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The econometric modeling of social Preferences

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  • Anna Conte

    ()
    (Strategic Interaction Group, Max-Planck-Institut für Okonomik, Jena, Germany)

  • Peter G. Moffatt

    ()
    (School of Economics, University of East Anglia, Norwich, UK)

Abstract

Experimental data on social preferences present a number of features that need to be incorporated in econometric modelling. We explore a variety of econometric modelling approaches to the analysis of such data. The approaches under consideration are: the random utility approach (in which it is assumed that each possible action yields a utility with a deterministic and a stochastic component, and that the individual selects the action yielding the highest utility); the random behavioural approach (which assumes that the individual computes the maximum of a deterministic utility function, and that computational error causes their observed behaviour to depart stochastically from this optimum); and the random preference approach (in which all variation in behaviour is attributed to stochastic variation in the parameters of the deterministic component of utility). These approaches are applied in various ways to an experiment on fairness conducted by Cappelen et al. (2007). At least two of the models that we estimate succeed in capturing the key features of the data set.

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Paper provided by Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics in its series Jena Economic Research Papers with number 2010-042.

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Date of creation: 29 Jun 2010
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Handle: RePEc:jrp:jrpwrp:2010-042

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Keywords: Econometric modelling and estimation; model evaluation; individual behaviour; fairness;

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  1. Todd L. Cherry & Peter Frykblom & Jason F. Shogren, 2002. "Hardnose the Dictator," Working Papers 02-06, Department of Economics, Appalachian State University.
  2. Anna Conte & John D Hey & Peter G Moffatt, 2007. "Mixture Models of Choice Under Risk," Discussion Papers 07/06, Department of Economics, University of York.
  3. Nicholas Bardsley & Peter Moffatt, 2007. "The Experimetrics of Public Goods: Inferring Motivations from Contributions," Theory and Decision, Springer, vol. 62(2), pages 161-193, March.
  4. Anderson, Simon P. & Goeree, Jacob K. & Holt, Charles A., 1998. "A theoretical analysis of altruism and decision error in public goods games," Journal of Public Economics, Elsevier, vol. 70(2), pages 297-323, November.
  5. Fabrizio Botti & Anna Conte & Daniela T. Di Cagno & Carlo D'Ippoliti, . "Risk attitude in real decision proBLEMs," Quaderni DEF 144, Dipartimento di Economia e Finanza, LUISS Guido Carli.
  6. Spanos, Aris, 2010. "Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification," Journal of Econometrics, Elsevier, vol. 158(2), pages 204-220, October.
  7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, April.
  8. Anna Conte & Daniela Di Cagno & Emanuela Sciubba, 2009. "Strategies in Social Network Formation," Birkbeck Working Papers in Economics and Finance 0905, Birkbeck, Department of Economics, Mathematics & Statistics.
  9. Arthur van Soest, 1995. "Structural Models of Family Labor Supply: A Discrete Choice Approach," Journal of Human Resources, University of Wisconsin Press, vol. 30(1), pages 63-88.
  10. Loomes, G. & Moffatt, P.G. & Sugden, R., 1998. "A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," University of East Anglia Discussion Papers in Economics 9806, School of Economics, University of East Anglia, Norwich, UK..
  11. Stahl, Dale II & Wilson, Paul W., 1994. "Experimental evidence on players' models of other players," Journal of Economic Behavior & Organization, Elsevier, vol. 25(3), pages 309-327, December.
  12. Nicholas Bardsley, 2000. "Control Without Deception: Individual Behaviour in Free-Riding Experiments Revisited," Experimental Economics, Springer, vol. 3(3), pages 215-240, December.
  13. Alexander W. Cappelen & Astri Drange Hole & Erik Ø Sørensen & Bertil Tungodden, 2007. "The Pluralism of Fairness Ideals: An Experimental Approach," American Economic Review, American Economic Association, vol. 97(3), pages 818-827, June.
  14. Charles Bellemare & Sabine Kröger & Arthur van Soest, 2008. "Measuring Inequity Aversion in a Heterogeneous Population Using Experimental Decisions and Subjective Probabilities," Econometrica, Econometric Society, vol. 76(4), pages 815-839, 07.
  15. Anna Conte & M. Levati, 2014. "Use of data on planned contributions and stated beliefs in the measurement of social preferences," Theory and Decision, Springer, vol. 76(2), pages 201-223, February.
  16. Miguel A. Costa-Gomes & Georg Weizs�cker, 2008. "Stated Beliefs and Play in Normal-Form Games," Review of Economic Studies, Oxford University Press, vol. 75(3), pages 729-762.
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Cited by:
  1. Anna Contea & Daniela T. Di Cagno & Emanuela Sciubbad, 2011. "Behavioural patterns in social networks," Jena Economic Research Papers 2011-060, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
  2. Alice Becker, 2013. "Accountability and the fairness bias: the effects of effort vs. luck," Social Choice and Welfare, Springer, vol. 41(3), pages 685-699, September.
  3. Luis Miller & Heiko Rauhut & Fabian Winter, 2011. "The emergence of norms from conflicts over just distributions," Jena Economic Research Papers 2011-018, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.

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