Property researchers have sought to bring together macroeconomic variables in formal modelling of property variables and hopefully distil trends from cycles and thus discern turning points. The problem is it is difficult to know what exactly needs to be taken into account. To assess economic growth and property activity items such as income will clearly be influential and must be taken into account, while other factors will be of debatable relevance, such as wealth effect. The next problem is how much weight should be attached to each individual factor, which is required to make the model more accurate at forecasting future activity. Factors such as consumer confidence and debt asset ratio (which has become increasingly influential for the last two decades with the liberalisation of the credit market) can have varying importance over time and thus pose problems for anyone hoping to make a model that will last the test of time. Within these components lies even more complex analysis. For example, consumer confidence is regarded as a key determinant of demand for property, yet one must first analyse the key determinants for consumer confidence. This demonstrates how no model is exhaustive and how they need to be organic and dynamic with the ability to evolve as the economy develops.
Even if the components of the models were reasonable, the next dilemma facing the property profession is data. Data validity can be very problematic as depending on the sources and time line. This is heightened in the property market where pre-1980 property history (a major step to 1981 when IPD figures were based on 133 portfolios as opposed to 6 in1971) data was subject to uncertainties and errors arising from differences in coverage and in methods. Nevertheless, there has definitely been a conscious move by researchers- aided by globalisation and increased communication links and information through the internet- and today there are ample available and accurate sources used in economic models, such as the Economics Trend Annual Supplement. Up to date figures are essential as the markets are in a state of perpetual change. The lack of this data and failure of individual firms from pooling their research together may have been a key reason why they gave terrible advice to customers, yet it is best discuss the failure of the property profession in more detail later.
Unpredictable shocks and mismanaged government policies exacerbated problems for forecasters in property market. During the 80s government policy helped to fuel the boom in property, with incentives to become homeowners like MIRAS-mortgage income relief at source). This offered tax relief on mortgage payments of first time buyers, encouraging many new first time buyers into the market, thus accentuating the fluctuations in the cycle and worsening the recession following the boom as people plunged into negative equity. Prolonged cycles make turning points even more difficult to judge as they can give the impression that long-term trends are changing. Unpredictable government policy is therefore both difficult to factor in models, and has a very distorting impact on property markets. Mistakes in international government decisions can also be extremely damaging such as the catastrophic EU decision made by John Major to enter the ERM at too high a rate, thus prolonging the recession and delaying the recovery in the economy. Government raised interest rates to 15% at one stage on Black Wednesday to try and defend the pound. Other more direct shocks to the economy include the oil crises in the 1970s, which show how unpredictable factors make it difficult for analysts to forecast the future.
The time lags involved in property are arguably the most problematic influences to predict turning points correctly. There is a time lag concerning the decision to supply the property and actually supplying it. Although construction improved speed wise during the period, investors chose to build in a buoyant market and then have their finished product in the midst of a recession. This created immense as a sudden surge of property being supplied can often tip the cycle over the edge. This is not easy to forecast as the imperfect property market consists of delays between demand falling and supply responding. Another problem is that with property being such a vast outlay, investors prefer evidence that the market is going the right way before investing. This means that property investment is a lagging indicator, a year behind other key indicators. These lags are make turning points difficult to pin point as they are prone to variations.
The failure of the property profession in relation to all the other factors does seem to be a major reason why it has failed to forecast turning points. Despite the wealth of statistics and evidence, the lack of clear economic understanding and theory in the industry makes interpreting data difficult pointless. The lack of economic theory means models become useless too, and surveyors have been accused many times of just advising clients based just on ‘gut instinct.’ This intuition, although useful as it may be based on many years of experience in the industry, is far too unsubstantial to predict turning points in the market. Surveyors focused too much on the present, and are blissfully unaware of the wider structural changes occurring in society as a whole which are changing both the demand and supply of property. Maybe they do not have the resources or time to conduct detailed research within the market. The biggest problem during the period was the fact that property and economic information became a marketable commodity, thus each individual firm was suffering from asymmetric information. They did not see the benefit of pooling their information together, with no individual firm knowing enough about what is going on.
