{"title":"House price bubble detection in Ukraine","authors":"Alona Shmygel, Martin Hoesli","doi":"10.1108/jerer-10-2022-0031","DOIUrl":null,"url":null,"abstract":"Purpose The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble. Design/methodology/approach House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data. Findings The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense. Research limitations/implications The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates. Practical implications A tool for measuring fundamental house prices and a bubble indicator for 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. Social implications The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market. Originality/value The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"5 1","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of European Real Estate Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jerer-10-2022-0031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1
Abstract
Purpose The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble. Design/methodology/approach House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data. Findings The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense. Research limitations/implications The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates. Practical implications A tool for measuring fundamental house prices and a bubble indicator for 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. Social implications The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market. Originality/value The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.
本文的目的是为评估乌克兰最大城市房价的基本价值提供一个框架,并确定阈值,违反该阈值将标志着泡沫。设计/方法/方法房价泡沫检测使用两种方法:比率和回归分析。考虑了每种方法的两种变体。作者计算了房价租金比和房价收入比,可以确定房价可能被高估或低估。然后,作者通过考虑每个城市的单个多因素模型和使用单向(个体)影响面板数据的内部回归模型进行回归分析。唯一明显且持续时间长的房价泡沫时期是与全球金融危机同时出现的时期。平均而言,这些方法产生的泡沫信号是同步的,并且符合经济意义。本文中描述的框架可以作为一个模型,用于在其他新兴、小型和开放的经济体中检测房价泡沫的工具的实施,因为它包含了对高通货膨胀和对储备货币的严重依赖的调整。房地产市场的系统性风险将被用于监测房地产市场的系统性风险,并将使用衡量基本房价的工具和房地产市场泡沫指标。因此,它将帮助乌克兰国家银行(National Bank of Ukraine)维持金融稳定。本研究提出的框架将有助于增强乌克兰国家银行的系统性风险分析工具包。因此,这将有助于防止或减轻房地产市场可能产生的风险。原创性/价值作者展示了如何实现一种检测乌克兰房价泡沫的工具。在乌克兰战后重建的背景下,这将变得非常重要,抵押贷款可能成为住宅房地产存量重建/翻新融资的主要工具。