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Keynes Fund

 

Summary of Project Plan


In many contexts, individuals make decisions without full knowledge of the rewards from the available alternatives. Faced with this uncertainty, they experiment and also try and learn from the experience of proximate others.

The experiments individuals undertake, the information that these choices generate, and its social diffusion, are consequently a matter of first order importance. This process has a bearing on a wide array of social, economic and political questions. In recent years, the growth of large scale social media platforms has generated practical interest in understanding the learning process in large evolving networks. In particular, a great deal of interest has centred on the possibility of shaping opinion and human behavior through relatively low cost planting/seeding of ideas that are then widely diffused through social networks. The fear that false information may take hold in a population has given rise to the popularity of the term ‘fake news’. As a result, in the popular imagination, there appears to be a close connection between the rise of the large scale networks and the prevalence of fake news.

Our goal is to develop a better understanding of the process of social learning in large scale social networks. We propose to do this by conducting experiments with human subjects. The proposal studies a setting in which individuals form links and build networks and then use these networks to share information. Our interest is in understanding how the economic environment shapes the formation of the social networks and how the structure of the network in turn shapes the social learning process. We then examine the circumstances under which individuals can be misled – through a combination of network formation and poor learning – into choosing the wrong action through deliberate intervention by an external party.

Two aspects of the proposal are innovative: one, we will conduct large scale experiments on social learning that will involve up to 100 subjects, and two, we will study the formation of networks and the diffusion of information on networks within a common framework.

 

Project Output


Networks: An Economics Approach Book Cover

Networks: An Economics Approach, Sanjeev Goyal, MIT Press, (2023)

Description: An accessible and comprehensive overview of the economic theory and the realities of networks written by a pioneering economics researcher.

Networks are everywhere: the infrastructure that brings water into our homes, the social networks made up of our friends and families, the supply chains connecting cities, people, and goods. These interconnections contain economic trade-offs: for example, should an airline operate direct flights between cities or route all its flights through a hub? Viewing networks through an economics lens, this textbook considers the costs and benefits that govern their formation and functioning.

Networks are central to an understanding of the production, consumption, and information that lie at the heart of economic activity. Sanjeev Goyal provides advanced undergraduate and graduate students with an accessible and comprehensive introduction to the economics research on networks of the past twenty-five years. Each chapter introduces a theoretical model illustrated with the help of case studies and formal proofs. After introducing the theoretical concepts, Goyal examines economic networks, including infrastructure, security, market power, and financial networks. He then covers social networks, with chapters on coordinating activity, communication and learning, information networks, epidemics, and impersonal markets. Finally, Goyal locates social and economic networks in a broader context covering networked markets, economic development, trust, and group networks in their relation to markets and the state.

https://mitpress.mit.edu/9780262048033/networks/

 

 

Prof. Sanjeev Goyal

 

Professor Sanjeev Goyal is Professor of Economics, at the Faculty of Economics, University of Cambridge. His research interests are in Economic Theory, Networks.

 

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