与房价相关的社会经济因素。基于全球主要宏观经济总量的证据

Gabriela Lewandowska, Michal Taracha, Kamil Maciuk
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引用次数: 0

摘要

本文的目的是评估选定的经合组织国家的宏观经济因素与房价之间的关系。在本文中,作者描述了选定的社会经济因素,采用基于经合组织数据库的透明方法,得出的结果揭示了塑造房地产价格趋势的主要驱动因素。对1990-2020年期间已获得完整数据的经合发组织成员国和非成员国的通货膨胀和国内生产总值这两个主要经济总量进行了分析。经合组织总共提供60个国家的数据,其中38个是该组织的成员国。然而,由于缺少对某些国家的观察,在其中19个国家进行了分析。这项研究的目的是确定GDP和通胀动态如何与房地产价格变化相关。在分析的国家中,日本和南非在通货膨胀方面可以被区分为异常值,而在GDP方面,意大利、日本、爱尔兰和挪威则很突出。此外,还详细介绍了12个具有代表性的国家。这些国家包括四组,每组三个国家分为两个维度:第一组基于最高和最低的相关系数,第二组基于用于计算相关系数的测量(房价与GDP的相关性以及房价与通货膨胀的相关性)。在分析的基础上,GDP和房价之间的联系比通货膨胀和房价之间的联系更强——在大多数情况下,价格与GDP的增长速度相似。在挪威、新西兰和瑞典,GDP和房价之间的相关性特别高,这表明这些高度发达国家的住房财富变化对边际住房消费的反应可能更高,其特点是住房交易成本特别低,抵押贷款市场效率很高。由此推断,这些特征导致新房需求具有较高的财富弹性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Socio-economic factors associated with house prices. Evidence based on key macroeconomic aggregates globally
The aim of this paper is to assess the association between macroeconomic factors and house prices in selected OECD countries. In this paper, authors describe selected socioeconomic factors, adapt a transparent methodology based on the OECD database and derive results shedding a light on the main drivers shaping the trends of the real estate prices. Two main economic aggregates, inflation and gross domestic product (GDP) were analysed for the OECD member and non-member countries for which complete data have been made available for the period of 1990-2020. The OECD provides data for 60 countries in total, out of which 38 are members of the organization. Nevertheless, due to missing observations in certain countries, the analysis was carried out in 19 of them. The aim of the study was to determine how GDP and inflation dynamics are correlated with changes in property prices. Among the analysed countries, Japan and South Africa could be distinguished as outliers in terms of inflation, whereas in the case of GDP, Italy, Japan, Ireland and Norway stood out. Additionally, 12 representative countries were described in detail. These countries comprised four groups of three countries divided across two dimensions: the first, based on the highest and the lowest correlation coefficient, and the second, based on the measure used to calculate the correlation coefficient (correlation of the house prices with GDP and correlation of the house price with inflation). On the basis of the analyses, it was shown that the association between GDP and house prices is stronger than that between inflation and house prices – in most cases, prices increased at a similar rate as GDP. A particularly high correlation between GDP and house prices was found for Norway, New Zealand and Sweden, indicating a potentially higher marginal housing consumption responsiveness to changes in housing wealth in these highly developed countries, characterised by particularly low housing transaction costs and efficient mortgage market. It was deduced that such characteristics lead to a higher wealth elasticity of demand for new houses.
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CiteScore
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