Lead-Lag Relationship between the Price-to-Rent Ratio and the Macroeconomy: An Empirical Study of the Residential Market of Hong Kong
Author(s): |
Daniel Lo
Yung Yau Michael McCord Martin Haran |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 16 September 2022, n. 9, v. 12 |
Page(s): | 1345 |
DOI: | 10.3390/buildings12091345 |
Abstract: |
The price-to-rent (PtR) ratio is one of the most commonly used indicators to assess housing market conditions by policy makers and real estate practitioners. It is often employed as an economic barometer to detect whether a housing bubble exists and determine whether the property market has become unaffordable relative to historical trends. Despite a plethora of research studies on the PtR ratio in the housing literature, relatively little is known about its long-term dynamics with macroeconomic and financial determinants. By utilising time series data on the Hong Kong residential property market, this study examines the cointegration and causal relationships between a wide spectrum of macroeconomic indicators and the PtR ratios of housing segments of different tiers which comprise different socioeconomic groups of homebuyers and investors. The results point towards market compartmentalisation, in the sense that the PtR ratios of the housing submarkets respond to changes in macroeconomic fundamentals in a differential manner. For instance, the PtR ratios of housing segments with a greater proportion of owner-occupiers are statistically less y correlated with investment-related macroeconomic attributes, such as foreign direct investment and equity market performance. On the other hand, the pricing of large-sized housing units in prime locations, generally favoured by investors from mainland China, are found to be Granger-caused by the exchange rate of the Chinese Yuan to the Hong Kong dollar. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10692647 - Published on:
23/09/2022 - Last updated on:
10/11/2022