The technique of correlation measures the strength of the association between the variables. ‘7 Fig 1. 3 illustrates a positive correlation result indicating a close trend line between price and disposable income which suggests that the association is very strong.X-axis is the disposable income the independent variable and Y-axis is the house price dependant variable. `the variable we are trying to predict is the dependent variable while we are using as a basis for prediction is the independent variable illustrates the linear regression results which are derived from AHP (average house price the dependent variable) and RDI (real disposable income independent variable.
The equation of the slope indicates that the average growth of house price is 17. 2% per year and the forecast as to when DI reaches 15,000 the AHP would be 167,200. Table 1. 2 illustrates that the real interest rate is very much determined upon the calculation of the RPI inflation in relation to the interest base rate. For example year 2000 shows RPI of 3.0% and interest base rate 6% which results to a 3% actual rate for that year and 1995 shows 3. 5% RPI and 6.
5% base rate resulting to actual rate of 3%.In order to keep the actual rate low there has to be an increase in base rate to counter for the high inflation. However if the real rates are the same during the course of many years, this does not mean that you will be paying the average rate over that period, as the base and inflation rate will be high or low. Although the fundamentals are the same, mortgage lending is different, compared with the inflation rate.
In fact due to slightly higher inflation rate in 1995 it was more likely that home owners were paying slightly more than what they were in 2000. ( ) ‘The basic idea of regression is prediction, with the simplest case being that of predicting one continuous variable from another. ‘ 9 In other words linear regression is used to make predictions about a single value. Simple linear regression involves discovering the equation for a line that most nearly fits the given data. That linear equation is then used to predict values for the data.It is clearly understood that if we take the analysis of the DIPH, this shows that during the period of 1990 – 2000 the disposable income per head has increased over the years, which results in a greater spend value therefore an increase in house prices, as more properties are on the market. Due to this the summary output shows Pearson correlation efficient (r) has an increase from 87. 4% to 90.
7% and the coefficient of determination has increased from 0. 77% to 0. 83% for the 10-year term.
Disposable income and year together now contribute 82% to the average house price leaving 18% unexplained.Therefore an additional variable contributes to the improving of the regression equation. This means the regression equation should be more accurate in predicting AHP for a given year and disposable income. A hypothesis test is an unproved proposition to explain certain fact or observation. It is not a prediction itself but will allow making prediction of the relationship between the AHP and DI in this test.
`An hypothesis is a prediction of the relationship between an independent variable and dependent variable in an experiment.`The null hypothesis, H0 represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. The alternative hypothesis, H1, is a statement of what a statistical hypothesis test is set up to establish. ’11 Ho there is no relation between AHP & DI and economist cannot predict house price movements. Ha there are relations between AHP & DI & economist can predict future house price movement.
The critical value has already been calculated in the summer work out sheet and the significant value is 0. 003. The test statistic is however highlighted also in the disposable income as 4. 157 as illustrated in fig 1. 6. When the significant value is < 0.
5 then we would reject the null hypothesis as there is no sufficient evidence to support Ho, consequently rejecting Ho. As a result of the hypothesis test there is a relation between house price and disposable income and economist can predict house price movements.When the property has a value after considering the type, age & location there are various factors that would cause the average house price to increase and decrease and they are as follows: inflation; interest Rates; unemployment; disposable income; affordability ‘The traditional way of explaining inflation has been to treat it as the result of excessive demand, i.
e. , of excess demand pulling prices up. The value of aggregate supply and demand must be equal. ‘The rise of interest rates reduces the demand for housing which will ease the house price inflation reducing the average house price as seen on table 1.
1, where the interest increased to 6. 3 and the AHP decreased to 65,267. When interest rates rise, this causes AD (aggregate demand) to shift to the left due to the decrease in demand.”The fall in interest rates can also be expected to ease the financial constraints on the personal sector a little and the saving ratio may gradually begin to drift downwards, although there is unlikely to be a sharp turnaround until lower interest rates have been sustained for some time. ’13 When table 1. 2 is analysed it can be seen that the real for each year between 1990 and 2000 has been calculated. During the year 1995 and 2000 the real rate was 3.0.
Although the fundamentals are the same mortgage lending is different compared with inflation, this does not make it more affordable.Inflation can be caused by various reasons such as high oil prices, when the UK joined the EEC, war in other countries affecting UK food and retail price and high demand for housing etc. `Monetary and fiscal policies have succeeded in lowering inflation in industrial countries but the broader challenge of macroeconomic stabilization remains in two important respects. One is minimizing boom and bust cycles in economic activity and their disruptive effects on the financial system.The other is to keep at bay inflationary pressures while also preventing the emergence of its converse namely, generalised price deflation. ’14 There are three types of inflation: menu cost inflation which involves adjusting price list or labels associated with cost; productions that are related to the constant rising cost; and finally inflation that is created by continual rise in aggregate demand.
15 Through the fiscal or the monetary policies the government can try to and control inflation by increasing or decreasing interest rates and reducing low unemployment etc.’Monetary policy is not well equipped alone to deal with regional asset price booms. Fiscal and regulatory policies thus have a potentially important role to play. ’16 In spite of this, there are some factors that are beyond the governments control, such as increase in oil prices, war in other countries which affects the UK food and retail prices. Consequently these type of events can make it more difficult to control inflation, as was seen previously with the Kuwait war in 1990, where inflation was at 9. 5.In conclusion when the data was used to perform the regression analysis test, it can be seen in fig 1. 3 that there are strong relationships between AHP and DI with perfect correlation.
After conducting the hypothesis test, the result was to reject the null hypothesis which was to facilitate. There were no relation between AHP and DI and that it was not possible for economist to predict house price movements. `2003 prediction? Hometrack predicted modest growth of 4% in 2003, but this was an over estimate. According to its latest data available, house prices in November had risen by 1. 1% year-on-year.’However as there were no sufficient evidence to support this HO was rejected, consequently the decision concluded that there was a relation between AHP and DI, as a result economist may be able to predict house price movements.
Although the test concludes that economist can predict house price movements there are problems they may have to deal with, such as inflation, rise of interest rates, unemployment etc. ‘Interest rates are currently at 4. 75%, compared with 15% in 1991, incomes have increased, as have employment levels, and mortgage lenders are lending out higher multiples of income. ”Assuming base rates remain on hold, it said, inflation will pick up next year and rise to the Bank’s target rate of 2% in two years. ’19 On the other hand the government can use monetary and fiscal policies to tackle these problems and once the economy is stable the economist may be able to predict house price movements.