A study of corruption using the Institutional Analysis and Development framework with an application to the bidding phase of infrastructure procurement

Infrastructure projects are particularly vulnerable to corruption due to the complexity of processes and relationships between private and public entities, and the large-value contracts involved. Corrupt agreements can affect any phase of an infrastructure project, and the outcomes include reduced competition, poor-quality construction or infrastructure that does not meet value-for-money criteria. This PhD thesis brings together insights from economics, sociology and psychology to develop a broad framework of corruption with the focus on individuals, their actions and the settings in which corruption occurs. This framework is then applied to the bidding phase of physical infrastructure procurement. The method used to consolidate and analyse disparate theories and models of corruption across different disciplines is Elinor Ostrom’s Institutional Analysis and Development framework. Key variables of the corruption phenomenon are identified and organised using the IAD framework, and two models are developed. The first is a game-theoretic model analysing the importance of social networks and trust between corrupt partners and the intermediaries who facilitate corrupt exchanges. The second is a simulation model of decision-making processes in corrupt agreements based on a conflict of social norms and individual self-interest. The second model proposes a method of linking legitimacy of institutions, group behaviour status quo, and social network connections, with selfseeking behaviour. Case studies are then developed based on documents filed to support prosecutions under the US Foreign Corrupt Practices Act 1977. The proposed methods of corruption reduction are based on organisational controls and collectiveaction methods

Simulating water markets with transaction costs

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. KEY POINTS: Transaction tracking hydro-economic optimization models simulate water markets. Proposed model formulation incorporates transaction costs and trading behavior. Water markets benefit users with the most restricted water access