Political Uncertainty and the Real Estate Risk Premiums in Hong Kong

This study investigates the effects of political uncertainty associated with the 1997 repossession of Hong Kong by China on the real estate market. Such effect is reflected in the change in the real estate risk premiums. A model is derived to estimate the trend of real estate risk premium for each subsector of the real estate market from observable market data. The results suggest that there was a discrete jump in the risk premiums when the 1997 issue was revealed to the public in 1983, indicating investor concern about the post-1997 future of Hong Kong. The increase in the risk premium is much more obvious in nonresidential real estate than in the residential sector. This is probably due to its dual nature (an investment good as well as a good for self-consumption) and the effects of rent control, which only applies to the residential units. However there is also very strong evidence that investor confidence has been increasing recently, thus leading to a decline in the implied post-1997 risk premium, although the increasing confidence is still not sufficient to bring the risk premium back to pre-1983 levels. If the concern about the repossession of Hong Kong by China turns out to be unnecessary after 1997, a revaluation of the risk premium will take place. This will bring the risk premium level back to the pre-1983 level, assuming no other significant changes have taken place. Other things being equal, such revaluation will result in a one-time discrete increase in property prices. This is in contrast to the common view that investors have already discounted the 1997 Hong Kong/China issue completely.

Excess Returns in the Hong Kong Commercial Real Estate Market

This study examines the existence of excess returns of the office, retail and industrial real estate sectors in Hong Kong using time series of both valuations and transaction prices. The analysis covers the period from 1980 to 1995. If valuations are an accurate reflection of transaction prices then excess returns, if they exits, should be detected in both series. Our findings confirm that excess returns can be detected in both valuation and transaction-based series. They are not, however, persistent although there appear to be greater opportunities for earning excess returns in the office sector.

Evaluation of Several Algorithms in Forecasting Flood

Precise flood forecasting is desirable so as to have more lead time for taking appropriate prevention measures as well as evacuation actions. Although conceptual prediction models have apparent advantages in assisting physical understandings of the hydrological process, the spatial and temporal variability of characteristics of watershed and the number of variables involved in the modeling of the physical processes render them difficult to be manipulated other than by specialists. In this study, two hybrid models, namely, based on genetic algorithm-based artificial neural network and adaptive-network-based fuzzy inference system algorithms, are employed for flood forecasting in a channel reach of the Yangtze River. The new contributions made by this paper are the application of these two algorithms on flood forecasting problems in real prototype cases and the comparison of their performances with a benchmarking linear regression model in this field. It is found that these hybrid algorithms with a “black-box” approach are worthy tools since they not only explore a new solution approach but also demonstrate good accuracy performance.Department of Civil and Environmental EngineeringSeries: Lecture notes in computer scienceAuthor name used in this publication: K.W. Cha

Past and Future Sources of Real Estate Returns in Hong Kong

Historical commercial real estate returns are attributed to three fundamental factors: initial current yield, growth in net operating income, and changes in going-in versus going-out capitalization rates (i.e., pricing movements). Separating returns into these three factors appears to provide more insightful information than the traditionally reported income and appreciation returns. Using this three-factor model, historical real returns and inflation pass-through rates are estimated for each major type of real estate (residential A/B/C, residential D/E, office, retail, industrial).

A three-dimensional pollutant transport model in orthogonal curvilinear and sigma coordinate system for Pearl river estuary

In this paper, the development of a three-dimensional numerical pollutant transport model, which is coupled with a previously developed hydrodynamic model, is delineated in details. Special features of the model include orthogonal curvilinear coordinate in the horizontal direction and sigma coordinate in the vertical direction. Besides, a simple but efficient open boundary condition of pollutant transport is adopted. It is then applied to simulate the transport of a representative water quality parameter chemical oxygen demand in Manganese (COD[sub Mn]) in the Pearl river estuary, which is the largest estuary in South China. It can be shown, from the simulated results, that there exists a transboundary action between Guangdong province and Hong Kong special administrative region for the pollutants in the wastewater discharged from Pearl river delta region.Department of Civil and Environmental EngineeringAuthor name used in this publication: K. W. Cha

Predicting Construction Litigation Outcome Using Particle Swarm Optimization

Construction claims are normally affected by a large number of complex and interrelated factors. It is highly desirable for the parties to a dispute to know with some certainty how the case would be resolved if it were taken to court. The use of artificial neural networks can be a cost-effective technique to help to predict the outcome of construction claims, on the basis of characteristics of cases and the corresponding past court decisions. In this paper, a particle swarm optimization model is adopted to train perceptrons. The approach is demonstrated to be feasible and effective by predicting the outcome of construction claims in Hong Kong in the last 10 years. The results show faster and more accurate results than its counterparts of a benching back-propagation neural network and that the PSO-based network are able to give a successful prediction rate of up to 80%. With this, the parties would be more prudent in pursuing litigation and hence the number of disputes could be reduced significantly.Department of Civil and Environmental EngineeringAuthor name used in this publication: Kwokwing ChauSeries: Lecture notes in computer scienc

Economic sustainability of heritage conservation in Hong Kong: The impact of heritage buildings on adjacent property prices

Informed by the theoretical framework of sustainable development and economic theories including the cluster theory and the corollary of the Coase Theorem, this paper empirically investigates the economic impact of architectural heritage in Hong Kong. Using the hedonic price model, the research examines the economic impact of 50 publicly owned versus 50 privately owned heritage buildings on adjacent residential property prices with a sample size of over 43,240 property transaction records spanning a time period of 10 years. The research supports that heritage conservation can promote economic sustainability aside from cultural sustainability and social engagement. This research benefits government policymakers, urban planners, architects, and heritage conservationists by contributing new knowledge to the studies on sustainable urban development, heritage conservation, and cultural economics