What drives house prices in Turkey? Evidence from Bayesian SVAR model

被引:1
作者
Yildirim, Mustafa Ozan [1 ,2 ]
Yildirim, Ozge Filiz [3 ]
机构
[1] Pamukkale Univ, Dept Econ, Denizli, Turkiye
[2] Kings Coll London, Kings Business Sch, Dept Banking & Finance, London, England
[3] Izmir Katip Celebi Univ, Dept Econ, Izmir, Turkiye
关键词
House prices; Housing market; Sign and zero restrictions; Bayesian SVAR; Turkey; C32; E32; E51; R31; MONETARY-POLICY; CREDIT;
D O I
10.1007/s10644-024-09845-0
中图分类号
F [经济];
学科分类号
02 ;
摘要
Turkey has experienced one of the largest rises in house prices in the world, particularly after the COVID-19. Given the entangled relationship between house prices, macroeconomics, and financial markets, it is crucial to understand the causes of house price hikes from both academic and policy perspectives. This study aims to identify the determinants of house prices in Turkey. The analysis employs a Bayesian sign- and zero-restricted Structural Vector Autoregression (SVAR) model, utilizing monthly data spanning the period from January 2011 to December 2023. The model incorporates six shocks considered to affect house prices: housing supply, housing demand, credit conditions, mortgage rates, exchange rates, and market sentiment. The findings reveal that housing supply, mortgage rates and credit conditions are the primary drivers of house prices in Turkey. Prior to 2018, housing supply shocks accounted for nearly half of the observed increase in house prices. However, in the post-2018 period, mortgage rates and credit conditions emerged as the predominant drivers of house price dynamics. Moreover, consumer sentiment and exchange rate fluctuations also significantly contribute to house price variations. These findings offer valuable policy insights for mitigating the risk of housing market booms.
引用
收藏
页数:24
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