Identification of Housing Price Bubbles in Cyprus Using a Decision Support Model

Abstract

This paper attempts to formulate a means to identify potential bubbles that might occurs in the housing market, with a focus on the island of Cyprus. Over the past two decades, Cyprus has experienced a severe downfall of property prices, following a construction industry boom and then the bail-in and the restructuring of the two largest banks on the 16th of March 2013. The events which followed were unprecedented and their effect on property values has been proven intense. Currently, the general trend of property prices in Cyprus has been on a consistent upward trajectory, supported by constant demand, limited housing supply, increased foreign investment, population growth and broader economic growth across key regions. In achieving this aim, the decision support model developed by Pitros and Arayici (2016), was used. This methodology was enhanced with the use of correlation and regression analyses, in order to measure the relationships between the variables. The regression analysis showed that the independent variables can predict about 89% of the increases and decreases of HPI ratio over time, which was the dependant variable. Furthermore, according to the model, Cyprus has been in a high risk for a housing bubble during the period 2012 to 2013 and also recently from 2017 to 2024. In depth analysis of those results concluded that model has some disadvantages in its application, mainly the use of the definite threshold value. In the context of Cyprus, this model can be used as a measurement scale of the indication of an increasing or decreasing risk of a housing bubble episode.