Optimal Height Of Land Development – An Economic Perspective
Abstract Sky-scrapers are rising in the panorama of big modern cities more and more often, becoming a symbol of dynamic growth and prestige. High-rise development appears to be an answer to the expanding demand for new residential and commercial space as urban land prices continue to go up and the availability of land decreases. This article aims to identify factors affecting the choice of optimal building height in the context of economic effectiveness. It also presents factors that determine the implementation of high-rise development projects. Given the complexity of this subject matter, emphasis is placed on its economic dimension.
Determining Optimal Building Height
The paper examines how building height is determined in the absence of building height regulatory restrictions. A model is developed for determining optimal height using simple neo-classical economic analysis; this is then tested using empirical data from Hong Kong. The results show that the observed building heights are consistent with the optimal height predicted by the model. In addition, it was also found that the point of optimality varied positively with the quality of the external environment. An important practical implication is that town planners and policy-makers can make use of the model as a benchmarking tool to assess and quantify the effect of imposing or relaxing height restrictions.
On the issue of plan shape complexity: plan shape indices revisited
Plan shape indices are based on the geometry of the plan shape rather than on empirical data, and are problematic as they embrace implicit assumptions that are not tested empirically nor justified theoretically. Empirical research using data in Hong Kong confirms that these plan shape indices are much poorer predictors of unit construction costs than the variables used to construct the indices. This study also develops a method for constructing a plan shape index that is free from the unjustified assumptions implicit in existing plan shape indices; it involves an empirical cost model. Different functional specifications of the cost models are tested. The result rejects the linear model and other special case models such as semi-log and log-linear models. However, the reciprocal model is not rejected. This result suggests that a linear plan shape index can predict the amount of floor area that can be constructed with a fixed sum of money better than the construction cost per floor area.