillip (2002), "The influence of interest rates on the duration of business cycles," Essays on interest rates, NBER.
Karl Case, Ray Fair (2002) "Principles of Economics", Prentice Hall Busines Publish.
Darby, M. R. (1975) "The Financial and Tax Effects of Monetary Policy on Interest Rates", Economic Inquiry, Vol.13, pp. 266-276.
Duck, N. (1993), "Some International Evidence on the Quantity Theory of Money", Journal of Money, Credit and Banking, Vol.25, pp.1-12.
Engle, R. and C. Granger 1987, "Cointegration and error correction representation: estimation and testing", Econometrica, Vol. 55, pp. 251-276.
Engsted, T. (1995), "Does the Long-Term Interest Rate Predict Future Inflation?", Review of Economics and Statistics, Vol. 77, pp. 42-54.
Evans, L. T., Keef, S. P. and J. Okunev (1994), "Modelling Real Interest Rates", Journal of Banking and Finance, Vol.18, pp.153-165.
Gary R. Evans, (1999), Demand and Supply Curve Effect, Journal of Finance, Vol. 50, pp. 3-10
Fama, E. and M. R. Gibbons (1982), "Inflation, Real Returns, and Capital Investment", Journal of Monetary Economics, Vol.9, pp. 297-324.
Fama, E.F. (1975), "Short Term Interest Rates as Predictors of Inflation", American Economic Review, Vol.65, pp.269-282.
Fisher, I. (1930), The Theory of Interest, New York: Macmillan.
Huizinga, J. and F. S. Mishkin (1986), "Monetary Policy Regime Shifts and the Unusual Behavior of Real Interest Rates", Carnegie-Rochester Conference Series on Public Policy, Vol.15, pp.151-200.
Kandel, S., A. Ofer and O. Sarig (1996), "Real Interest Rates and Inflation: An Exante Empirical Analysis", Journal of Finance, Vol.51, pp.205-225.
Modigliani, F. and R. Cohn (1979), "Inflation, Rational Valuation, and the Market", Financial Analysts Journal, Vol. 35, pp. 24-44.
Tanzi, V. (1980), "Inflationary Expectations, Economic Activity, Taxes and Interest Rates", American Economic Review, Vol. 70, pp.12-21.
Tobin, J. (1965), "Money and Economic Growth", Econometrica, Vol.33, pp.671-684.
Tobin, J. (1969), "A General Equilibrium Approach to Monetary Theory", Journal of Money, Credit and Banking, Vol.1, pp.15-29.
Websites: Forex trading, currency. 2009 <http://forex-trading-currency.org/m4-money-supply/>.
Richard Tejvan Pettinger, "Factors That affect House Prices in UK", 2010<http://www.ukhouseprices.co.uk/housing_market/factors_affecting_prices.html>
