ABSTRACT
This study attempted at examining empirically the effects of inflation rate, interest rate and unemployment on the U.K housing market index. The methodology of the research was basically the multiple regression analysis which was utilized with Microsoft excel. The study employs the use of secondary quarterly time series data on the variables. An evaluatory analysis of the results obtained in this study reveals that inflation rate effect and unemployment effect on the U.K housing market demand were found to be negative and statistically significant while the interest rate effect was also negative but insignificant.
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INTRODUCTION
According to the United Nations (1965), “…. the situation of housing is getting worse owning to the increasing impact of its causes-population growth and even worse, urbanization”. The fifth session of the Unite Nations Committee on Housing Building and Planning held in Geneva in October 1967 also reported that little general progress had been achieved recently in the field of housing and that the cause of housing is being downgraded (Burns and Tjeo, 1967).
The United Nations (1965) in recognition of the housing needs in developing of countries estimated that in order to provide for present and future needs an annual rate of housing construction of 8 to 10 housing units per 1,000 persons is needed. Based on this, Adeniyi (1981) estimated that taking a very high population of U.K economy, government needed to construct 10,000 housing united every year in order to meet the present and future housing needs of its citizens. The construction of housing in the U.K is primary a function of the private market i.e. approximately 90% of urban housing is produced by private developers (Taylor, 2000). The objective of this paper is to prove, that economic indicators do precede the housing industry. This paper aims to give an indication of an economic question:
(I) Does economic indicator have effect on housing market?
(II) How strong is the effect of the economic variables used?
STATEMENT OF THE PROBLEM
Housing issue has become a significant one in the world all over. The emergence of substantial housing problems in the world has led to widespread debate about it causes. Many economists that favour traditional adjustment strategies contend that monetary growth, arising particularly from the domestic bank financing of large budget deficits, interest rate, and inflation rate have debilitating efforts on housing market. By contrast, some critics of this approach contend that, unemployment is the major source of the housing problem in the world.
Despite its importance, there has been surprisingly little research on the causes of housing problems in most countries of Europe particularly the U.K. Thus, the relative importance of different factors (inflation rate, interest rate and unemployment rate) as causes of housing remains to be determined.
AIMS AND OBJECTIVES OF THE RESEARCH
The aims of this study are:
To examine the impact of interest rate on the housing market index.
To analysis rigorously the impact and influence of inflation rate on the housing market index in the U.K.
To establish empirically the effect of unemployment level on the housing market index in the U.K. Thus, it is an attempt to determine the role played by unemployment in generating the problems associated with housing in the UK.
RESEARCH HYPOTHESIS
Having identified that it is the objectives of this study principally to examine empirically, the effects of inflation rate, interest rate and unemployment on housing in the U.K, the following hypotheses have been designed to enable us carry out our empirical verifications into the research problem and are thus subjected to empirical testing.
Does economic indicator have effect on housing market?
How strong is the effect of the economic variables used?
RATIONALE OF THE STUDY
The rationale for this research is that;
(I) The research will complement existing empirical work.
(II) The empirical analysis of the relationship between housing market index in the U.K and macro-economic variables (inflation rate, interest rate and unemployment level) is lacking in the U.K.
(III) The research empirically distinguishes the role played by inflation rate, interest rate and unemployment level on the housing market index in the U.K.
LITERATURE REVIEW
THE NATURE OF THE HOUSING MARKET
According to Gavin Cameron (2005), the UK housing market has been booming in the past few years, with prices rising much faster than household incomes. He also underlies the drivers of house price growth, concludes that the current high ratio of prices to earnings may not be sustainable, and discusses what policy measures might help to make the market less volatile in future. After its dramatic crash in the early 1990s, the UK housing market has staged a remarkable recovery. According to the HBOS index, the average house price currently stands at about £163,000, almost exactly double the £82,000 it would have been worth at the turn of the millennium. Research published on (www.housingoutlook.co.uk) suggests that house prices have now surpassed their 1989 peak, relative to average household incomes. Like all markets, the housing market is bound up in a web of institutions, and these institutions differ markedly across countries. Across the world, housing markets divide into three main types. In the first, exemplified by the UK, most mortgages are at variable interest rates (according to Council of Mortgage Lenders data, around two thirds of all loans are currently at variable rates), loan-to-value ratios tend to be high (the current median advance is around seventy per cent of the house price) and re-mortgaging is easy (re-mortgages and further advances account for over half of all mortgage lending at the moment). In the second, exemplified by the USA, most mortgages are at fixed interest rates, loan-to-value ratios tend to be slightly lower, but re-mortgaging is still easy. In the third, exemplified by Germany, most mortgages are at fixed rates, but loan to value ratios are low and re-mortgaging is difficult. Not surprisingly, in countries like Germany and Italy, a much bigger proportion of the population chooses to rent rather than buy. An appreciation of the difference between housing markets suggests that the volatility and determinants of house prices will be quite different in different countries.
Most models of house prices also find strong positive effects from recent rises in house prices (this is the so-called ‘bubble-builder’ effect) and that there are negative effects from high levels of house prices (the so-called ‘bubble-buster’ effect). Taken together, these effects mean that house price rises tend to build up a momentum of their own until eventually they become simply too high for the prevailing economic conditions and then they fall dramatically. Of course, some countries are more susceptible to bubbles than others – it is very difficult for bubbles to get started in Germany because the market is not very sensitive to interest rates. Most importantly though, over the long-run, the principal determinant of prices is household earnings. Changes in house prices affect the economy through a number of channels. The most obvious is through their effects on households. First, a fall in house prices makes households feel less wealthy and so consume less. Second, a fall in house prices means that households have less collateral to borrow against, and so cannot finance holidays and new kitchens by re-mortgaging. Research by the OECD suggests that these effects are stronger for the UK than for any other developed economy, with a 1 per cent fall in UK housing wealth being correlated with a 0.07 per cent fall in consumer spending. Research also shows that house prices are more volatile in the UK than across the rest of Europe too.
INTEREST RATES
The rate of interest is the reward for parting with liquidity for a specified period. It is the inverse proportion between a sum of money and what can be obtained for parting with control over the money in exchange for a debt for a stated period of time. In this sense, it is seen as a measure of the unwillingness, of those who possess money to part with their liquid control over it.
Various theories of interest rates put together explain or provide variable, which determine interest rates. These theories differ because of differences of opinion as to whether interest rates are monetary or real phenomenon. These theories are: The classical theory of interest, the Keynesian liquidity preference theory of the rate of interest, the loanable funds theory of interest, the neo-classical theory of Pigou, the Hicksian IS-LM framework and the monetarist framework of Friedman (Anyanwu, 1993).
According to the classical theory the interest rate is determined by the intersection of the investment-demand-schedule and the saving-schedule, i.e. schedule disclosing the relation of investment and saving to the rate of interest. The Keynesian liquidity preference theory of the rate of interest posits that the rate of interest is determined by the intersection of the supply-schedule of money (perhaps interest inelastic, if rigorously fixed by the monetary authorities) and the demand schedule for money (the liquidity-preference schedule). The loanable funds theory of Dennis H. Robertson, the rate of interest is determined by the intersection of the demand schedule for loanable funds with the supply-schedule. Here the supply-schedule is compounded or composed saving (in the Robertsonian sense voluntary savings) plus net additions to loanable funds from new money (Ms) and the dishoarding of idle balance (DH). In the Pigouvian parlance, interest rate is determined by the intersection of the demand-schedule for money with the supply-schedule of savings. Here the relevant supply-schedule is conceived in terms of saving out of current income, i.e., the excess of total income received over income received for services in providing for consumption. The Keynesian and the neo-classical propositions, taken together supply us with a theory of the interest rate of J.R. Hicks. From liquidity preference schedule at various income levels. These together with the supply of money fixed by the monetary authorities, give us the Hicksian LM-curve, which tells us what the various rates of interest will be (given the quantity of money and the family of liquidity preference curves) at different levels of income.
INFLATION
Inflation is a sustained increase in the average price of all goods and services produced in an economy. Different theories exist regarding what causes inflation. Different theories exist regarding what causes inflation. The Keynesian school of economics asserts that inflation is the result of the market forces of supply and demand causing changes in prices. Higher demand for goods and services results in “demand -pull” inflation. That is, more employees and higher incomes lead to more to expenditures and more demand for goods and services. Different theories exist regarding what causes inflation. The Keynesian school of economics asserts that inflation is the result of the market forces of supply and demand causing changes in prices. Higher demand for goods and services results in “demand -pull” inflation. That is, more employees and higher incomes lead to more to expenditures and more demand for goods and services. On the supply side, higher cost of supplies and services result in higher product prices, leading to “cost-push” inflation. For instance, when the cost of bricks rises, buildings cost more to construct. A combination of cost-push inflation can result in built -in inflation or a price- wage spiral. In this scenario, higher wages lead to higher prices of goods and services which in turn lead workers to demand pay raises. In the Keynesian view, money supply does not play a key role in causing inflation. Inflation is determined by aggregate demand measured in terms of gross domestic product (GDP). Money supply is just one of many determinants of aggregate demand. The Keynesian school also proposed the concept of optimal level of production, known as potential aggregate output or natural GDP. This is the highest level of GDP an economy can produce without adding to inflation pressures. The level of GDP in any period may be higher or lower than potential GDP, and the difference is known as the output gap. Another theory, the monetary school of economics inflation, says inflation is caused by an increase by an increase in the quantity of money in circulation relative to the supply of goods and services. As the late Milton Friedman, a Nobel Prize- winning economist, stated, “inflation is always and everywhere a monetary phenomenon”.
This literature identifies a number of theories of inflation, viz: demand-pull, cost-push, structural, monetary, and imported inflation. The demand -pull paradigm opines that demand-pull inflation occurs when aggregate demand for goods and service is greater than the aggregate supply such that the resultant excess demand cannot be satisfied by running down on existing stocks, diverting supplies from the export market or the postponing demand. The cost-pull school opines that inflation arises from increases in the cost of the factors of production, especially rising wages emanating from trade union activities -embodying also a ‘socio-political view’ (Addison et al, 1980, 1981 and Cobham, 1981). The stucturalists explain the long -run inflationary trend in developing nations in terms of certain structural rigidities; market imperfections and social tensions in those nations -relative inelasticity of the food supply, foreign -exchange constraint, protective measures, rise in the demand for food, fall in export earnings, boarding import substitution industrialization, political instability, etc. Monetarists opine that inflation is always and everywhere a monetary phenomenon: (Friedman, 1966, p.18) hence prices tend to rise when the rate of increase in money supply is greater than the rate of increase in real output of goods and services (Johnson, 1973). On the other hand, imported inflation arises from international trade whereby inflation is transmitted from one country to another and this is more so during a period of rising prices all over the world (Harberger, 1978).
UNEMPLOYMENT
It is generally agreed that unemployment like inflation, is a symptom of basic economic illness or macroeconomic disequilibrium. What is, however, controversial is the “appropriate” conceptualization of the subject. During the early days of the development of unemployment theory, much controversy over the definition and origins of unemployment revolved around the distinction between “voluntary” and “involuntary”. unemployment. Even the conceptualization of these categories has been a source of contention. Nevertheless, voluntary unemployment is said to exist when persons choose not to work or accept job for which they are qualified at the going wage rate and conditions probably because they have means of support other than employment. On the other hand, involuntary unemployment exists when persons cannot obtain work even if they are willing to accept lower real wages or poorer conditions than similarly qualified workers who are currently in employment. Despite the difficulties of measurement and norm-setting the above classification, the taxonomy of unemployment includes a condition (being out of work), an activity, (searching for work), an attitude (desiring a job under certain conditions), and a need (needing a job) (Levine, 1957).
Unemployment may be classified into two basic categories: Unemployment that results from deficient aggregate demand and all other unemployment due to frictions and labour market (mal) adjustments. The latter in turn is often divided into frictional, structural, seasonal, real-wage, technological cyclical, unemployment. Deficient demand unemployment occurs when there is not enough aggregate demand to produce work for the whole labour force no matter how it is trained or deployed. Frictional or search unemployment arises because it takes time and resources for workers to change jobs, either voluntarily or involuntarily, even though suitable job vacancies exist and can be found without the worker having to adjust his broad occupational status or his reservation wage. Thus, fractional unemployment is normally viewed as that amount of unemployment that corresponds to (unfilled) variant of normal unemployment -hard-core unemployment (irreducible minimum value) being the long-term variant. Structural unemployment, on the other hand, exists when there is a mismatching between the unemployed and the available jobs in terms of geographic location, required skills or any other relevant dimension. Seasonal unemployment is seen as unemployment due to the existing too high level of real wages. Technological unemployment, technological unemployment arises when machines replace men in the production process. This is a regular feature of technologically advanced nations of Europe and America. Cyclical unemployment however, is traditionally associated with the trade cycle, especially recession and depression. This explains why some experts classify it as a variant of deficient-demand unemployment (see Anyanwu, 1985 and 1991).
DATA AND METHODOLOGY OF THE RESEARCH
METHODOLOGY
The relationship between the dependent and explanatory variables is examined in this study using regression analysis. Regression analysis shows how the typical value dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. A regression analysis aims to find a relationship between the dependent variable (house price) and the independent variables (inflation, unemployment and interest rates) which are possible predictors of such. This commonly used statistical tool determines if there is a correlation between the variables and if so, the nature of their correlation.
Therefore the estimated regression equation is thus:
Where µ is the error term that assumed normal distribution (µ) with mean, 0 and standard deviation, .
The result is a regression equation shown above, which is a numerical equation that defines how dependent variables are predicted by independent variables. The regression also gives indicators on how good or poor the model is in predicting the dependent variable. Therefore we set the hypothesis
If the p-value is below 0.05 for each variable, then those independent variables are correlated to the dependent variable.
The multiple regression correlation coefficient, ,
is a measure of the proportion of variability explained by the regression relationship model or the regression equation. Roughly, this means the is the percentage at which the model explains the changes in the dependent variable based on the independent variables. Lastly, the standard deviation is the range at which there is +/- error with a 95% confidence level.
DATA SOURCES
The study employs the use of secondary data. In other words annual time series data on inflation rate, interest rate, unemployment and the housing market index were all obtained from secondary sources including the International Monetary Fund’s International Financial Statistics CD and from Office of National Statistics.
EMPIRICAL ANALYSIS OF RESULT
Following the model specification presented and utilizing quarterly time series data on housing market, inflation rate, interest rate and unemployment as obtained from secondary sources. The results obtained after running the data through Microsoft Excel 2007 are as follows:
The estimated regression model becomes;
61.39964-6.22001-7.10866-0.56578
Regression Statistics
Multiple R
0.801376611
R Square
0.642204472
Adjusted R Square
0.611536284
Standard Error
6.52483476
Observations
39
The value of R (Correlation coefficient) obtained for our data is 0.80 which lies between 0 and 1 indicating a positive relationship between housing market index and the selected macroeconomic variable (Inflation, interest rates and unemployment).
Its is important to note that out of all the possible economic indicators that affect housing prices, the one that will explain 64% of the changes in real estate prices comes from inflation, unemployment and interest rate. Inflation rates and unemployment rates are negatively correlated while interest rates are positively correlated. Exploring each variables in more details:
Coefficients
Standard Error
t Stat
P-value
Housing
61.39964
15.06058
4.076844
0.00025
Inflation
-6.22001
1.255517
-4.95414
1.84E-05
Unemployment
-7.10866
2.150694
-3.30529
0.002198
interest rate
-0.56578
1.130659
-0.5004
0.619928
Housing
Inflation
Unemployment
Interest rate
Housing
1
Inflation
-0.68146
1
Unemployment
-0.61329
0.317403
1
Interest rate
0.340454
-0.12518
-0.698823941
1
Inflation rates
The p-value suggests that there is a strong significant relationship between inflation and house prices. Inflation increase should lead to decrease in house prices.
Unemployment rates
From the analysis, it shows that unemployment is negatively correlated but has a significant relationship with house prices.
Interest rates
Interest rate from the analysis shows an insignificant relationship with house prices. But the relationship is positively correlated.
CONCLUSION
This study essentially discusses the effects of inflation rate, interest rate and unemployment on housing market in the U.K. The period of study is 2000-2009. Using the regression technique, two of the variables namely, inflation and unemployment were found to be statistically significant in determining the market behaviour of housing in the U.K, while interest rate was found to be insignificant. Thus, empirical findings in the study provides evidence in support of the economic question that economic indicators do have effects on housing market and also the need for policy makers to tolerate a certain rate of inflation as a way of boosting the housing market index in the economy, and also enunciating policies that would reduce unemployment. policy actions needs to be taken so as to improve on the housing market demand. In other words, a higher proportion of the total variations in housing demand in the U.K is as a result of the variations in inflation rate, interest rate and unemployment level.
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