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- Tradeoff method’s error propagation
- Tradeoff method
- Risk averse for gains, risk seeking for losses
- R.C. Jeffrey model updating
SEU = risk: p. 539 writes that Savage (1954) called the conceptual difference between known and unknown probabilities into question, in the sense that his axioms imply the existence of subjective probabilities and that the agent treats these in the same way as objective probabilities. %} Dekel, Eddie, Barton L. Lipman, & Aldo Rustichini (1998) “Recent Developments in Modeling Unforeseen Contingencies,” European Economic Review 42, 523–542. {% Correction in their 2007 paper. Text up to p. 901 (§2) gives nice general introduction on Kreps’ (1979) preference for flexibility but interpreted as Kreps’ (1992) unforeseen contingencies. %} Dekel, Eddie, Barton L. Lipman, & Aldo Rustichini (2001) “Representing Preferences with a Unique Subjective State Space,” Econometrica 69, 891–934. {% In their 2001 paper, independence is too strong and continuity too weak. %} Dekel, Eddie, Barton L. Lipman, & Aldo Rustichini (2007) “Representing Preferences with a Unique Subjective State Space: A Corrigendum,” Econometrica 75, 591–600. {% A generalization of Gul & Pesendorf temptation. %} Dekel, Eddie, Barton L. Lipman, & Aldo Rustichini (2009) “Temptation-Driven Preferences,” Review of Economic Studies 76, 937–971. {% game theory for nonexpected utility & dynamic consistency: use recursive utility, giving up RCLA %} Dekel, Eddie, Zvi Safra, & Uzi Segal (1991) “Existence and Dynamic Consistency of Nash Equilibrium with Non-expected Utility Preferences,” Journal of Economic Theory 55, 229–246. {% %} Dekel, Eddie & Suzanne Scotchmer (1990) “Collusion through Insurance: Sharing the Cost of Oil Spill Cleanups,” American Economic Review 80, 249–252. {% survey on belief measurement: in developing countries. %} Delavande, Adeline, Xavier Giné, & David McKenzie (2011) “Measuring Subjective Expectations in Developing Countries: A Critical Review and New Evidence,” Journal of Development Economics 94, 151–163. {% This paper provides an expected utility axiomatization for decision under risk, extending the von Neumann-Morgenstern axiomatization to nonsimple prospects. Several preceding axiomatizations used conditions implying continuity of utility. This paper provides results that do not require continuity of utility. As pointed out by Spinu & Wakker (2012), more general results, neither using continuity of utility, had been obtained before by Fishburn (1975, Annals of Statistics, Theorem 3 = Fishburn’s 1982 monograph, Theorem 3.4), Kopylov (2010 JME), and Wakker (1993, MOR, Theorem 3.6). An appealing feature ofTheorem 1 in this paper, obtaining expected utility on the set of all probability distributions by no more than the usual weak ordering, independence, and Archimedeanity, and then stochastic dominance, is that it can be stated entirely in elementary terms, unlike the preceding references. It does imply boundedness of utility. %} Delbaen, Freddy, Samuel Drapeau, & Michael Kupper (2011) “A von Neumann-Morgenstern Representation Result without Weak Continuity Assumption,” Journal of Mathematical Economics 47, 401–408. {% Seems that he considered capacities that are convex transformations of additive measures (law-invariant). %} Delbaen, Freddy (1974) “Convex Games and Extreme Points,” Journal of Mathematical Analysis and Applications 45, 210–233. {% Comments on version of Feb. 2014. Subjects pay a prior endowment to invest in a financial option continuously and deterministically growing over time. However, at some random time point the option will expire and lose all value, and this is very probable to happen before some time so one can’t wait too long. Subjects must decide how long to wait before exercising the option. There is a basic treatment with a fixed expiration rate, and then there are two uncertain treatments where the expiration rate with 0.5 probability is favorable (small) and with 0.5 probability is unfavorable. In treatment 2, the risky treatment, subjects are told about the 0.5 probability. In treatment 3, the ambiguous treatment, subjects are not told that this probability is 0.5 and it is unknown to them. In the risky treatment, subjects may want to wait longer and do later exercise because they can learn about the expiration rate as time proceeds. (I am not sure if I really understand this. Once you waited long and things went well, you will wait more, but couldn’t you be scared at the very beginning and more quickly exercise? Will depend much on the particular rates chosen.) In the ambiguous treatment, ambiguity aversion is predicted in this paper to lead to earlier exercise because that gives certainty, and ambiguity aversion means going more for certainty. The latter the authors derive for the maxmin multiple priors model assuming Bayesian prior-by-prior updating. (P. 26 writes: “Apart from the maxmin specification, there are alternative ways to model ambiguity aversion but we have no reason to expect that our qualitative predictions would change by using other transformations on the set of priors.”) Here learning apparently does not have the same effect as with risk, or, maybe, ambiguity aversion adds the opposite effect. An experiment confirms the risky prediction but not the ambiguous one. To explain, the authors cite literature questioning universal ambiguity aversion. What may play a role is that each subject did the decision 10 times. In the ambiguous case they could learn about the unknown probability of previous times. The authors model learning within each of the 10 times, but not between these 10 times if I understand right. The paper concludes with the desirability of more future research. %} Della Seta, Marco, Sebastian Gryglewicz, & Peter M. Kort (2014) “Willingness to Wait under Risk and Ambiguity,” working paper. {% %} Dellacherie, Claude (1970) “Quelques Commentaires sur les Prolongements de Capacités,” Seminaire de Probabilités V Strasbourg, (Lecture Notes in Mathematics 191), Springer Verlag, Berlin. {% time preference. Uses Total utility theory of Kahneman et al. %} Dellaert, Benedict G.C. & Barbara E. Kahn (1999) “How Tolerable is Delay? Consumers’ Evaluations of Internet Web Sites after Waiting,” Journal of Interactive Marketing 13, 41–54. {% Paper surveys behavioral-economics models in risky choice, intertemporal choice, social preferences, overconfidence, choice from menus, with some more framing effects. It focuses on a detailed discussion of a limited nr. of empirical studies, being field studies. P. 318: in beta-delta model, beta captures self-control problems. %} DellaVigna, Stefano (2009) “Psychology and Economics: Evidence from the Field,” Journal of Economic Literature 47, 315–372. {% %} DellaVigna, Stefano & Marco LiCalzi (2000) “Learning to Make Risk Neutral Choices in a Symmetric World,” Mathematical Social Sciences 41, 19–37. {% %} DellaVigna, Stefano & Ulrike Malmendier (2004) “Contract Design and Self-Control: Theory and Evidence,” Quarterly Journal of Economics 119, 353–402. {% %} Delnoij, Diana M.J., Jack B.F. Hutten, Corina C. Ros, Peter P. Groenewegen, Roland D. Friele, Eloy van de Lisdonk, & Dinny H. de Bakker (1999) “Effecten van Eigen Bijdragen in het Ziekenfonds in Nederland,” Tijdschrift voor Gezondheidswetenschappen 77, 406–412. {% SG higher than CE %} Delquié, Philippe (1993) “Inconsistent Trade-Offs between Attributes: New Evidence in Preference Assessment Biases,” Management Science 39, 1382–1395. {% %} Delquié, Philippe (1997) “ “Bi-Matching”: A New Preference Assessment Method to Reduce Compatibility Effects,” Management Science 43, 640–658. {% error theory for risky choice: in devising tradeoff-stimuli in multiattribute settings, it is useful to consider which sizes of tradeoffs will lead to minimal errors in the parameters of interest. Should think about the response errors, but also in the “leverage,” which means how much the parameter of interest is sensitive to a response error. P. 108 (Tradeoff method’s error propagation): often the response error (in an absolute sense?) will increase with tradeoff size, but the leverage will decrease. This is a useful observation for the error-propagation problem in the TO-method. %} Delquié, Philippe (2003) “Optimal Conflict in Preference Assessment,” Management Science 49, 102–115. {% value of information Takes it in the EU-LaValle sense, of EU increase generated. There are not many clear relations with risk aversion and so on. This paper does find some regularities. Usually the value of info decreasing in preference intensity. %} Delquié, Philippe (2008) “The Value of Infrmation and Intensity of Preference,” Decision Analysis 49, 129–139. {% %} Delquié, Philippe (2008) “Valuing Information and Options: An Experimental Study,” Journal of Behavioral Decision Making 21, 91–109. {% Under linear-exponential (CARA) utility, utility is bounded above. Hence there is, for every probability, a loss threshold that cannot be made up by an infinite utility even. This provides an interpretation of risk tolerance. Table 1 gives results. %} Delquié, Philippe (2008) “Interpretation of the Risk Tolerance Coefficient in Terms of Maximum Acceptable Loss,” Decision Analysis 5, 5–9. {% Assume a prospect x = (p1:x1,…,pn:xn). The authors assume that x is kind of compared to an independent replica. If the subject evaluates xi, he thinks that it could have been xj with probability pj. Thus he evaluates the prospect by (using my notation) i=1;n piU(xi) + i=1;n pi(j=1;n pjD(U(xj) U(xi))) where in the second summation D(U(xj) U(xi)) is the disappointment of haven gotten just xi and not xj. If xi is in fact better than xj then it is negative disappointment, so it is elation. The authors use a different symbol E for the disappointment function defined on its negative domain. It is natural that in disappointment emotions all other possible outcomes float around in the mind of the decision maker. biseparable utility: for the most common D, that is piecewise linear with a kink at 0. %} Delquié, Philippe & Alessandra Cillo (2006) “Disappointment without Prior Expectation: A Unifying Perspective on Decision under Risk,” Journal of Risk and Uncertainty 33, 197–215. {% %} Delver, Robert, Herman Monsuur, & Ton J.A. Storcken (1991) “Ordering Pairwise Comparison Structures,” Theory and Decision 31, 75–94. {% DOI: http://dx.doi.org/10.1016/j.paid.2009.04.013 gender differences in risk attitudes: no difference %} Demaree, Heath A., Michael A. DeDonno, Kevin J. Burns, Pavel Feldman, & D. Erik Everhart (2009) “Trait Dominance Predicts Risk-Taking,” Personality and Individual Differences 47, 419–422. {% Discuss questionaires to measure optimism/pessimism; Find that optimism is not inverse of pessimism; they are more or less independent entities. %} Dember, William N., Stephanie H. Martin, Mary K. Hummer, Steven R. Howe, & Richard S. Melton (1989) “The Measurement of Optimism and Pessimism,” Current Psychology: Research & Reviews 8, 102–119. {% That we perceive things relative to status quo/neutral level of well-being (though it seems to relate more to a physical sense than otherwise). In reality we apprehend nothing for certain, but only as it changes according to the condition of our body and of the things that impinge upon or offer resistence to it. %} Kirk, Geoffrey S. & John E. Raven (1957) “The Pre-Socrates Philosophers.” P. 422, Cambridge University Press, Cambridge. {% %} Dempster, Arthur P. (1967) “Upper and Lower Probabilities Induced by a Multivalued Mapping,” Annals of Mathematical Statistics 38, 325–339. {% foundations of statistics %} Dempster, Arthur P. (1997) “The Direct Use of Likelihood for Significance Testing,” Statistics and Computing 7, 247–252. (Originally published in 1973). {% %} Demuynck, Thomas (2009) “Absolute and Relative Time-Consistent Revealed Preferences,” Theory and Decision 66, 283–299. {% Apply revealed-preference techniques to Nash Bargaining and so on. %} Demuynck, Thomas & Luc Lauwers (2009) “Nash Rationalization of Collective Choice over Lotteries,” Mathematical Social Sciences 57, 1–15. {% DC = stationarity: distinguish the conditions well, and have longitudinal data to properly test for DC (dynamic consistency) also. This paper is in this regard a paticularly clean version of what was also done by Halevy (2015). The authors use the term dynamic consistency for what Halevy calles time consistency, the term age independence (which would in fact be my preference also, were it not that the conventions in the field have gone differently and are beyond return) for Halevy’s vague term time invariance, and the term stationarity is the same way as Halevy’s. The field has by now (2017) converged on Halevy’s terminology. This paper does more, by comparing individual decisions with group decisions, where it again does a clean job showing that group communication (and not repeated choice or other-regarding preferences) decreases impatience and inconsistencies. %} Denant-Boemont, Laurent, Enrico Diecidue, Olivier l’Haridon (2017) “Patience and Time Consistency in Collective Decisions,” Experimental Economics 181–208. {% %} Denayer, Lieve, Myriam Welkenhuysen, Gerry Evers-Kiebooms, Jean-Jacques Cassiman, & Herman Van den Berhe (1997) “Risk Perception after CF Carrier Testing and Impact of the Test Result on Reproductive Decision Making,” American Journal of Medical Genetics 69, 422–428. {% In Dutch. Propagates the Tradeoff method, in general multiattribute setting, for consultancy purposes. real incentives/hypothetical choice: propagates the use of hypothetical choice to reveal client’s preferences, because these can give precisely the data needed. %} Deneffe, Daniel (2003) “Waarvoor Wil de Klant Betalen,” Industrie Magazine (September), 20. Link to paper
Deneffe, Daniel & Peter P. Wakker (1996) “Mergers, Strategic Investments and Antitrust Policy,” Managerial and Decision Economics 17, 231–240. Link to paper
Denes-Raj, Veronika & Seymour Epstein (1994) “Conflict between Intuitive and Rational Processes: When People Behave against Their Better Judgment,” Journal of Personality and Social Psychology 66, 819–829. {% SIIA/IIIA %} Denicolò, Vincenzo (2000) “Independence of Irrelevant Alternatives and Consistency of Choice,” Economic Theory 15, 221–226. {% %} Denicolò, Vincenzo & Marco Mariotti (2000) “Nash Bargaining Theory, Nonconvex Problems and Social Welfare Orderings,” Theory and Decision 48, 351–358. {% %} Denneberg, Dieter (1988) “On Non-Expected-Utility Preferences,” paper presented at 4th FUR conference, Budapest, 1988. {% %} Denneberg, Dieter (1990) “Premium Calculation: Why Standard Deviation Should Be Replaced by Absolute Deviation,” ASTIN Bulletin 20, 181–190. {% Proposition 3.1: nice equivalent formulations of comonotonicity; P. 19: gives nice reference to Hardy, Littlewood & Pòlya (1934) with term “similarly ordered” for comonotonicity. %} Denneberg, Dieter (1990) “Subadditive Measure and Integral,” Preprint 39, Universität Bremen, Dept. Mathematik/Informatik. Presented at 5th FUR conference, Duke University, Durham, NC USA. {% %} Denneberg, Dieter (1992) “Lectures on Non-Additive Measure and Integral,” Preprint 42, Fachbereich Mathematik/Informatik, Universität Bremen, Germany. {% First draft, November 1992, Fachbereich Mathematik/Informatik, Universität Bremen, Germany. Grabisch (2016) is a follow-up in a similar spirit. %} Denneberg, Dieter (1994) “Non-Additive Measure and Integral.” Kluwer Academic Publishers, Dordrecht. {% updating %} Denneberg, Dieter (1994) “Conditioning (Updating) Non-Additive Measures,” Annals of Operations Research 52, 21–42. {% %} Denneberg, Dieter (1997) “Representation of the Choquet Integral with the -Additive Möbius Transform,” Fuzzy Sets and Systems 92, 139–156. {% conditioning and product measures for capacities %} Denneberg, Dieter (2002) “Conditional Expectation for Monotone Measures, the Discrete Case,” Journal of Mathematical Economics 37, 105–121. {% %} Denneberg, Dieter & Michel Grabisch (1999) “Interaction Transform of Set Functions over a Finite Set,” Information Sciences 121, 149–170. {% %} Denneberg, Dieter & Michel Grabisch (2004) “Measure and Integral with Purely Ordinal Scales,” Journal of Mathematical Psychology 48, 15–27. {% Analyzes optimal design of lotteries for RDU participants. Finite prizes can only be under implausible utility and probability weighting. Continuum of prizes can well be, under inverse-S probability weighting. %} Dennery, Charles & Alexis Direr (2014) “Optimal Lottery,” Mathematical Social Sciences 55, 15–23. {% conservation of influence: social sciences takes intentional rather than physical stance. %} Dennett, Daniël C. (1987) “The Intentional Stance.” MIT Press, Cambridge MA. {% %} Dennett, Daniel C. (1995) “Darwin’s Dangerous Idea. Evolution and the Meanings of Life.” Simon and Schuster. {% free-will/determinism. Seems to argue that there is no real difference between “real randomness” and quasi-randomness, in the same way as there is no real difference between “real free will” and quasi-free will. Wrote on it since 1980s. %} Dennett, Daniël C. (2003) “Freedom Evolves.” Viking Penguin, London. {% Combining several non-independent belief functions. %} Denoeux, Thierry (2008) “Conjunctive and Disjunctive Combination of Belief Functions Induced by Non Distinct Bodies of Evidence,” Artificial Intelligence 172, 234–264. {% Show that Yaari’s 1987 representation is dual to vNM EU. %} Dentcheva, Darinka & Andrzej Ruszczynski (2013) “Common Mathematical Foundations of Expected Utility and Dual Utility Theories,” SIAM Journal on Optimization 23, 2381–405. {% Gives general definitions of higher-order absolute risk aversion, extending previous work by Chiu. %} Denuit, Michel M. & Louis Eeckhoudt (2010) “A General Index of Absolute Risk Attitude,” Management Science 56, 712–715. {% one-dimensional utility: linex family (part of Bell’s one-switch family) is only one that satisfies particular Ross-type strong risk aversion conditions everywhere. %} Denuit, Michel M., Louis Eeckhoudt, & Harris Schlesinger (2013) “When Ross Meets Bell: The Linex utility Function,” Journal of Mathematical Economics 49, 177–182. {% Optimal risk sharing. %} Denuit, Michel & Jan Dhaene (2012) “Convex Order and Comonotonic Conditional Mean Risk Sharing,” Insurance: Mathematics and Economics 51, 265–270. {% %} Denuit, Michel, Jan Dhaene, Marc Goovaerts, Rob Kaas, & Roger Laeven (2006) “Risk Measurement with Equivalent Utility Principles,” Statistics and Decisions 24, 1–26. {% %} Deschamps, Robert & Louis Gevers (1978) “Leximin and Utilitarian Rules: A Joint Characterization,” Journal of Economic Theory 17, 143–163. {% %} Deschamps, Robert & Louis Gevers (1979) “Separability, Risk-Bearing and Social Welfare Judgements.” In Jean-Jacques Laffont (ed.) Aggregation and Revelation of Preferences, Ch. 8, 145–160, North-Holland, Amsterdam. {% Should rare diseases get priority in C/E (cost-effectiveness) analyses? This was asked to Norwegian doctors, and to the general public. Doctors, rationally I think, did not want prioritizing the rare diseases, but the general pubic did. Doctors did want to leave a little budget for the rare diseases, and did not want the budget to go entirely to the more frequent disease with more cost-effective treatment. %} Desser, Arna S. (2013) “Prioritizing Treatment of Rare Diseases: A Survey of Preferences of Norwegian Doctors,” Social Science and Medicine 94, 56–62. {% Seem to find that people are not willing to spend more money on rare diseases if the opportunity costs (non-rare-disease treatments lost) are specified. %} Desser Arna S., Dorte Gyrd-Hansen, Jan A. Olsen, Sverre Grepperud, & Ivar S. Kristiansen (2010) “Societal Views on Orphan Drugs: Cross Sectional Survey of Norwegians Aged 40 to 67,” British Medical Journal 341, c4715. {% %} Detsky, Allan S. (1993) “Guidelines for Economic Analysis of Pharmaceutical Products: A Draft Document for Ontario and Canada,” PharmacoEconomics 3, 354–361. {% foundations of probability: popular book on invention of probability, from correspondence of Pascal and Fermat (1654), Christiaan Huygens, Johan de Witt, up to Black & Scholes. %} Devlin, Keith (2008) “The Unfinished Game.” Basic Books, New York. {% Propose to handle states worse than death in TTO by interspersing some duration with positive health state at the beginning, so that the overall utilities are always positive, and test it. %} Devlin, Nancy J., Aki Tsuchiya, Ken Buckingham, & Carl Tilling (2011) “A Uniform Time Trade Off Method for States Better and Worse than Dead: Feasibility Study of the ‘Lead Time’ Approach,” Health Economics 20, 348–361. {% %} Dewdney, Alexander K. (1993) “200% of Nothing. An Eye-Operning Tour through the Twists and Turns of Math Abuse and Innumeracy.” Wiley, New York. {% %} Dhaene, Jan, Michel Denuit, Marc J. Goovaerts, Rob Kaas, & David Vyncke (2002) “The Concept of Comonotonicity in Actuarial Science and Finance: Theory,” Insurance: Mathematics and Economics 31, 3–33. {% %} Dhaene, Jan, Roger J.A. Laeven, Steven Vanduffel, Grzegorz Darkiewicz, & Marc J. Goovaerts (2008) “Can a Coherent Risk Measure Be too Subadditive?,” Journal of Risk and Insurance 75, 365–396. {% Assume random variables X1,…,Xn with some joint distribution that is assumed hard to analyze, and consider their sum. They are maximally correlated, and their sum is most risky, if they are taken to be comonotonic (Theorem 1, p. 258). Hence, under risk aversion, a comonotonic combination of the marginals gives a worst-case approximation. The authors demonstrate analytical advantages, taking the Xj as incomes over several years, and considering criteria as maximization of probability of reaching some target (the “termunal wealth problem,” p. 254) or maximizing the 1‑p quantile (the “p-target capital,” p. 277), or maximization of integral over the lowest p-part of the distribution etc. for investment problems (conditional left-tail expectation). %} Dhaene, Jan, Steven Vanduffel, Marc J. Goovaerts, Rob Kaas, & David Vyncke (2005) “Comonotonic Approximations for Optimal Portfolio Selection Problems,” Journal of Risk and Insurance 72, 253–300. {% Give survey of risk measures, and how those can be modeled through RDU. %} Dhaene, Jan, Steven Vanduffel, Marc J. Goovaerts, Rob Kaas, & David Vyncke (2004) “Solvency Capital, Risk Measures and Comonotonicity: A Review,” Research Report OR 0416, Dept. of Applied Economics, K.U. Leuven. {% %} Dhami, Sanjit (2016) “Foundations of Behavioral Economic Analysis.” Oxford University Press, Oxford. {% Given small fees, under EU it is optimal to evade tax. Prospect theory can explain that people still pay tax. %} Dhami, Sanjit & Ali al-Nowaihi (2007) “Why Do People Pay Taxes,” Journal of Economic Behavior and Organization 64, 171–192. {% Find that a model with prospect theory for taxpayers and EU for government best explains phenomena related to tax. Nice for the view that PT is descriptive and EU is normative. %} Dhami, Sanjit & Ali al-Nowaihi (2010) “Optimal Taxation in the Presence of Tax Evasion: Expected Utility versus Prospect Theory,” Journal of Economic Behavior and Organization 75, 313–337. {% Becker argued, based on EU, that punishment of crimes works best if the the punishment is maximized while probability of punishment may get very small. The authors show similar things under RDU and PT, where the overestimation of small probabilities will add. %} Dhami, Sanjit & Ali al-Nowaihi (2012) “An Extension of the Becker Proposition to Non-Expected Utility Theory,” Mathematical Social Sciences 65, 10–20. {% A cardinal version of Arrow giving utilitarianism. %} Dhillon, Amrita & Jean-François Mertens (1999) “Relative Utilitarianism,” Econometrica 67, 471–498. {% Subjects trade state-contingent payments in an experimental market. They get a prize conditional on an event, either a chance event with know probability 0.5, or an event about temperature exceeding some value in some city. The temperature was always the median, although subjects did not know this. In one treatment, subjects indicated about which cities they were knowledgeable, in the other not. If subjects understood arbitrage, all market probabilities would satisfy the laws of probability. Subjects may pay more for gambling on an ambiguous event than on a chance event, not because they are ambiguity seeking, but because they consider the ambiguous event more likely, especially if they are knowledgeable. Hence just testing that is not good. The author, properly, always takes the price for a gamble on an event PLUS the price on its complement, thus avoiding likelihood effects as mentioned and truly testing ambiguity attitudes. Subjects paid most for ambiguous events they were knowledgeable about (ambiguity seeking), more than for random events, and paid more for the latter than for ambiguous events they were not knowledgeable about. This confirms the competence effect of Heath & Tversky (1991). As explained by the author, it also implies arbitrage opportunities. %} Di Mauro, Carmela (2008) “Uncertainty Aversion vs. Competence: An Experimental Market Study,” Theory and Decision 64, 301–331. {% In Voluntary Contribution Mechanism games, ambiguity aversion may be an explanation for deviations from classical models rather than other-regarding preferences. %} Di Mauro, Carmela & Massimo Finocchiaro Castro (2011) “Kindness, Confusion, or … Ambiguity?,” Experimental Economics 14, 611–633. {% all hypothetical. N = 84. Ambiguity through 2nd order probability. Table 6: to some extent ambiguity seeking for losses (because anchoring and adjustment model, which is inverse-S, does by far the best) reflection at individual level for ambiguity: only losses so does not consider it. %} Di Mauro, Camela & Anna Maffioletti (1996) “An Experimental Investigation of the Impact of Ambiguity on the Valuation of Self-Insurance and Self-Protection,” Journal of Risk and Uncertainty 13, 53–71. {% losses from prior endowment mechanism: subjects receive £10 as prior endowment, and then are faced with a risk of losing these £10 again, and can ”insure” against it. This term insure is NOT used in the instructions for the subjects. It is described to them as “reduce this potential loss to zero.” In one treatment they receive probabilities of loss, in second it is said that an expert has guessed a probability, in a third an expert has expressed an interval of probabilities, and in a fourth (“SOP”) the probability is mean of second-order probability distribution. Difficulty with second treatment may be that there is no full control of belief, and a regression to the mean (0.5) can be expected because of absence of control for beliefs, and not because of ambiguity attitude, in the same way as this occurs in studies by Einhorn & Hogarth. They interpret the second-order probabilities treatment as more probabilistic information and less ambiguity than the expert-judgment treatment, but find no significant differences in the data (though they discuss nonsignificant trends). ambiguity seeking for losses: find this for high probabilities ambiguity seeking for unlikely: they find the reflected effect; i.e., ambiguity aversion for unlikely losses. Find ambiguity neutrality for intermediate probabilities (0.20 to 0.50). reflection at individual level for ambiguity: only losses so does not consider it. %} Di Mauro, Camela & Anna Maffioletti (2001) “The Valuation of Insurance under Uncertainty: Does Information about Probability Matter?,” Geneva Papers on Risk and Insurance Theory 26, 195–224. {% ambiguity seeking for losses: Study ambiguity attitudes for gains and losses (comparing gambles with known probabilities to those with unknown). Ambiguity means second-order distributions. Use WTP questions. For losses they have, in fact, regular CE (certainty equivalent) questions and there their findings agree with those in the literature; i.e., with ambiguity seeking for events of moderate and high likelihood. For gains, the WTP questions mean that, after aggregation of the gamble obtained and the price paid, that it is a gamble with a gain and loss, so loss aversion comes in. Real incentives: by means of auctions among 8 participants each time. reflection at individual level for ambiguity: only losses or mixed (that is what WTP for gains is) so does not consider it. correlation risk & ambiguity attitude: Table 6: no relation. %} Di Mauro, Camela & Anna Maffioletti (2004) “Attitudes to risk and Attitudes to Uncertainty: Experimental Evidence,” Applied Economics 36, 357–372. {% Compare bidding behavior and prices in market-like settings to valuations obtained from individual pricing tasks. Repetitions of the market experience tends to improve SEU. (real incentives/hypothetical choice) Presence or absence of financial incentives does not matter. second-order probabilities to model ambiguity: ambiguity is generated through second-order probabilities. It is not easy to derive aspects of individual risk and uncertainty attitudes from the findings of this paper. First, participants get 8 (or 8 times 4?) repetitions of gambles and are paid the sum of the separate gambles, so it is not single choice but repeated and integrated choice. Second, the bidding and market environment can distort. Third, for the real incentives experiments, participants receive a prior payment so that in total they never really lose and, therefore, the part of the participants who integrate the payments and don’t do isolation do not really perceive losses. (The third argument does not hold for the hypothetical payment participants.) The real incentives were 1% of the nominal amounts. %} Di Mauro, Camela & Anna Maffioletti (2000) “Reaction to Uncertainty and Market Mechanisms: Experimental Evidence,” Dept. of Economics, University of Torino. {% Show how direct introspective measurements of happiness are affected by macro-economic phenomena. %} Di Tella, Rafael, Robert J. MacCulloch, & Andrew J. Oswald (2004) “The Macroeconomics of Happiness,” Review of Economics and Statistics 85, 809–827. {% Develops a decision model for the Harsanyi/Mertens-Zamir hierarchies of beliefs over types. %} di Tillio, Alfredo (2008) “Subjective Expected Utility in Games,” Theoretical Economics 3, 287–323. {% How counterfactuals are construed and justified. Omniscientist does not benefit from considering counterfactuals. %} Di Tillio, Alfredo, Itzhak Gilboa, & Larry Samuelson (2013) “The Predictive Role of Counterfactuals,” Theory and Decision 74, 167–182. {% %} Di Tillio, Alfredo, Nenad Kos, & Matthias Messner (2017) “The Design of Ambiguous Mechanisms,” Review of Economic Studies, forthcoming. {% Show that people who are more subject to decision biases more often refuse flu vaccin. To the extent that the latter is irrational [sic] biases then correspond with bigger irrationality in real-life decisions. %} DiBonaventura, Marco daCosta & Gretchen B. Chapman (2008) “Do Decision Biases Predict Bad Decisions? Omission Bias, Naturalness Bias, and Influenza Vaccination,” Medical Decision Making 28, 532–539. {% three-prisoners problem %} Diaconis, Persi (1978) Review of Shafer (1976) Journal of the American Statistical Association 73, 677–678. {% Discuss de Finetti’s exchangeability theorem and give recent references on it %} Diaconis, Persi & David A. Freedman (1990) “Cauchy’s Equation and de Finetti’s Theorem,” Scandinavian Journal of Statistics 17, 235–250. {% Explain bootstrep %} Diaconis, Persi & Bradley Efron (1982) “Computer-Intensive Methods in Statistics,” Scientific American 248, May, 96–108. {% conditional probability; %} Diaconis, Persi & Sandy L. `l (1982) “Updating Subjective Probability,” Journal of the American Statistical Association 77, 822–830. {% Kirsten&I: assumes bounded utility, infinitely many time points as in Koopmans (1960), and shows that continuities imply ultimate impatience. And that his versions of continuity exclude symmetry (such as under zero discounting) of the preference relation. %} Diamond, Peter A. (1965) “The Evaluation of Infinite Utility Streams,” Econometrica 33, 170–177. {% Seems to claim that a major contribution of “behavioral economics is the identification of circumstances where people make mistakes.” %} Diamond, Peter A. (2008) “Behavioral Economics,” Journal of Public Economics 92, 1858–1862. {% %} Diamond, Peter A. & Joseph E. Stiglitz (1974) “Increases in Risk and in Risk Aversion,” Journal of Economic Theory 8, 337–360. {% Analyze Hume’s views on utility, which are Benthamite, and on “beliefs” that, as the authors argue, captures some sort of psychological distance (reminding me of Baucells & Heukamp, 2012) that can as much concern time as probability. just noticeable difference: Hume wrote quite some on this. %} Diaye, Marc-Arthur Diaye & André Lapidus (2012) “Pleasure and Belief in Hume’s Decision Process,” European Journal of the History of Economic Thought 19, 355–384. {% N = 9 subjects. Real incentives: random prize mechanism, but with two choices paid out which may have generated some income effect. Data are from the same experiment as their Management Science 2003 paper. Risk averse for gains, risk seeking for losses: they find that, with much risk aversion for gains and close to risk neutral for losses. In choice situations where one of the two options is riskless, brain activities and response times are different than if both options are risky. The latter finding is repeatedly interpreted by the authors as showing that “choice behavior alone [they mean whether it is going for lowest variance (called risk averse) to highest variance (called risk seeking)] does not reveal completely how choices are made” (p. 3536), and as possibly informative on policy decisions and on how social institutional forms (regarding risky situations) have evolved (p. 3541). They interpret context-dependence not as it is commonly done in the literature, where preferences and utilities over IDENTICAL choice options are different due to different contexts (= available choice options), but they interpret it as changes from biggest-variance to smallest-variance choices when the choice options are different. %} Dickhaut, John W., Kevin McCabe, Jennifer C. Nagode, Aldo Rustichini, Kip Smith, & José V. Pardo (2003) “The Impact of the Certainty Context on the Process of Choice,” Proceedings of the National Academy of Sciences 100, 3536–3541. {% From the abstract: “The model predicts that the further two stimuli are from each other in utility space, the shorter the reaction time will be, fewer errors in choice will be made, and less neural activation will be required to make the choice.” %} Dickhaut, John, Vernon Smith, Baohua Xin, & Aldo Rustichini (2013) “Human Economic Choice as Costly Information Processing,” Journal of Economic Behavior and Organization 94, 206–221. {% Seems to be experimental counterpart to Köbberling & Peters (2003). %} Dickinson, David L. (2009) “The Effects of Beliefs versus Risk Attitude on Batrgaining Outcomes,” Theory and Decision 66, 69–101. {% %} Diecidue, Enrico (2001) “Nonexpected Utility and Coherence,” Ph.D. dissertation, CentER, Tilburg University, the Netherlands. {% %} Diecidue, Enrico (2006) “Deriving Harsanyi’s Utilitarianism from De Finetti’ Book-Making Argument,” Theory and Decision 61, 363–371. {% Formalize support theory with axioms. Probably first to give preference axioms for support theory. There is formally a set of states of nature, and a set of hypotheses, where each hypothesis corresponds with an event but different hypotheses may correspond with the same event. They consider extended gambles, being gambles with outcomes depending on hypotheses. They use an affine bookmaking argument corresponding with multiple priors, where the different priors relate to the nonextensionality. %} Diecidue, Enrico & Dolchai La-Ornual (2009) “Reconciling Support Theory and the Book-Making Principle,” Journal of Risk and Uncertainty 38, 173–190. {% Dutch book. %} Diecidue, Enrico & Fabio Maccheroni (2003) “Coherence without Additivity,” Journal of Mathematical Psychology 47, 166–170. {% The authors carefully test the aspiration level theory introduced by two of them in the well-known Diecidue & van de Ven (2008). They do not find any support at all. I admire their decision to just publish this negative finding. Prospect theory can explain their findings. %} Diecidue, Enrico, Moshe Levy, & Jeroen van de Ven (2015) “No Aspiration to Win? An Experimental Test of the Aspiration Level Model,” Journal of Risk and Uncertainty 51, 245–266. {% Utility of gambling %} Diecidue, Enrico, Ulrich Schmidt, & Peter P. Wakker (2004) “The Utility of Gambling Reconsidered,” Journal of Risk and Uncertainty 29, 241–259. Link to paper Link to comments Link does not work for some computers. Then can:
Diecidue, Enrico, Ulrich Schmidt, & Horst Zank (2009) “Parametric Weighting Functions,” Journal of Economic Theory 144, 1102–1118. {% Tradeoff method: Regret theory gives up transitivity. It is hard to imagine what optimization then means, and what a utility function could mean. This may explain why measuring or axiomatizing it is hard. Mainly Fishburn worked on axiomatizations with his skew-symmetric models. Bleichrodt, Cillo, & Diecidue (2010) showed that the tradeoff method can be used to still measure the theory. This paper shows that it can give an axiomatization of the most popular special case with nonlinearly transformed utility differences. D-transitivity generalizes transitivity by imposing it only whenever one of the antecedent preferences is by dominance. The proof heavily uses a nontransitive state-dependent utility axiomatization by Fishburn (1990). The acknowledgement makes clear that Horst Zank contributed much. %} Diecidue, Enrico & Jeeva Somasundaram (2017) “Regret Theory: A New Foundation,” Journal of Economic Theory 172, 88–119. {% Payne (2005) and others have shown that people are especially sensitive to the probability of a lottery giving strictly positive outcomes, and giving strictly negative outcomes. This paper formalizes the idea, adding only that deviation to EU. Mathematically, though not psychologically, this amounts to the same as utility being discontinuous at 0. %} Diecidue, Enrico, & Jeroen van de Ven (2008) “Aspiration level, Probability of Success and Failure, and Expected Utility,” International Economic Review 49, 683–700. {% inverse-S %} Diecidue, Enrico & Peter P. Wakker (2001) “On the Intuition of Rank-Dependent Utility,” Journal of Risk and Uncertainty 23, 281–298. Link to paper
Diecidue, Enrico & Peter P. Wakker (2002) “Dutch Books: Avoiding Strategic and Dynamic Complications, and a Comonotonic Extension,” Mathematical Social Sciences 43, 135–149. Link to paper
Diecidue, Enrico, Peter P. Wakker, & Marcel Zeelenberg (2007) “Eliciting Decision Weights by Adapting de Finetti’s Betting-Odds Method to Prospect Theory,” Journal of Risk and Uncertainty 34, 179–199. Link to paper
Diener, Ed, & Robert Biswas-Diener (2008) “Rethinking Happiness: The Science of Psychological Wealth.” Blackwell Publishing, Malden, MA. {% %} Diener, Ed, Eunkook M. Suh, Richard E. Lucas, & Heidi L. Smith (1999) “Subjective Well-Being: Three Decades of Progress,” Psychological Bulletin 125, 276–303. {% If all experts have subjective probability 0.7, should aggregation also be 0.70? Probably yes if something like fair group decision, but less so if purpose is information aggregation. %} Dietrich, Franz (2010) “Bayesian Group Belief,” Social Choice and Welfare 35, 595–626. {% A scoring rule for judgment aggregation. %} Dietrich, Franz (2014) “Scoring Rules for Judgment Aggregation,” Social Choice and Welfare 42, 873–911. {% If judgment aggregation is relaxed by allowing for incomplete judgments (so as to escape from the dictator result), only an oligarchy result follows. %} Dietrich, Franz & Christian List (2008) “Judgment Aggregation without Full Rationality,” Social Choice and Welfare 31, 15–39. {% paternalism/Humean-view-of-preference: Propose a theory with weighting arguments to underly choice making, giving reasons why subjective parameters such as utility are as they are. The primary purpose is positive, although there are also implications for normative choice. The opening para equates rational-choice-in-general (which can include intertemporal choice) with expected utility maximization. %} Dietrich, Franz & Christian List (2013) “A Reason-Based Theory of Rational Choice,” Noûs 47, 104–134. {% %} Dietrich, Franz & Christian List (2013) “Reasons for (Prior) Belief in Bayesian Epistemology,” Synthese 190, 787–808. {% %} Dietrich, Franz & Christian List (2013) “Propositionwise Judgment Aggregation: The General Case,” Social Choice and Welfare 40, 1067–1095. {% How preferences come into existence and can develop depending on properties of the alternatives, with a role for perception and formal versus substantive concepts of rationality. (utility = representational?) %} Dietrich, Franz & Christian List (2013) “Where Do Preferences Come from,” International Journal of Game Theory 42, 613–637. {% Argue against Gul & Pesendorfer’s mindless economy. The authors favor, as I do, the mentalist view, where concepts as utility are treated as really existing, such as electrons. I like more the comparison with energy. (utility = representational?) Section 3.1, nicely, puts forward the misconception of a fixed evidence base: the strict revealed-preference view does not realize that we cannot predict what phenomena and data we may get in the future, and that we cannot exclude the future decision-relevance of what now only is introspective data. I argue the same in my 2010 book p. 3 3rd para. This is why I disagree with Friedman (1953). Section 8, p. 274, nicely, formulates the supervenience thesis: people who think that micro-levels such as molecules completely determine macro-levels. %} Dietrich, Franz & Christian List (2016) “Mentalism versus Behaviourism in Economics: A Philosophy-of-Science Perspective,” Economics and Philosophy 32, 249–281. {% R.C. Jeffrey model & updating: present a general model of belief updating that contains Bayesian updating but many generalizations most notably for Jeffrey’s model. %} Dietrich, Franz, Christian List, & Richard Bradley (2015) “Belief Revision Generalized: A Joint Characterization of Bayes's and Jeffrey's Rules,” Journal of Economic Theory 162, 352–371. {% I discovered this in Sep. 2011 because Nicolas Gravel sent it to me. Then there were different versions of this paper on internet, one with pages missing and another with no figures, and with inconsistent page breaks. Many theorems on EU with finitely many equally likely states. P. 358 explains how the theory of general means is related to decision making. It discusses consistency in aggregation, as used by Nagumo and the like, and as generalized associativity or substitution independence from DUR. Section 3 shows that you essentially only need it for binary decompositions of the attributes and for the overall attributes, and not for all decompositions of the attributes. This is similar to Köbberling & Wakker (2003, p. 407 bottom), who wrote, on multisymmetry: “The preference conditions need to be imposed only on one mixing event. With the exception of Quiggin (1982), all the works mentioned imposed the preference conditions on all mixing events.” K&W are somewhat more general because they have no symmetry. They did not know about Diewert’s chapter. Diewert also discusses constant absolute and relative risk aversion for these functionals, and aversion to mean-preserving spread type conditions. End of §4 mentions that log-power and linear-exponential is “all of the nontrigonometric elementary functions of one variable.” Download 7.23 Mb. Share with your friends:
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