UK Data Service data catalogue record for:

Dispositional free riders do not free ride on punishment: Experimental data

Title details

SN: 853250
Title: Dispositional free riders do not free ride on punishment: Experimental data
Persistent identifier: 10.5255/UKDA-SN-853250
Depositor: Simon Gaechter, University of Nottingham
Principal investigator(s): Gaechter, S, University of Nottingham
Sponsor(s): Economic and Social Research Council
Grant number: ES/K002201/1
Other acknowledgements: Till Weber
Ori Weisel


The citation for this study is:

Gaechter, S. (2018). Dispositional free riders do not free ride on punishment: Experimental data. [data collection]. UK Data Service. SN: 853250,

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Abstract copyright data collection owner.

Strong reciprocity explains prosocial cooperation by the presence of individuals who incur costs to help those who helped them (‘strong positive reciprocity’) and to punish those who wronged them (‘strong negative reciprocity’). Theories of social preferences predict that in contrast to ‘strong reciprocators’, self-regarding people cooperate and punish only if there are sufficient future benefits. Here, we test this prediction in a two-stage design. First, participants are classified according to their disposition towards strong positive reciprocity as either dispositional conditional cooperators (DCC) or dispositional free riders (DFR). Participants then play a one-shot public goods game, either with or without punishment. As expected, DFR cooperate only when punishment is possible, whereas DCC cooperate without punishment. Surprisingly, dispositions towards strong positive reciprocity are unrelated to strong negative reciprocity: punishment by DCC and DFR is practically identical. The ‘burden of cooperation’ is thus carried by a larger set of individuals than previously assumed.

This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change; to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.

Coverage, universe, methodology

Dates of fieldwork: 31 December 2012 - 28 February 2014
Country: United Kingdom
Observation units: Individuals
Kind of data: Alpha-numeric
Method of data collection: We conducted the experiments between November 2012 and February 2014. We recruited 184 students at the University of Nottingham without prior experience in public goods experiments (101 females, average age = 19.84, SD = 2.14), using the recruitment software ORSEE64. The sample size was determined in expectation of heterogeneity in cooperative dispositions and to ensure a minimum number of participants from each type.

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Administrative and access information

Date of release:
First edition: 06 July 2018
Latest edition: 06 July 2018 (minor amendments only)
Copyright: Simon Gaechter, University of Nottingham
Access conditions: The Data Collection is available from an external repository. Access is available via Related Resources.
Availability: UK Data Service
Contact: Simon Gaechter, University of Nottingham


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