e a variable rather than a fixed mortgage rate in my study. The source of the data is provided by the Bank of England. I will be finding the correlation between the actual price level and the amount that can be borrowed based on the first equation. A high correlation between the series would therefore suggest a long term relationship between actual house prices and the price based on the average amount borrowed. I will also be performing cointegration tests based on Johansen's (1995) systematic approach to testing for cointegration between the actual price and the amount that can be borrowed. Based on my results from my cointegration test, I will proceed to estimate a long run relationship between the logs of the actual house prices and the amount that can be borrowed. I will be employing the dynamic ordinary least squares (DOLS) methodology of Stock and Watson (1993). The DOLS estimator falls under the single-equation Engle Granger (Engle and Granger, 1987) approach to cointegration while allowing for endogeneity (i.e. when correlation exists between a parameter or variable and an error term) is within the specified long run relationships.
Data relating to K which is the amount of household income that goes on mortgages, is provided by the Office for National Statistics and the Council of Mortgage Lenders. Figured show that as of July 2010, households spend 13.5 per cent of their income on mortgage repayment.
In this model, the demand side factors are being looked at in detail with respect to income and interest rates. I particularly argue that housing demand is primarily a function of the amount that potential home-owners, can borrow from financial institutions and is in turn, depends on the mortgage rate in that time period and also the current disposable income. This lead me to the term, annuity. This is a fraction of a households' current disposable income signified by κYt, that goes towards mortgage repayments and is treated by discounting, at the present mortgage interest rate such that it is equal to the mortgage term τ. This leads on to the derivation of the amount of financing that can be borrowed B-t
This equation, in reality simulates the idea that people seek to maximise the amount of leverage available to them. This equation is then going to be integrated within a more generalised model of the housing market as seen below.
From the model above, I have firstly defined Xt as the time-varying component of Bt as I have not taken into consideration, the proportion of household income that goes towards mortgage repayments. Secondly I have incorporated the time varying component (Xt) and proportion of household income going on mortgage repayments (κ) into an inverted demand function of:
Following basic economic theory I assume a downward sloping demand curve with the price elasticity of demand for housing indicated by the inverse of the parameter μ. Changes in income or interest rates are the demand shifting factors in this context. The housing supply variable S comes into this function through the own price elasticity thus resulting in negativity.
Delta is the supply functions intercept which primarily causes shifts in the supply of housing stock. Which is determined by construction firms and government policies that affect them? It should be noted that supply is assumed to be inelastic in the short-run as there is a time interval in the provision of new-builds (S=S^-). Furthermore, house pric
