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§ 3.6.2 and 3.6.3 on two families of Bleichrodt et al. are incorrect. They are criticized by Bleichrodt et al. (2013
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| § 3.6.2 and 3.6.3 on two families of Bleichrodt et al. are incorrect. They are criticized by Bleichrodt et al. (2013 Judgment and Decision Making 8): Link to paper %}
Doyle, John R. (2013) “Survey of Time Preference, Delay Discounting Models,” Judgment and Decision Making 8, 116–135. {% Propose risk measures, characterized mostly by quasi-concavity, that can be applied both to probability-contingent and event-contingent prospects. %} Drapeau, Samuel & Michael Kupper (2013) “Risk Preferences and Their Robust Representation,” Mathematics of Operations Research 38, 28–62. {% dynamic consistency: surveys Kydland & Prescott like time inconsistency in macro-economics. %} Drazen, Allen (2000) “Political Economy in Macroeconomics.” Princeton University Press, Princeton NJ. {% %} Drechsler, Itamar (2013) “Uncertainty, Time-Varying Fear, and Asset Prices,” Journal of Finance 68, 1843–1889. {% %} Drèze, Jacques H. (1958) “Individual Decision Making under Partially Controllable Uncertainty.” Ph.D. dissertation, Columbia University. {% %} Drèze, Jacques H. (1961) “Les Fondements Logiques de l’Utilité Cardinale et de la Probabilité Subjective,” La Décision, 73–83, Paris, CNRS. {% %} Drèze, Jacques H. (1971) “Market Allocation under Uncertainty,” European Economic Review 2, 133–165. {% %} Drèze, Jacques H. (1974, ed.) “Allocation under Uncertainty: Equilibrium and Optimality.” MacMillan, London. {% risky utility u = transform of strength of preference v, haven’t checked if latter doesn’t exist %} Drèze, Jacques H. (1982) “The Marginal Utility of Income Does Not Increase. Comment.” Core Discussion paper 8231, Louvain-La-Neuve. {% state-dependent utility; P. 15 has example where consequences are act-dependent. The letters of Savage and Aumann are in Appendix 2.A. %} Drèze, Jacques H. (1987) “Essays on Economic Decision under Uncertainty.” Cambridge University Press, Cambridge. {% Reconsidering the beautiful work by Drèze on state dependence and moral hazard. %} Drèze, Jacques H. & Aldo Rustichini (1998) “State Dependent Utility and Decision Theory.” In Salvador Barberà, Peter J. Hammond, & Christian Seidl (eds.) Handbook of Utility Theory, Vol. 1, Principles, 839–895, Kluwer Academic Publishers, Dordrecht. {% Put together models on preferences between conditioned acts such as Fishburn (1973), Luce & Krantz (1971) and, in particular, Drèze’s moral hazard. %} Drèze, Jacques H. & Aldo Rustichini (1999) “Moral Hazard and Conditional Preferences,” Journal of Mathematical Economics 31, 159–181. {% This paper studies risk sensitivity in bargaining. That is, how the solution is affected by changes in risk attitudes. More precisely, it assumes the AA framework and considers both risk attitudes, through the vNM utility function where, here, EU is assumed, and ambiguity attitudes, through a nonadditive weighting function. In this, it assumes exactly Schmeidler’s (1989) RDU model. The Nash bargaining solution has no clear results and mostly things can go any way. This paper follows up on Köbberling & Peters (2003). For ambiguity, they use the Ghirardato & Marinacci (2002) comparative results giving pointwise dominance fo capacities. %} Driesen, Bram, Michele Lombardi, & Hans Peters (2016) “Feasible Sets, Comparative Risk Aversion, and Comparative Uncertainty Aversion in Bargaining,” Journal of Mathematical Economics 67, 162–170. {% This paper reconsiders the Holt & Laury (2002) measurement of risk attitudes. I have always been unhappy that Holt & Laury simply assumed expected utility, ignoring for instance the contrary evidence of the Nobel-awarded prospect theory—Holt & Laury cite prospect theory but only for some irrelevant details. Many experimental economists followed Holt & Laury, and one reason for the popularity of their paper is that it provided an excuse to ignore oceans of critical and preceding literature from behavioral economics. The present paper puts everything in the right place, with many nice sentences. The authors make clear that choice lists were used long before Holt & Laury, and cite the important Cohen, Jaffray, & Said (1987). P. 89: “This observation about MPLs is well known to experts in the field of risk preference elicitation, and yet in our experience, it is not well known to newcomers or those outside the field.” P. 90 footnote 1: “The word “multiple” in multiple price list is redundant since the word “list” already implies repetitive choices. Nevertheless, we adopt the phrasing MPL in this paper as it is more commonly used in the literature than other variants such as “choice list.” ” P. 91: “In what follows, we show that H&L’s original MPL is, perhaps ironically, not particularly well suited to measuring the traditional notion of risk preferences — the curvature of the utility function. Rather, it is likely to provide a better approximation of the curvature of the probability weighting function. P. 93 2nd para gives a reason: the amount involved are too moderate to capture much utility curvature. %} Drichoutis, Andreas C. & Jayson L. Lusk (2016) “What Can Multiple Price Lists Really Tell Us about Risk Preferences?,” Journal of Risk and Uncertainty 53, 89–106. {% %} Driesen, Bram, Andres Perea, & Hans J.M. Peters (2010) “On Loss Aversion in Bimatrix Games,” Theory and Decision 68, 376–391. {% %} Driesen, Bram, Andres Perea, & Hans J.M. Peters (2011) “The Kalai-Smorodinsky Bargaining Solution with Loss Aversion,” Mathematical Social Sciences 61, 58–64. {% Use the elegant Shalev model of loss aversion to redo the Rubinstein bargaining solution, establishing the solution and providing results on it being (un)favorable to be loss averse. %} Driesen, Bram, Andrés Perea, & Hans Peters (2012) “Alternating Offers Bargaining with Loss Aversion?,” Mathematical Social Sciences 64, 103–118. {% %} Driessen, Theo S.H. (1988) “Cooperative Games, Solutions and Applications.” Kluwer Academic Publishers, Dordrecht. {% Uses Choquet integral (RDU) for pricing European exchange options involving uncertain strikes under uncertainty. %} Driouchi, Tarik, Lenos Trigeorgis, & Yongling Gao (2015) “Choquet-Based European Option Pricing with Stochastic (and Fixed) Strikes,” OR Spectrum 37, 787–802. {% %} Dror, Itiel E., Beth Basola, & Jeromy R. Busemeyer (1999) “Decision Making under Time Pressure: An Independent Test of Sequential Sampling Models,” Memory & Cognition 27, 713–725. {% utility families parametric %} Dror, Moshe & Bruce C. Hartman (1994) “Stopping Rules for St. Petersburg Gamble: Utility Functions and Stochastic Dynamic Programming Framework.” {% DC = stationarity: the author distinguishes them. %} Drouhin, Nicolas (2009) “Hyperbolic Discounting may be Time Consistent,” Economics Bulletin 29, 2549–2555. {% In the model considered, a time consistency can be satisfied iff the probability transformation is a power function, which is related to multiplicative is (Yaari 1965 additive) interaction with the hazard rate. %} Drouhin, Nicolas (2015) “A Rank-Dependent Utility Model of Uncertain Life Time,” Journal of Economic Dynamics and Control 53, 208225. {% P. 32: “the literature suggests that all analysts would be willing to include estimates discounted at 5% per annum” P. 33, near bottom: “economists are more frequently being asked to construct confidence intervals around their cost estimates, as is commonly done for the clinical outcome variables.” %} Drummond, Michael F., Arno Brandt, Bryan R. Luce, & Joan Rovira (1993) “Standardizing Methodologies for Economic Evaluation in Health Care,” International Journal of Technology Assessment in Health Care 9, 26–36. {% statistics for C/E; use moment method to estimate variance of Cauchy distribution (which is infinite!?!?) %} Drummond, Michael F. & Bernie J. O’Brien (1992) “Clinical Importance, Statistical Significance and the Assessment of Economic and Quality-of-Life Outcomes,” Health Economics 2, 205–212. {% Health related MAU scales; discount rate in cost-effectiveness and cost-benefit analysis for health should agree with “current practice” or be the government recommended rate. Note: this claim involves discounting of money!!!! History of QALYs. Seem to consider SG as gold standard for utility measurement (SG gold standard). %} Drummond, Michael F., Gregg L. Stoddart, & George W. Torrance (1987) “Methods for the Economic Evaluation of Health Care Programmes.” Oxford University Press, Oxford; 2nd edn. 1997. Drummond, Michael F., Bernie J. O’Brien, Gregg L. Stoddart, & George W. Torrance (1997) “Methods for the Economic Evaluation of Health Care Programmes; 2nd edn. Oxford University Press, Oxford.
Drynan, Ross G. (1981) “Risk Attitudes amongst Australian Farmers; Comment,” Australian Journal of Agricultural Economics 25, 73–76. {% Real incentives: use hypothetical choice; Measure ambiguity attitudes for gains versus losses (manipulated by putting the benchmark for supposed managerial decision above or below all outcomes considered), when ambiguity is modeled the usual way through events and “vague probabilities” versus when ambiguity is modeled deviating from conventions through ambiguous outcomes (ambiguous outcomes vs. ambiguous probabilities), and when ambiguity is modeled through separate evaluation of prospects through certainty equivalents (pseudo-pairwise choice, PPC, modeled as the choice for the option with the higher certainty equivalent) or when it is modeled through joint evaluation in direct pairwise choice (PC). Ambiguity is generated by giving probability intervals, and they also measure the effect of interval range. P. 1797 1st para of 2nd column: strangely enough, subjects are risk seeking. ambiguity seeking for losses: this they find. Subjects are ambiguity averse for gains but ambiguity seeking for losses (p. 1797 2nd column), although the latter is not significantly different from ambiguity neutrality (p. 1798 Table 3). Pp. 1798-1799: people get more ambiguity averse for gains if ambiguity increases (so larger probability intervals), and more ambiguity seeking for losses if ambiguity increases, although the effect for losses is smaller than the effect for gains. Table 5 displays choices from straight choice. Interesting is the middle left matrix, which considers a classical preference reversal for ambiguity. Unfortunately, the data are not clear and may be mostly noise. In the upper row of people preferring ambiguity in pairwise choice (PC) exactly half prefers ambiguity in pseudo-pairwise choice. In the lower row of people preferring unambiguous in PC, some more, 60%, prefers unambiguous in PCC, but this difference apparently is not significant. reflection at individual level for ambiguity: no data because gains-losses was between subjects. loss aversion without mixed prospects and/or loss aversion: erroneously thinking it is reflection: : p. 1800 2nd column 2nd para erroneously suggests that loss aversion can play a role in their data on losses. This paper has no mixed prospects and, hence, loss aversion can play no role at all. %} Du, Ning & David V. Budescu (2005) “The Effects of Imprecise Probabilities and Outcomes in Evaluating Investment Options,” Management Science 51, 1791–1803. {% anonymity protection %} du Feu, Chris (2006) “Biodiversity for Beginners,” Teaching Statistics 28, 66–70. {% DOI: http://dx.doi.org/10.1287/mnsc.2013.1758 Discuss ways to derive risk aversion indexes and risk premiums from finance data. %} Duan, Jin-Chuan & Weiqi Zhang (2014) “Forward-Looking Market Risk Premium,” Management Science 60, 521–538. {% Discuss in detail how important it is to separately identify utility and discount rates (and uncertainty) and how difficult that is. They use stated (hypothetical introspective, equated with the cardinal intertemporal utility function) questions to elicit utility. %} Dubé, Jean-Pierre, Günter J. Hitsch & Pranav Jindal (2014) “The Joint Identification of Utility and Discount Functions from Stated Choice Data: An Application to Durable Goods Adoption,” Quantitative Marketing and Economics 12, 331–377. {% finite additivity %} Dubins, Lester E. & Leonard J. Savage (1965) “How to Gamble if You Must.” Dover Publications, New York. Retitled 1976: “Inequalities for Stochastic Processes.” {% %} Dubois, Didier (1988) “Possibility Theory: Searching for Normative Foundations.” In Bertrand R. Munier (ed.) Risk, Decision and Rationality, 601–614, Reidel, Dordrecht. {% %} Dubois, Didier, Lluís Godo, Henri Prade, & Adriana Zapico (1999) “On the Possibilistic Decision Model: From Decision under Uncertainty to Case-Based Decision,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 7, 631–670. {% About insurance in low development countries %} Dubois, Pierre, Bruno Jullien, & Thierry Magnac (2008) “Formal and Informal Risk Sharing in LDCs: Theory and Empirical Evidence,” Econometrica 76, 679–725. {% %} Dubois, Didier, Endre Pap, & Henri Prade (1999) “Hybrid Probabilistic-Possibilistic Mixtures and Utility Functions,” Université Paul Sabbatier. {% %} Dubois, Didier & Henri Prade (1988) “Default Reasoning and Possibility Theory,” Artificial Intelligence 35, 243–257. {% survey on nonEU; updating: %} Dubois, Didier & Henri Prade (1988) “Modelling Uncertainty and Inductive Inference: A Survey of Recent Non-Additive Probability Systems,” Acta Psychologica 68, 53–78. {% %} Dubois, Didier & Henri Prade (1988) “Fuzzy Measures: Fuzzy Integral Approach.” In Madan G. Singh (ed.) Systems & Control Encyclopedia; Theory, Technology, Applications, 1821–1822, Pergamon, New York. {% That fuzzy sets are still awaiting operationalization %} Dubois, Didier & Henri Prade (1989) “Fuzzy Sets, Probability, and Measurement,” European Journal of Operational Research 40, 135–154. {% %} Dubois, Didier & Henri Prade (1990) “Probability Theory in Artificial Intelligence. A Review of “Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference,” by Judea Pearl,” Journal of Mathematical Psychology 34, 472–482. {% Discusses Dempster’s rule for combining evidence, discusses three-prisoners problem, and distinguishes between information and evidence. %} Dubois, Didier & Henri Prade (1992) “Evidence, Knowledge and Belief Functions,” International Journal of Approximate Reasoning 6, 295–319. {% Focusing: conditioning beforehand; learning: conditioning after. %} Dubois, Didier & Henri Prade (1994) “Focusing versus Updating in Belief Function Theory.” In Ronald R. Yager, Janusz Kacprzyk, & Mario Fedrizzi (eds.) Advances in the Dempster-Shafer Theory of Evidence, Wiley, New York.. {% Explain that probabilities, or other degrees of belief, cannot be modeled as multi-valued logic (degree of truth). The reason is that the degree of belief of a composition of propositions is not determined only by the degree of belief of the separate propositions. They refer to de Finetti (1936) who made the same point, and discuss many historical misunderstandings. %} Dubois, Didier & Henri Prade (2001) “Possibility Theory, Probability Theory and Multiple-Valued Logics: A Clarification,” Annals of Mathematics for Artificial Intelligence 32, 35–66. {% Presented at FUR in Oslo, with the strong evidence of anchoring biases and other things. %} Dubourg, W. Richard, Michael W. Jones-Lee, & Graham Loomes (1997) “Imprecise Preferences and the WTP-WTA Disparity,” Journal of Risk and Uncertainty 9, 115–133. {% Presented at FUR in Oslo; contains the experiment with the different starting point of a wheel affecting WTP to an extreme extent. Starting the wheel at 25 pound gives a WTP of, if I remember right, about 100 pound, starting the wheel at 75 gives a WTP of about 180 pound. This is not just anchoring because the resulting answers differ greatly from the starting values. Maybe it is that the participants want to ask five times for increases of the initial value but not more. %} Dubourg, W. Richard, Michael W. Jones-Lee, & Graham Loomes (1997) “Imprecise Preferences and Survey Design in Contingent Valuation,” Economica 64, 681–702. {% Generalizes the bivariate additive representation without additivity of Ok & Masatlioglu (2007) “A Theory of (Relative) Discounting,” by allowing the first component not to refer to real numbers but to a separable connected compact topological space. A natural conjecture is that both components need only be connected. Only considers positive first coordinates, so monotonicity in time. %} Dubra, Juan (2009) “A Theory of Time Preferences over Risky Outcomes,” Journal of Mathematical Economics 45, 576–588. {% Considers mixture set of probability distributions over a finite set. Shows that (usual, weak) forms of continuity hold if and only if completeness holds. Cites the related Schmeidler (1971, Econometrica). %} Dubra, Juan (2011) “Continuity and Completeness under Risk,” Mathematical Social Sciences 61, 80–81. {% completeness-criticisms; Argue that it is natural to first determine preferences in simple situations (“core preferences”), then extend them to more complex through, for example, independence condition %} Dubra, Juan & Efe A. Ok (2002) “A Model of Procedural Decision Making in the Presence of Risk,” International Economic Review 43, 1053–1080. {% completeness-criticisms; Take vNM axioms with its least convincing one dropped. This least convincing one is completeness. Prove that then there is a set of utility functions such that one prospect is preferred to the other if and only if EU prescribes so for every utility function in the set. That is, there should be unanimous EU agreement. A very pretty result, of which it is amazing that it had not been discovered before. The probable reason that it had not been discovered before is that Aumann (1962) raised confusions about it, because Aumann claimed the result in his text without really having it. %} Dubra, Juan, Fabio Maccheroni, & Efe A. Ok (2004) “Expected Utility without the Completeness Axiom,” Journal of Economic Theory 115, 118–133. {% Seems that they define a bi-order between sets and that that is very close to triple cancellation etc. %} Ducamp, André & Jean-Claude Falmagne (1969) “Composite Measurement,” Journal of Mathematical Psychology 6, 359–390. {% Treats the Ky Fan metric on L0 which amounts to the Sugeno integral. Referred to by Denneberg (1994). %} Dudley, Richard M. (1989) “Real Analysis and Probability.” Wadsworth and Brooks/Cole, Pacific Grove. {% information aversion: for genetic diseases such as Huntington’s disease people can have themselves tested but there is no cure for the disease. For example, if your father has it you have .5 probability of also having it. Some want to have that test, others really do not want to know if they have the bad gene. %} DudokdeWit, A. Christine (1997) “To Know or not to Know; The Psychological Implications of Presymptomatic DNA Testing for Autosomal Dominant Inheritable Late Onset Disorders,” Ph.D. dissertation, Erasmus University, Rotterdam, the Netherlands. {% information aversion: for genetic diseases such as Huntington’s disease people can have themselves tested but there is no cure for the disease. For example, if your father has it you have .5 probability of also having it. Some want to have that test, others really do not want to know if they have the bad gene. %} DudokdeWit, A. Christine, E.Johanna Meijers-Heijboer, Aad Tibben, et al. (1994) “Effect on a Dutch Family of Predictive DNA-Testing for Hereditary Breast and Ovarian Cancer,” Lancet 344, 197. {% Seems to have introduced habit formation. %} Duesenberry, James (1952) “Income, Saving, and the Theory of Consumer Behavior.” Harvard University Press, Cambridge, MA. {% %} Duffie, Darrell & Larry G. Epstein (1991) “Stochastic Differential Utility,” Econometrica 60, 353–394. {% probability elicitation: applied to experimental economics %} Dufwenberg, Martin & Uri Gneezy (2000) “Measuring Beliefs in an Experimental Lost Wallet Game,” Games and Economic Behavior 30, 163–182. {% Nash equilibrium discussion %} Dufwenberg, Martin & Johan Linden (1996) “Inconsistencies in Extensive Games,” Erkenntnis 45, 103–114. {% %} Dugundji, James (1966) “Topology.” Allyn and Bacon, Boston. {% anonymity protection %} Duncan, George T. & Diane Lambert (1986) “Disclosure-Limited Data Dissemination,” Journal of the American Statistical Association 81, 10–28. {% Total utility theory; Greater Detroit area, housewives in 1955 and 1971 gave same experienced utility scores to income although real income had increased by 42% in 1971; compare Easterlin (1974) %} Duncan, Otis D. (1975) “Does Money Buy Satisfaction?,” Social Indicators Research II, 267–274. {% %} Duncker, Karl (1941) “On Pleasure, Emotion, and Striving,” Philosophy and Phenomenological Research 1, 391–430. {% finite additivity; IV.2.12, p. 240: the set of simple functions is supnorm-dense in the set of all measurable bounded functions. %} Dunford, Nelson & Jacob T. Schwartz (1958) “Linear Operators, Part I.” Interscience Publishers, New York. {% PT, applications, loss aversion, downward-sloping labor supply: on overtime puzzle, which is an application of loss aversion. Data of over 2,000 workers in seven labor markets. Their tradeoffs between labor time and income kind at their current position, as loss aversion predicts. P. 449 2nd column: workers are prepared to give up substantially more leisure to prevent a loss of income than to gain the equivalent amount of income. I did not find, in my superficial reading, similar statements about the labor time dimension. %} Dunn, Lucia F. (1996) “Loss Aversion and Adaptation in the Labour Market: Empirical Indifference Functions and Labour Supply,” Review of Economics and Statistics 78, 441–450. {% Asymmetric information in rational-agent framework can lead to similar phenomena as loss aversion %} Dupont, Dominique Y. & Gabriel S. Lee (2002) “The Endowment Effect, Status Quo Bias and Loss Aversion: Rational Alternative Explanation,” Journal of Risk and Uncertainty 25, 87–101. {% conservation of influence; text that exchanging goods (or at least money) does not produce utility. “There is a cancellation; no utility is produced.” (Cited by Stigler, 1950, Footnote 36). %} Dupuit, Jules (1934) “De l’Utilité et de sa Mesure.” La Fiforma Sociale, Torino (reprint of papers of 1844 and 1849) {% common knowledge; French/American philosophers; ascribes invention of CK to David Lewis %} Dupuy, Jean-Pierre (1989) “Common Knowledge, Common Sense,” Theory and Decision 27, 37–62. {% equity-versus-efficiency: seems to be on it %} Durante, Ruban, Louis Putterman, & Joël J. van der Weele (2014) “Preferences for Redistribution and Perception of Fairness: An Experimental Study,” Journal of the European Economic Association 12, 1059–1086. {% survey on nonEU: useful survey of different ways to model uncertainty for multicriteria decision making, including decision analysis, fuzzy sets, and so on. %} Durbach, Ian N. & Theodor J. Stewart (2012) “Modeling Uncertainty in Multi-Criteria Decision Analysis,” European Journal of Operational Research 223, 1–14. {% natural-language-ambiguity: seems to argue that tolerance of ambiguity (in general natural-language sense) is not so much related to individual personality traits but rather is a situation-dependent/content-specific expression of psychological stress. %} Durrheim, Kevin (1998) “The Relationship between Tolerance of Ambiguity and Attitudinal Conservatism: A Multidimensional Analysis,” European Journal of Social Psychology 28, 731–753. {% %} Dutt, Samir K. & Gerd M. Welke (2015) “A CAPM for Prospect Theory,” working paper. {% %} Dutt, Varun, Horacio Arló-Costa, Jeffrey Helzner, & Cleotilde Gonzalez (2014) “The Description–Experience Gap in Risky and Ambiguous Gambles,” Journal of Behavioral Decision Making 27, 316–327. {% Measure ambiguity aversion twice (Ellsberg 3-color), two months in between, and find 57% stability, more than under randomness—but less than if back-to-back (75%). %} Duersch, Peter, Daniel Römer, & Benjamin Roth (2017) “Intertemporal Stability of Uncertainty Preferences,” Journal of Economic Psychology 60, 7–20. {% Axiomatization of poverty measures that depend on past poverty. %} Dutta, Indranil, Laurence Roope, & Horst Zank (2013) “On Intertemporal Poverty Measures: The Role of Affluence and Want,” Social Choice and Welfare 41, 741–762. {% %} Dutta, Jayasri & Stephen Morris (1997) “The Revelation of Information and Self-Fulfilling Beliefs,” Journal of Economic Theory 73, 231–244. {% Seem to find evidence for quasi-convexity w.r.t. probabilistic mixing , supporting convex probability weighting in RDU. Seems that subjects get the option to delegate their choice to an external device to avoid making decisions, and use this option. %} Dwenger, Nadja, Dorothea Kübler, & GeorgWeizsäcker (2015) “Flipping a coin: Theory and Evidence.” WZB Discussion Paper, No. SP II 2013-201r. {% gender differences in risk attitudes: find, as do other studies, that women are more risk averse than men. The authors write many things that are provocative for emancipation. Guess they wrote it tongue in cheek. For example, they write that the difference is partly (though not completely), due to knowledge disparity. So, women know less about the market!? In the conclusion, they suggest that, for women’s best interest, they better not manage their own retirement investments. Oh well …!?!? %} Dwyer, Peggy D., James H. Gilkeson, & John A. List (2002) “Gender Differences in Revealed Risk Taking: Evidence from Mutual Fund Investors,” Economics Letters 76, 151–158. {% utility elicitation; show that if joint distribution of returns and available assets is known, vNM utility can be recovered from assets demands. %} Dybvig, Philip & Herakles M. Polemarchakis (1981) “Recovering Cardinal Utility,” Review of Economic Studies 48, 159–166. {% %} Dyckerhoff, Rainer (1994) “Decomposition of Multivariate Utility Functions in Non-Additive Expected Utility Theory,” Journal of Multi-Criteria Decision Analysis 3, 41–58. {% %} Dyckerhoff, Rainer (1993) “Choquet-Erwartungsnutzen und Anticipiertern Nutzen. Ein Beitrag zur Entscheidungstheorie bei Einem und Mehreren Attributen,” PhD Dissertation, Universität der Bundeswehr Hamburg. {% %} Dyckerhoff, Rainer & Karl C. Mosler (1993) “Stochastic Dominance with Nonadditive Probabilities,” Methods and Models of Operations Research 37, 231–256. {% utility elicitation %} Dyckman, Thomas R. & Roberto Salomon (1972) “Empirical Utility Functions and Random Devices: An Experiment,” Decision Science 3, 1–13. {% %} Dyer, Douglas, John H. Kagel, & Dan Levin (1989) “A Comparison of Naive and Experienced Bidders in Common Value Offer Auctions: A Laboratory Analysis,” Economic Journal 99, 108–115. {% They start from a proposition being acceptable as soon as its probabilitye exceeds some threshold, discuss problems and paradoxes coming from it, with contributions by Kyburg. %} Douven, Igor & Timothy Williamson (2006) “Generalizing the Lottery Paradox,” British Journal for the Philosophy of Science 57, 755–779. {% Discusses AHP (analytical hierarchy process)-model, followed by comments %} Dyer, James S. (1990) “Remarks on the Analytic Hierarchy Process,” Management Science 36, 249–258. {% %} Dyer, James S., Thomas Edmunds, John C. Butler, & Jianmin Jia (1998) “A Multiattribute Utility Analysis of Alternatives for the Disposition of Surplus Weapons-Grade Plutonium,” Operations Research 46, 749–762. {% %} Dyer, James S., Peter C. Fishburn, Ralph E. Steuer, Jyrki Wallenius, & Stanley Zionts (1992) “Multiple Criteria Decision Making, Multiattribute Utility Theory: The Next Ten Years,” Management Science 38, 645–654. {% %} Dyer, James S. & Jianmin Jia (2000) “Decision Making under Ambiguous Risk,” {% %} Dyer, James S. & Rakesh K. Sarin (1978) “On the Relationship between Additive Conjoint and Difference Measurement,” Journal of Mathematical Psychology 15, 270–272. {% %} Dyer, James S. & Rakesh K. Sarin (1979) “Measurable Multiattribute Value Functions,” Operations Research 27, 810–822. {% risky utility u = transform of strength of preference v, latter doesn’t exist %} Dyer, James S. & Rakesh K. Sarin (1979) “Group Preference Aggregation Rules Based on Strenght of Preference,” Management Science 25, 822–832. {% risky utility u = transform of strength of preference v ; Download 7.23 Mb. Share with your friends:
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