Speaker: Prof Tom Wilkening – (Optima/Melbourne University)

Bio:

Tom Wilkening is Professor of Economics at the University of Melbourne. His areas of research are in experimental economics, behavioural economics, and market design. In his research, Professor Wilkening explores how to design markets, matching systems, auctions, and economic institutions in environments where behavioural biases and inexperience may affect how people make decisions. His research combines experimental economics with theory to understand how markets evolve and to understand the role the government and private sector might play to improve them.

Professor Wilkening’s research has been published in the top general interest and field journals in his field including The American Economic Review, The Journal of Political Economy, The Journal of Economic Literature, The Journal of the European Economic Association, Management Science, The Journal of Public Economics, The Journal of Economic Theory, and Experimental Economics. His work has attracted significant support by the Australian research Council through a Discovery Early Career Research Award, a Discovery Grant, and a Future Fellowship Award. He is on the editorial boards of Experimental Economics and the Journal of the Economic Science Association.

Professor Wilkening is the director of MACTCH lab at the University of Melbourne, which combines market design with experimental economics and computer science to develop real-world matching systems and combinatorial exchanges. He leads a branch of the lab that investigates how combinatorial exchanges can be used to help farmers in developing countries consolidate fragmented landholdings.

Abstract:

Agriculture in low-income countries is characterised by misallocation of land across farmers and by fragmentation — the division of farms into smaller plots—which increases costs and limits farmers’ ability to adopt technologies with increasing returns. We explore whether a trading platform that enables conditional land swaps can help farmers address these challenges. Theoretically, combinatorial bidding can thicken markets, reduce exposure to risk, and facilitate coordination among traders. However, implementing such a platform presents two optimisation challenges. First, from an algorithmic perspective, determining both the set of winning bids and the prices at which plots should be traded requires solving constraint-based optimisation problems quickly enough to support near-continuous-time trading.

Second, from a user perspective, package bidding can make it difficult for farmers to identify mutually beneficial trades and formulate effective bids. We discuss our approaches to solving and scaling the underlying optimisation problems, as well as our ongoing work on bid suggestion mechanisms designed to help farmers identify and execute mutually beneficial trades.

This event is Hybrid:
JOIN VIA ZOOM – MEETING ID: 873 1557 5255; PASSWORD: 778635
Level 8, Room 8109, Melbourne Connect

SEMINAR: WED 28 OCTOBER 2026 4.00PM-5.00PM (AEST, Melbourne Time)