Disparity between residual valuation and actual transaction price in the land sale programme : a case study of Hong Kong

Abstract

This study focuses on investigating the disparity between the valuation using the residual valuation method documented in the HKIS Guidance Notes on Valuation of Development Land (RV) and the actual transaction prices (TP) in the Land Sale Programme of Hong Kong, with a particular emphasis on residential land sales. The residual valuation method is a widely adopted means of estimating the land value by deducting the total development cost, which includes construction cost, marketing, and professional fees, and the developer’s profit, from the gross development value. Since the RV so derived is only an estimation of TP and may not fully capture all the factors that affect the highest bid made by the winning developer, it is unlikely that it will coincide with TP. If the disparity between RV and TP is not a random error and can be explained by observable factors, incorporating these factors into the residual valuation method can improve its accuracy in predicting the TP. The primary objective of this study is to investigate the factors that influence the bidding behavior of the developers and how they contribute to the disparity between RV and TP. Based on the findings obtained, the study would then examine the effect of different project variables and market dynamics on the implied developer's profit (IP). It intends to develop residual valuation guidelines that can improve the accuracy of residual valuation of vacant land. To achieve these objectives, the study employs a two-stage quantitative analysis framework. Since previous studies suggest that land sale mechanisms may influence the TP, only tender-based transactions of residential land between 2012/2013 and 2021/2022 will be used in the study. In Regression Model 1, the empirical results demonstrate that project duration and yield have a significant negative effect on TP. Inversely, interest rate and market sentiment have positive relationships with it. In addition, gross floor area (GFA) demonstrates a non-linear impact. It initially correlates positively with TP but exhibits a negative effect beyond a critical threshold. In Regression Model 2, the empirical results exhibit a significant positive relationship between GFA and IP, as well as a significant negative relationship between market sentiment and IP. Although the coefficients of project duration and yield demonstrate a positive effect on IP while that of interest rate indicates a negative effect, their correlations are not statistically significant. To assess the study's effectiveness in improving residual valuation accuracy, the mean absolute percentage error (MAPE) is examined. For residual valuations employing the fixed percentage of the developer’s profit approach (typically 15% to 20%), the MAPE is 14.04%. By considering duration, yield, interest rate, GFA, and market sentiment in valuation, and dynamically adjusting the IP, the MAPE drops to 11.86%. Therefore, adopting the empirical findings of this study improves valuation accuracy by 15.5%. Through identifying the factors that contribute to the disparity between RV and TP, the study offers practical recommendations for surveyors, developers, and policymakers who participate in the Land Sale Programme, enhancing the current residual valuation method and bidding strategies.