• Room 02.033 - Riddel Hall Block 3

    United Kingdom

Accepting PhD Students

PhD projects

Open to PhD students in the field of behavioural economics with a special interest in social learning.


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Personal profile


Office location: Riddel Hall Block 3, Room 02.033

Research Interests

Social Learning; Strategic Formation of Coalitions and Networks

Research Statement

As a behavioural economist, my research focuses primarily on incorporating empirically sound assumptions into applicable formal economic theory.
    My main topic of interest is social learning. An individual learns from another individual’s behaviour because the behaviour is motivated by some information which is private. The process of social learning is the diffusion of the private information to all individuals through the interactions of observations, learning and choices. In numerous contexts, learning from others leads individuals to herd and herding behaviour generates social epidemics (e.g. market booms and crashes). My experimental work investigates the validity of the rational view of herding with the ultimate goal of building behavioural models of social learning.
    I have also worked on the price dynamics in parimutuel betting markets, the strategic formation of coalitions and networks, and methodological issues such as the effects of lottery-based incentives in large-scale experiments or the evaluation of Internet-based dynamic experiments.


Economic Decision Making --- Postgraduate module


Work in progress

Excessive Herding in the Laboratory: The Role of Intuitive Judgments, with Christoph March

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure


Dive into the research topics where Anthony Ziegelmeyer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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