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Processing Data from Social Dilemma Experiments: A Bayesian Comparison of Parametric Estimators

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Author Info

  • Klaus Moeltner

    ()
    (Department of Resource Economics, University of Nevada, Reno)

  • James J. Murphy

    ()
    (Department of Resource Economics & Center for Public Policy and Administration, University of Massachusetts-Amherst)

  • John K. Stranlund

    (Department of Resource Economics, University of Massachusetts-Amherst)

  • Maria Alejandra Velez

    (Center for Research on Environmental Decisions, Columbia University)

Abstract

Observed choices in Social Dilemma Games usually take the form of bounded integers. We propose a doubly-truncated count data framework to process such data. We compare this framework to past approaches based on ordered outcomes and truncated continuous densities using Bayesian estimation and model selection techniques. We find that all three frameworks (i) support the presence of unobserved heterogeneity in individual decision-making, and (ii) agree on the ranking of regulatory treatment effects. The count data framework exhibits superior efficiency and produces more informative predictive distributions for outcomes of interest. The continuous framework fails to allocate adequate probability mass to boundary outcomes, which are often of pivotal importance in these games.

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File URL: http://www.business.unr.edu/econ/wp/papers/UNRECONWP07013.pdf
File Function: First version, 2007
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Bibliographic Info

Paper provided by University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics in its series Working Papers with number 07-013.

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Length: 51 pages
Date of creation: Dec 2007
Date of revision:
Handle: RePEc:unr:wpaper:07-013

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Related research

Keywords: Social dilemma games; Hierarchical modeling; Bayesian simulation; Common property resource;

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Cited by:
  1. Klaus Moeltner & James J. Murphy & John K. Stranlund & Maria Alejandra Velez, 2012. "Institutional Heterogeneity in Social Dilemma Games: A Bayesian Examination," Working Papers 2012-04, University of Alaska Anchorage, Department of Economics.

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