Proposing a novel model based on ARIMA technique for forecasting housing price: a case study of Tehran

Determination and prediction of housing price in urban areas plays a significant role for governments, public and private enterprises, and financial evaluators. An accurate estimation of the housing price can be employed for future planning and decision making in many urban and regional policies. However, the growth of the housing sector has a profound impact on gross national product, resulting in a significant increase in employment. On the other hand, an increase in loan for purchasing house leads to a rise in liquidity and inflation rate. This means that the gap between the income and housing price is increased. Therefore, it is necessary to develop new models for making decisions in order to prevent the increase in the inflation rate and housing price. According to the key importance of housing price, a number of models have been developed to formulate the price behavior with regard to its effective components. In this study, a novel model based on the ARIMA method for forecasting and formulating the housing price has been developed. The results show that the model proposed has a high potential (with a determination coefficient of 99.7%) to foresee the housing prices in the city of Tehran.