Hong Kong: A Review of Its Land System, Real Estate Market, and Related Matters

Author(s):  
Roger Nissim
2014 ◽  
Vol 10 (2) ◽  
pp. 241-262 ◽  
Author(s):  
Kim Hin/David Ho ◽  
Kwame Addae-Dapaah

Purpose – The purpose of this paper is to help us understand the real estate cycle and offers an analysis using a vector auto regression (VAR) model. The authors study the key international cities of Hong Kong, Kuala Lumpur and Singapore. The authors find four key outcomes. One, the real estate cycle is generally different from the underlying business cycle in local markets for the cities studies. Two, the real estate cycle is more exaggerated in the construction and development areas than in rents and vacancies. Three, the vacancy cycle tends to lead the rental cycle. And four, new construction completions tend to peak when vacancy is also peaking. The authors believe that future research should try to help understand the linkages that drive these outcomes. For example, are rigidities in the local permit and construction markets responsible for the link between construction peaks and vacancy peaks? Design/methodology/approach – Real estate market cyclical dynamics and its estimation via VAR model offers an insightful set of practical and empirical models. It affirms a comprehensive theoretical underpinning for analysing the prime office and residential sectors of the capitol cities of Kuala Lumpur, Singapore and Hong Kong in the fast developing Asia region. Its unrestricted form also provides an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, furnished by real estate market data providers. Findings – The office rental VAR model for Singapore (SOR), KL (KOR) and HK (HOR) show good fits. In the HOR model, rents and vacancies are negatively signed and significant for certain lagged relationships with other variables and with rents themselves. The office CV VAR model for Singapore (SOCV), KL (KOCV) and HK (HOCV) show good fits. In the HOCV model, capital values (CVs) and initial yields are negatively signed and significant for certain lagged relationships with other variables and with CVs themselves. Impulse response functions specified for seven years to mirror a medium-term real estate market cycle “die out” to zero for the stationary VAR models that are estimated for the endogenous variables. The accumulated responses asymptote to some non-zero constant. Practical implications – The VAR model offers a complete and meaningful dynamic system of solely real estate variables for international real estate investors and policy makers in decision making. Its unrestricted form offers an effective and insightful way of modelling real estate market cyclical dynamics utilising only real estate market indicators, which can be reliably provided by a dedicated real estate information and consultancy provider of international standing. Originality/value – The theoretical model offers a complete dynamic model system of the real estate space market, comprising a unique system of six linked equations that denote the relationship among supply, demand, construction, vacancy and rent over time, inclusive of price response slopes and lags. The VAR model enables the investigation of the effect of the lagged values of all the variables concerned. It also enables the explicit and rigorous quantitative forecasts of say rents and CVs when the rest of the variable can be forecasted beforehand.


2015 ◽  
Vol 45 (1) ◽  
pp. 133-153 ◽  
Author(s):  
Siu Kei Wong ◽  
Thomas C. C. Lai ◽  
Kuang Kuang Deng

2020 ◽  
Vol 69 ◽  
pp. 958-976
Author(s):  
Tatsuyoshi Miyakoshi ◽  
Kui-Wai Li ◽  
Junji Shimada ◽  
Yoshihiko Tsukuda

2001 ◽  
Vol 18 (3) ◽  
pp. 187-216 ◽  
Author(s):  
K.W. Chau ◽  
Bryan D. MacGregor ◽  
Gregory M. Schwann

2011 ◽  
Vol 15 (1) ◽  
pp. 26-34 ◽  
Author(s):  
Eddie C. M. Hui

This paper aims to examine the relationship between real estate market and stock market in the United Kingdom and in Hong Kong, from 1993 to 2007, using the method of datamining. The results provide evidence for the existence of not only a positive correlation, but also a co-movement, between the two markets. Such interactions reflect the similarities among these two regions, which can be explained by two transmission mechanisms: wealth effect and credit-price effect. However, the two real estate markets respond differently upon similar adjustments of the respective stock markets. Such dissimilarity is attributed to their respective local factors. It is shown in the paper that datamining could be an appropriate option for studying this kind of relationships. Santrauka Šiame darbe siekiama duomenų analizės metodu išnagrinėti ryšį tarp Jungtinės Karalystės ir Honkongo nekilnojamojo turto rinkų ir akcijų rinkų nuo 1993 iki 2007 m. Remiantis gautais rezultatais matyti, kad tarp minėtų dviejų rinkų egzistuoja ne tik teigiama koreliacija, bet ir kovariacija. Tokios sąveikos rodopanašumus tarp šių dviejų regionų, o tai paaiškinama dviem perdavimo mechanizmais: turto poveikiu ir kredito bei kainos poveikiu. Tačiau dvi nekilnojamojo turto rinkos skirtingai reaguoja į panašų akcijų rinkų reguliavimą. Taip vyksta dėl jų vietinių veiksnių įtakos. Duomenų analizė galėtų būti tinkama alternatyva tiriant tokius ryšius.


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