Three New Tests of Independence That Differentiate Models of Risky Decision Making

Published Online:https://doi.org/10.1287/mnsc.1050.0404

References

  • Abdellaoui M. Parameter-free elicitation of utility and probability weighting functions. Management Sci. (2000) 46:1497–1512LinkGoogle Scholar
  • Birnbaum M. H. The nonadditivity of personality impressions. J. Experimental Psych. (1974) 102:543–561CrossrefGoogle Scholar
  • Birnbaum M. H., Marley A. A. J. Violations of monotonicity in judgment and decision making. Choice, Decision, and Measurement: Essays in Honor of R. Duncan Luce (1997) (Erlbaum, Mahwah, NJ) 73–100Google Scholar
  • Birnbaum M. H., Shanteau J., Mellers B. A., Schum D. A. Paradoxes of Allais, stochastic dominance, and decision weights. Decision Science and Technology: Reflections on the Contributions of Ward Edwards (1999a) (Kluwer Academic Publishers, Norwell, MA) 27–52CrossrefGoogle Scholar
  • Birnbaum M. H. Testing critical properties of decision making on the Internet. Psychological Sci. (1999b) 10:399–407CrossrefGoogle Scholar
  • Birnbaum M. H., Reips U.-D., Bosnjak M. A Web-based program of research on decision making. Dimensions of Internet Science (2001) (Pabst Science Publishers, Lengerich, Germany) 23–55Google Scholar
  • Birnbaum M. H. Causes of Allais common consequence paradoxes: An experimental dissection. J. Math. Psych. (2004a) 48(2):87–106CrossrefGoogle Scholar
  • Birnbaum M. H. Tests of rank-dependent utility and cumulative prospect theory in gambles represented by natural frequencies: Effects of format, event framing, and branch splitting. Organ. Behavior Human Decision Processes (2004b) 95:40–65CrossrefGoogle Scholar
  • Birnbaum M. H., Chavez A. Tests of theories of decision making: Violations of branch independence and distribution independence. Organ. Behavior Human Decision Processes (1997) 71(2):161–194CrossrefGoogle Scholar
  • Birnbaum M. H., McIntosh W. R. Violations of branch independence in choices between gambles. Organ. Behavior Human Decision Processes (1996) 67:91–110CrossrefGoogle Scholar
  • Birnbaum M. H., Navarrete J. B. Testing descriptive utility theories: Violations of stochastic dominance and cumulative independence. J. Risk Uncertainty (1998) 17:49–78CrossrefGoogle Scholar
  • Birnbaum M. H., Patton J. N., Lott M. K. Evidence against rank-dependent utility theories: Violations of cumulative independence, interval independence, stochastic, dominance, and transitivity. Organ. Behavior Human Decision Processes (1999) 77:44–83CrossrefGoogle Scholar
  • Blavatskyy P. R. Back to the St. Petersburg paradox? Management Sci. (2004) 51(4):677–678LinkGoogle Scholar
  • Camerer C. F., Ho T.-H. Violations of the betweenness axiom and nonlinearity in probability. J. Risk Uncertainty (1994) 8:167–196CrossrefGoogle Scholar
  • Gonzalez R., Wu G. Composition rules in original and cumulative prospect theory. (2003) . Working paper, Department of Psychology, University of Michigan, Ann Arbor, MIGoogle Scholar
  • Humphrey S. J. Regret aversion or event-splitting effects? More evidence under risk and uncertainty. J. Risk Uncertainty (1995) 11:263–274CrossrefGoogle Scholar
  • Kahneman D., Tversky A. Prospect theory: An analysis of decision under risk. Econometrica (1979) 47:263–291CrossrefGoogle Scholar
  • Levy M., Levy H. Prospect theory: Much ado about nothing. Management Sci. (2002) 48:1334–1349LinkGoogle Scholar
  • Luce R. D.Utility of Gains and Losses: Measurement-Theoretical and Experimental Approaches (2000) (Lawrence Erlbaum Associates, Mahwah, NJ) Google Scholar
  • Luce R. D., Fishburn P. C. Rank- and sign-dependent linear utility models for finite first order gambles. J. Risk Uncertainty (1991) 4:29–59CrossrefGoogle Scholar
  • Luce R. D., Fishburn P. C. A note on deriving rank-dependent utility using additive joint receipts. J. Risk Uncertainty (1995) 11:5–16CrossrefGoogle Scholar
  • Marley A. A. J., Luce R. D. Rank-weighted utilities and qualitative convolution. J. Risk Uncertainty (2001) 23(2):135–163CrossrefGoogle Scholar
  • Marley A. A. J., Luce R. D. Independence properties vis-à-vis several utility representations. Theory DecisionIn pressGoogle Scholar
  • Neilson W., Stowe J. A further examination of cumulative prospect theory parameterizations. J. Risk Uncertainty (2002) 24(1):31–46CrossrefGoogle Scholar
  • Quiggin J.Generalized Expected Utility Theory: The Rank-Dependent Model (1993) (Kluwer, Boston, MA) CrossrefGoogle Scholar
  • Savage L. J.The Foundations of Statistics (1954) (Wiley, New York) Google Scholar
  • Starmer C. Developments in non-expected utility theory: The hunt for a descriptive theory of choice under risk. J. Econom. Literature (2000) 38:332–382CrossrefGoogle Scholar
  • Starmer C., Sugden R. Testing for juxtaposition and event-splitting effects. J. Risk Uncertainty (1993) 6:235–254CrossrefGoogle Scholar
  • Tversky A., Fox C. R. Weighing risk and uncertainty. Psychological Rev. (1995) 102(2):269–283CrossrefGoogle Scholar
  • Tversky A., Kahneman D. Advances in prospect theory: Cumulative representation of uncertainty. J. Risk Uncertainty (1992) 5:297–323CrossrefGoogle Scholar
  • Tversky A., Wakker P. Risk attitudes and decision weights. Econometrica (1995) 63:1255–1280CrossrefGoogle Scholar
  • Wakker P. The data of Levy and Levy (2002), “Prospect theory: Much ado about nothing?” Support prospect theory. Management Sci. (2003) 49:979–981LinkGoogle Scholar
  • Wu G. An empirical test of ordinal independence. J. Risk Uncertainty (1994) 9:39–60CrossrefGoogle Scholar
  • Wu G., Gonzalez R. Curvature of the probability weighting function. Management Sci. (1996) 42:1676–1690LinkGoogle Scholar
  • Wu G., Markle A. B. An empirical test of gain-loss separability in prospect theory. (2004) . Working paper, Graduate School of Business, University of Chicago, Chicago, ILGoogle Scholar
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