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Technique of Design for Integrated Economic and Mathematical Model for Mass Appraisal of Real Estate Property. Study Case of Yekaterinburg Housing Market
There are a number of economic and mathematical models designed for mass appraisal of residential real estate at the moment, which take into account their construction and performance characteristics but do not take into account the evolving macroeconomic situation in the country and in the world. The drawback of such static models is their rapid obsolescence, the need for constant updating and unsuitability for medium-term forecasting. On the other hand, there are dynamic models that take into account the current macroeconomic situation but are designed for predicting and studying the overall price situation on the market rather than for mass appraisal of real estate with their variety of construction and performance characteristics. This paper proposes a technique of creating integrated models with properties of such static and dynamic models, i.e. taking into account both construction and performance characteristics of residential facilities and evolving macroeconomic situation in the country and in the world. Development of the technique and creation of models is carried out with the use of neural network technology on the basis of statistical data for the period from 2006 to 2016. In addition to its main purpose – the mass appraisal of urban apartments, the model is suitable for medium-term forecasting and identification of the patterns of the housing market. For example, the model was used to study the effect of the state financial policy on the housing market in Yekaterinburg. Computer experiments have shown that in case of growth in housing lending, the apartment prices will rise, and the rate of growth of luxury apartments with larger area will be about 2.2 times higher than the growth rate of cheaper apartments with smaller area. It was found that an increase in housing construction in Yekaterinburg up to 2,550 thous. sq.m. would lead to a further increase in value of apartments. However, with the increase in new housing above the 2,550 thous. sq.m. mark, the model predicts market saturation, prices growth cessation and their further decline. Similar studies and forecasts can be made for the real estate market in other countries and cities using the proposed technique.