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The first Hong Kong Real Estate Investment Trust (HK‐REIT), the Link REIT, was successfully launched in late 2005. The retail tranche of its initial public offering (IPO) was 19 times oversubscribed, and the IPO is the largest of its kind in the world until now. Despite the initial phenomenon success, there have been only three others to follow and get listed. Indeed, it took Hong Kong over two years to have her first Link REIT listed after the legislation for REIT products had come into force. The development of REIT market in Hong Kong has been slow compared to its counterparts in some other Asian countries. This paper aims to explain the somewhat sluggish growth of the HK‐REIT market. Its development is compared with some emerging Asian markets as well as the more mature markets in the USA and Australia. The study is focused on the legislations that govern REITs in different jurisdictions, their different REIT market envi‐ronments and the rationale from the respective governments to introduce their REITs. It is concluded that the sluggish development of HK‐REITs is mainly due to its market environment and industry structure. There is not enough incentive for developers to dispose their assets in the form of REITs. Besides, the HK‐REIT Code was initially criticized by the industry as being too restrictive. Though subsequent amendments on the HK‐REIT Code have been made to make it more conducive to the development of REIT market, further sustainable success will however hinge on the willingness from sponsors, particularly large developers, to offer their portfolios of properties for sale through REITs.

Manpower is the most valuable asset in the construction industry. Based on an examination of literature, selected key data sources, and views from 29 key informants, this paper addresses the important labour resource context related to the construction industry in the case of Hong Kong. These include the trends of the critical indicators of the labour market in construction and the implications of the changing markets and technology on the future pattern of skill requirements, and the government policies on construction personnel. The findings are of immense importance to anyone involved in the construction industry, particularly training organizations and policy makers in their mission to maintain a skilled, competitive and adequate workforce able to meet the future demands of the industry. The changing labour market trends and skill requirements pose challenges for construction personnel in terms of upgrading their skills. Further research is recommended to construct robust models predicting the occupational trends in labour resources for effective manpower planning and to establish a labour market information system which could lead to capturing periodic labour market signals with a view to assisting the process of policy making on various human resource development aspects of construction workforce in Hong Kong.

The construction industry plays a significant role to the economy of Hong Kong not only in terms of output but also the employment. The sector, however, has been severely hit by the economic downturn in recent years resulting in serious unemployment. Employment planning becomes one of the critical aspects for the recovery of the economy. The main objective of this paper is to establish a labour demand model for the Hong Kong construction industry. The unique characteristics and the current conditions of the construction labour market are reviewed. Regression analysis based on 123 construction projects was used to compute the relationship between expenditure and site workers employed. The best predictor of average labour demand of construction projects in Hong Kong is found to be DL = 463 C 0.934, where DL is the actual labour demand in man‐days, C is the final cost of contract in millions. The labour demand‐cost relationship can be applied as a manpower forecasting model to estimate the total labour required for a given type of project. The developed model enables a more reliable and accurate planning of manpower requirements in the construction industry.

This study finds evidence that a stock return is inversely correlated with downside risk, confirming a pattern of risk-aversion behavior. Evidence from testing a stock return's response to a change in economic policy uncertainty indicates a significantly negative effect in the Chinese stock market; this conclusion holds true for testing the impacts of changes in fiscal and monetary policy uncertainties. However, the data produce a mixed effect for the change in fiscal policy uncertainty. The evidence produced from examining the geopolitical effect on the stock market strongly supports the presence of an adverse effect on stock market performance.

This chapter tests the market risk and economic policy uncertainty (EPU) of five Asian stock market returns and finds positive and significant intertemporal relations between excess stock returns and conditional volatility/downside risk. The results support positive risk-return relations across five Asian markets after controlling for the lagged dividend yield and the change in EPU ( Δ EPU). The evidence strongly indicates that excess stock returns are negatively correlated with the Δ EPUs. This finding holds true not only for the domestic market but also for external sources. The negative effect of Δ EPU is more profound from the US and global markets as compared with those from the Europe, Japanese, and domestic markets and suggests that a pathway to forming an optimal strategy for portfolio risk management depends on developing an effective hedging strategy against the impact of Δ EPUs from US/global markets.

Fluctuations in the tender price index have an adverse effect on the construction sector and the economy at large. This is largely due to the positive relationship that exists between the construction industry and economic growth. The consequences of these variations include cost overruns and schedule delays, among others. An accurate forecast of the tender price index is good for controlling the uncertainty associated with its variation. In the present study, the efficacy of using an adaptive neuro-fuzzy inference system (ANFIS) for tender price forecasting is investigated. In addition, the Box–Jenkins model, which is considered a benchmark technique, was used to evaluate the performance of the ANFIS model. The results demonstrate that the ANFIS model is superior to the Box–Jenkins model in terms of the accuracy and reliability of the forecast. The ANFIS could provide an accurate and reliable forecast of the tender price index in the medium term (i.e. over a three-year period). This chapter provides evidence of the advantages of applying nonlinear modelling techniques (such as the ANFIS) to tender price index forecasting. Although the proposed ANFIS model is applied to the tender price index in this study, it can also be applied to a wider range of problems in the field of construction engineering and management.

This chapter examines changes in US monetary policy uncertainty (ΔMPU) and fiscal policy uncertainty (ΔFPU) on stock returns while controlling for downside risk, lagged dividend yield, and time series patterns. Testing G7 markets consistently shows that both ΔMPU and ΔFPU have significant negative impacts on stock returns. Evidence shows that any downside risk, ΔMPU or ΔFPU in US market will soon be transmitted to G6 industrial markets and the impacts are extended to two months. These risk and uncertainty premiums should be priced in the stocks of the major industrial markets.

Efficient manpower planning has been recognized as a critical aspect for the development of an economy. In 2001, the Works Bureau of the Hong Kong SAR Government (predecessor of Environment, Transport and Works Bureau) commissioned an HKPolyU consultancy team to develop a computer‐based model to estimate the demand for different categories of construction personnel. This article presents the concept and features of the manpower demand‐forecasting model developed for the construction industry of Hong Kong. The forecasting model is formulated on the basis of the labour multiplier approach by deriving the relationship between the number of workers required and the project expenditure in the given project duration. Multipliers for 61 project types were derived for 38 labour trades using completed project data. The labour demand by occupation for each project can then be estimated by multiplying the corresponding multipliers and the estimated project expenditure. Several unique features of the model have been developed, including “normalization” and “contract cost adjustment factor”. Normalizing the labour multipliers can facilitate the prediction of occupational labour requirements at different stages of a construction project. The adjustment factor is introduced to eliminate the discrepancy between the original estimates and final contract values so as to enhance the estimation accuracy. The model can also be used to predict the number of jobs created for a given level of investment. The government can apply this model to check and compare which project types will generate most jobs before committing public money. This model could be easily adopted and adapted by foreign construction authorities while planning manpower.