House price bubble detection in Ukraine - Alona Shmygel (Graduate Institute of International and Development Studies, 2022)
In this article, we developed a reliable method to detect house price bubbles using data for the largest Ukrainian cities. Further, we identified the thresholds, the breach of which is signaling that house price growth may be problematic as a bubble may be forming. In this paper, house price bubbles are detected with the help of two general approaches: ratio calculation and regression analysis. These general approaches are subdivided into two each. We calculated the Price-to-Rent and Price-to-Income ratios that can identify a possible over- or undervaluation of house prices for Ukrainian cities under the scope of this investigation. Then, we performed the regression analysis by building individual multifactor models for different cities and by running a pooled OLS regression for the panel data. According to the results, the only pronounced and prolonged period of house price bubbles is the one that coincides in time with the Global Financial Crisis - from late 2005 to early 2009. The bubble signals, produced by these methods are, on average, simultaneous and are in accordance with economic sense. A tool for measuring fundamental house prices and an indicator of bubble on housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability.
Keywords: C31; C33; E30; G21; 330; house price bubbles; fundamental house prices; mortgage lending; systemic risk; regression analysis