`Stochastically more risk averse': a contextual theory of stochastic discrete choice under risk
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Publication:737885
DOI10.1016/j.jeconom.2009.10.012zbMath1441.62903OpenAlexW2056139070MaRDI QIDQ737885
Publication date: 12 August 2016
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://mpra.ub.uni-muenchen.de/11851/1/MPRA_paper_11851.pdf
Related Items (29)
Expected utility theory and inner and outer measures of loss aversion ⋮ Fechner's strong utility model for choice among \(n > 2\) alternatives: risky lotteries, savage acts, and intertemporal payoffs ⋮ Noise and bias in eliciting preferences ⋮ Uncertainty and binary stochastic choice ⋮ Probability weighting and L-moments ⋮ Explaining deviations from equilibrium in auctions with avoidable fixed costs ⋮ When is coarseness not a curse? Comparative statics of the coarse random utility model ⋮ Varieties of risk preference elicitation ⋮ Loss aversion ⋮ Testing the TASP: an experimental investigation of learning in games with unstable equilibria ⋮ Does risk aversion explain behavior in a lemon market? ⋮ Empirical underidentification in estimating random utility models: The role of choice sets and standardizations ⋮ Probabilistic subjective expected utility ⋮ Harmonic choice model ⋮ Beyond fictitious play beliefs: incorporating pattern recognition and similarity matching ⋮ Which decision theory? ⋮ Inferring beliefs as subjectively imprecise probabilities ⋮ Estimation of social preferences in generalized dictator games ⋮ Overbidding and overspreading in rent-seeking experiments: cost structure and prize allocation rules ⋮ Knowing me, imagining you: projection and overbidding in auctions ⋮ Behavior in the centipede game: a decision-theoretical perspective ⋮ Probabilistic risk aversion with an arbitrary outcome set ⋮ The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity ⋮ Stronger utility ⋮ A Bayesian method for characterizing population heterogeneity ⋮ An axiomatic foundation of conditional logit ⋮ Do people maximize quantiles? ⋮ Asymmetric noise and systematic biases: a new look at the trade-off method ⋮ Future plans and errors
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