This paper introduces a principal-agent analysis of the public sector decisions made by a non-democratic planning body under public scrutiny. The central idea is that divergence between the interests of the principal (citizens), whose objective is to maximize the total value of the land in Hong Kong, and the agent (planning approval authority), whose concern is about Approval Risk, which is the agent's risk of being accused of collusion or even bribery. This principal-agent analysis can be applied to any public-sector decision-making process in a society with the rule of law and freedom of speech. It was found by a logit analysis of 1440 sets of disaggregate data that planning applications by non-profit applicants for uses in Government/Institution/Community (GIC) zones were more likely to be approved than those by for-profit private organizations, in line with the idea of a lower perceived Approval Risk. Amongst the applications by private organizations, proposed high-value land uses were less likely to be approved than those proposed for low-value uses, probably because the former results in potentially higher economic gain for the applicants. The legislative change that took effect in July 2005 has allowed a wider public participation in the planning application process. This policy change was used in this study as a test condition for the effect on planning approvals of an increase in the principal's involvement in the decision-making process. It was found that the policy change did increase the success rate of planning applications made by private organizations, though the impact was mainly on the applications for low-value land uses only. The empirical result shows that the perceived Approval Risk for high-value land uses was too high to be affected by the policy change.
|Early online date||29 Mar 2023|
|Publication status||E-pub ahead of print - 29 Mar 2023|
Bibliographical noteThe authors are thankful to our Research Assistant Mr. Ronald K.K. Yu for data collection and processing.
- Planning applications
- Principal-agent problem
- Approval risk
- Logistic regression
- Pseudo R2
- Land use
- Community use