Y. H. Chiang

Modeling Construction Occupational Demand: Case of Hong Kong

Appropriate training can only be developed if training needs for specific skills are carefully identified. This paper, further to an aggregate model developed previously, aims to forecast the occupational share of the aggregate manpower demand for the construction industry of Hong Kong. The forecast, based on existing manpower statistics, is divided into two levels: broad occupations and detailed occupations. The broad occupational demand forecasting model is formulated using a time-series regression analysis to derive the relationship between the occupational share and the construction output cycle, technology, and various work-mix variables; whereas exponential smoothing technique is used to forecast the share of detailed occupations. This occupational demand estimation can provide solid information to facilitate manpower planning. It enables the policymakers to foresee the trends of occupational manpower demand and formulate policies and training and retraining programs tailored to deal effectively wit...

FORECASTING CONSTRUCTION MANPOWER DEMAND: AN ECONOMETRIC MODEL

Manpower forecast has become an important management tool for decision makers and policy makers to match and structure the skills of the workforce. National planners are also increasingly aware that the competitiveness and growth of the nation, as well as its social welfare, depend in no small degree on the full exploitation of the skills of its people. However, there is very limited research in establishing a comprehensive manpower demand forecasting model in construction. This paper aims to present the framework of an advanced econometric model for estimating the manpower demand in construction. Vector error correction modeling, regression analysis and exponential smoothing technique were applied to develop the relationships between manpower demand and the relevant variables in the construction industry. The forecasting models developed can benefit the construction industry by providing critical information on the future construction manpower requirements and assist policy makers and training planners to formulate training strategies. Apart from this practical use, the research also contributes new knowledge and a solid framework to the area of manpower forecasting and planning.