Charting the Type Space—The Case of Linear Public Good Experiments

43 Pages Posted: 4 Jul 2022 Last revised: 23 Dec 2022

See all articles by Christoph Engel

Christoph Engel

Max Planck Institute for Research on Collective Goods; University of Bonn - Faculty of Law & Economics; Erasmus University Rotterdam (EUR), Erasmus School of Law, Rotterdam Institute of Law and Economics, Students; Universität Osnabrück - Faculty of Law

Carina Ines Hausladen

ETH Zürich - Department of Humanities, Social and Political Sciences (GESS)

Marcel Schubert

Max Planck Institute for Research on Collective Goods

Abstract

Behaviour in economic games is not only noisy. One has reason to believe that heterogeneity is patterned. A prominent application is the linear public good. It is widely accepted that choices result from participants holding discernible types. Proposed types, like freeriders or conditional cooperators, are intuitive. But the composition of the type space is neither theoretically nor empirically settled. In this paper, we leverage machine learning methods to chart the type space. We use simulation to understand what can be achieved with machine learning. We rely on these insights to find clusters in a large (N = 12,414) set of experimental data points from public good games. We discuss ways in which these clusters could be rationalized.

Keywords: repeated public goods game, heterogeneity, type space, machine learning, clustering, reaction functions

Suggested Citation

Engel, Christoph and Hausladen, Carina Ines and Schubert, Marcel, Charting the Type Space—The Case of Linear Public Good Experiments. Available at SSRN: https://ssrn.com/abstract=4153371 or http://dx.doi.org/10.2139/ssrn.4153371

Christoph Engel (Contact Author)

Max Planck Institute for Research on Collective Goods ( email )

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University of Bonn - Faculty of Law & Economics

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Erasmus University Rotterdam (EUR), Erasmus School of Law, Rotterdam Institute of Law and Economics, Students ( email )

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Universität Osnabrück - Faculty of Law

Osnabruck, D-49069
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Carina Ines Hausladen

ETH Zürich - Department of Humanities, Social and Political Sciences (GESS) ( email )

Stampfenbachstrasse 48
Zürich, 8006
Switzerland

Marcel Schubert

Max Planck Institute for Research on Collective Goods ( email )

Kurt-Schumacher-Str. 10
D-53113 Bonn, 53113
Germany

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