Peter P. Wakker

Erasmus Universiteit Rotterdam, Rotterdam, South Holland, Netherlands

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Publications (161)203.59 Total impact

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    ABSTRACT: This paper introduces the Prince incentive system for measuring preferences. Prince clarifies consequences of decisions and incentive compatibility of experimental choice questions to subjects. It combines the efficiency and precision of matching with the improved clarity and validity of choice questions. It helps distinguish between (a) genuine deviations from classical economic theories (such as the endowment effect) and (b) preference anomalies due to fallible measurements (such as preference reversals). Prince avoids the opaqueness in Becker-DeGroot-Marschak and strategic behavior in adaptive experiments. It helps reducing violations of isolation in the random incentive system. Using Prince we shed new light on willingness to accept and the major components of decision making under uncertainty: utilities, subjective beliefs, and ambiguity attitudes.
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    Celia Sales · Peter Wakker · Paula Alves · Luís Faísca
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    ABSTRACT: This paper presents the metric-frequency calculator (MF Calculator), an online application to analyze similarity. The MF Calculator implements a metric-frequency similarity algorithm for the quantitative assessment of similarity in ill-structured data sets. It is widely applicable as it can be used with nominal, ordinal, or interval data when there is little prior control over the variables to be observed regarding number or content. The MF Calculator generates a proximity matrix in CSV, XML or DOC format that can be used as input to traditional statistical techniques such as hierarchical clustering, additive trees, or multidimensional scaling. The MF Calculator also displays a graphical representation of outputs using additive similarity trees. A simulated example illustrates the implementation of the MF calculator. An additional example with real data is presented, in order to illustrate the potential of combining the MF Calculator with cluster analysis. The MF Calculator is a user-friendly tool available free of charge. It can be accessed from http://mfcalculator.celiasales.org/Calculator.aspx, and it can be used by non-experts from a wide range of social sciences.
    Journal of statistical software 05/2015; 65:Code Snippet 2. · 3.80 Impact Factor
  • Han Bleichrodt · Peter P. Wakker
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    ABSTRACT: In their famous 1982 paper in this Journal, Loomes and Sugden introduced regret theory. Now, more than 30 years later, the case for the historical importance of this contribution can be made.
    The Economic Journal 03/2015; 125(583). DOI:10.1111/ecoj.12200 · 1.95 Impact Factor
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    ABSTRACT: Uncertainty pervades most aspects of life. From selecting a new technology to choosing a career, decision makers rarely know in advance the exact outcomes of their decisions. Whereas the consequences of decisions in standard decision theory are explicitly described (the decision from description (DFD) paradigm), the consequences of decisions in the recent decision from experience (DFE) paradigm are learned from experience. In DFD, decision makers typically overrespond to rare events. That is, rare events have more impact on decisions than their objective probabilities warrant (overweighting). In DFE, decision makers typically exhibit the opposite pattern, underresponding to rare events. That is, rare events may have less impact on decisions than their objective probabilities warrant (underweighting). In extreme cases, rare events are completely neglected, a pattern known as the “Black Swan effect.” This contrast between DFD and DFE is known as a description–experience gap. In this paper, we discuss several tentative interpretations arising from our interdisciplinary examination of this gap. First, while a source of underweighting of rare events in DFE may be sampling error, we observe that a robust description–experience gap remains when these factors are not at play. Second, the residual description–experience gap is not only about experience per se but also about the way in which information concerning the probability distribution over the outcomes is learned in DFE. Econometric error theories may reveal that different assumed error structures in DFD and DFE also contribute to the gap.
    Marketing Letters 09/2014; 25(3):269-280. DOI:10.1007/s11002-014-9316-z · 1.06 Impact Factor
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    Amit Kothiyal · Vitalie Spinu · Peter P. Wakker
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    ABSTRACT: This paper provides necessary and sufficient preference conditions for average utility maximization over sequences of variable length. We obtain full generality by using a new algebraic technique that exploits the richness structure naturally provided by the variable length of the sequences. Thus we generalize many preceding results in the literature. For example, continuity in outcomes, a condition needed in other approaches, now is an option rather than a requirement. Applications to expected utility, decisions under ambiguity, welfare evaluations for variable population size, discounted utility, and quasilinear means in functional analysis are presented.
    Operations Research 02/2014; 62(1). DOI:10.1287/opre.2013.1230 · 1.50 Impact Factor
  • Amit Kothiyal · Vitalie Spinu · Peter P. Wakker
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    ABSTRACT: Prospect theory is the most popular theory for predicting decisions under risk. This paper investigates its predictive power for decisions under ambiguity, using its specification through the source method. We find that it outperforms its most popular alternatives, including subjective expected utility, Choquet expected utility, and three multiple priors theories: maxmin expected utility, maxmax expected utility, and a-maxmin expected utility.
    Journal of Risk and Uncertainty 02/2014; 48(1). DOI:10.1007/s11166-014-9185-0 · 1.53 Impact Factor
  • Chen Li · Zhihua Li · Peter P. Wakker
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    ABSTRACT: A central question in many debates on paternalism is whether a decision analyst can ever go against the stated preference of a client, even if merely intending to improve the decisions for the client. Using four gedanken-experiments, this paper shows that this central question, so cleverly and aptly avoided by libertarian paternalism (nudge), cannot always be avoided. The four thought experiments, while purely hypothetical, serve to raise and specify the critical arguments in a maximally clear and pure manner. The first purpose of the paper is, accordingly, to provide a litmus test on the readers’ stance on paternalism. We thus also survey and organize the various stances in the literature. The secondary purpose of this paper is to argue that paternalism cannot always be avoided and consumer sovereignty cannot always be respected. However, this argument will remain controversial.
    Theory and Decision 01/2014; DOI:10.1007/s11238-013-9375-2 · 0.48 Impact Factor
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    ABSTRACT: Doyle’s (2013) theoretical survey of discount functions criticizes two parametric families abbreviated as CRDI and CADI families. We show that Doyle’s criticisms are based on a mathematical mistake and are incorrect.
    Judgment and decision making 09/2013; 2013(8):630-631. · 2.62 Impact Factor
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    Aurélien Baillon · Laure Cabantous · Peter Wakker
  • Han Bleichrodt · Amit Kothiyal · Drazen Prelec · Peter P. Wakker
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    ABSTRACT: Behavioral conditions such as compound invariance for risky choice and constant decreasing relative impatience for intertemporal choice have surprising implications for the underlying decision model. They imply a multiplicative separability of outcomes and either probability or time. Hence the underlying model must be prospect theory or discounted utility on the domain of prospects with one nonzero outcome. We indicate implications for richer domains with multiple outcomes, and with both risk and time involved.
    Journal of Mathematical Psychology 06/2013; 57(s 3–4):68–77. DOI:10.1016/j.jmp.2013.04.002 · 1.81 Impact Factor
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    ABSTRACT: Uncertainty pervades most aspects of life. From selecting a new technology to choosing a career, decision makers often ignore the outcomes of their decisions. In the last decade a new paradigm has emerged in behavioral decision research in which decisions are “experienced” rather than “described”, as in standard decision theory. The dominant finding from studies using the experience-based paradigm is that decisions from experience exhibit "black swan effect", i.e. the tendency to neglect rare events. Under prospect theory, this results in an experience-description gap. We show that several tentative conclusions can be drawn from our interdisciplinary examination of the putative experience-description gap in decision under uncertainty. Several insights are discussed. First, while the major source of under-weighting of rare events may be sampling error, it is argued that a robust experience-description gap remains when these factors are not at play. Second, the residual experience-description gap is not only about experience per se, but also about the way in which information concerning the probability distribution over possible outcomes is learned.Additional econometric and empirical work might be required to fully flech out these tentative conclusions. However, there was a consensus that an initially polemical literature turns out to be constructive in drawing researcher towards greater rapprochements.
    Choice Symposium, Rotterdam; 06/2013
  • Vitalie Spinu · Peter P. Wakker
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    ABSTRACT: This paper presents preference axiomatizations of expected utility for nonsimple lotteries while avoiding continuity constraints. We use results by Fishburn (1975), Wakker (1993), and Kopylov (2010) to generalize results by Delbaen et al. (2011). We explain the logical relations between these contributions for risk versus uncertainty, and for finite versus countable additivity, indicating what are the most general axiomatizations of expected utility existing today.
    Journal of Mathematical Economics 01/2013; 49(1):28–30. DOI:10.1016/j.jmateco.2012.09.005 · 0.50 Impact Factor
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    Peter P. Wakker
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    ABSTRACT: This paper uses decision-theoretic principles to obtain new insights into the assessment and updating of probabilities. First, a new foundation of Bayesianism is given. It does not require infinite atomless uncertainties as did Savage s classical result, AND can therefore be applied TO ANY finite Bayesian network.It neither requires linear utility AS did de Finetti s classical result, AND r ntherefore allows FOR the empirically AND normatively desirable risk r naversion.Finally, BY identifying AND fixing utility IN an elementary r nmanner, our result can readily be applied TO identify methods OF r nprobability updating.Thus, a decision - theoretic foundation IS given r nto the computationally efficient method OF inductive reasoning r ndeveloped BY Rudolf Carnap.Finally, recent empirical findings ON r nprobability assessments are discussed.It leads TO suggestions FOR r ncorrecting biases IN probability assessments, AND FOR an alternative r nto the Dempster - Shafer belief functions that avoids the reduction TO r ndegeneracy after multiple updatings.r n
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    ABSTRACT: Experiments frequently use a random incentive system (RIS), where only tasks that are randomly selected at the end of the experiment are for real. The most common type pays every subject one out of her multiple tasks (within-subjects randomization). Recently, another type has become popular, where a subset of subjects is randomly selected, and only these subjects receive one real payment (between-subjects randomization). In earlier tests with simple, static tasks, RISs performed well. The present study investigates RISs in a more complex, dynamic choice experiment. We find that between-subjects randomization reduces risk aversion. While within-subjects randomization delivers unbiased measurements of risk aversion, it does not eliminate carry-over effects from previous tasks. Both types generate an increase in subjects’ error rates. These results suggest that caution is warranted when applying RISs to more complex and dynamic tasks. KeywordsRandom incentive system–Incentives–Experimental measurement–Risky choice–Risk aversion–Dynamic choice–Tremble–Within-subjects design–Between-subjects design
    Experimental Economics 09/2012; 15(3):1-26. DOI:10.1007/s10683-011-9306-4 · 1.36 Impact Factor
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    Baillon · Bram Driesen · Peter P. Wakker
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    ABSTRACT: This paper presents a general technique for comparing the concavity of different utility functions when probabilities need not be known. It generalizes: (a) Yaariʼs comparisons of risk aversion by not requiring identical beliefs; (b) Kreps and Porteusʼ information-timing preference by not requiring known probabilities; (c) Klibanoff, Marinacci, and Mukerjiʼs smooth ambiguity aversion by not using subjective probabilities (which are not directly observable) and by not committing to (violations of) dynamic decision principles; (d) comparative smooth ambiguity aversion by not requiring identical second-order subjective probabilities. Our technique completely isolates the empirical meaning of utility. It thus sheds new light on the descriptive appropriateness of utility to model risk and ambiguity attitudes.
    Games and Economic Behavior 07/2012; 75(2):481–489. DOI:10.1016/j.geb.2012.01.006 · 0.83 Impact Factor
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    Arthur E Attema · Han Bleichrodt · Peter P Wakker
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    ABSTRACT: Time discounting and quality of life are two important factors in evaluations of medical interventions. The measurement of these two factors is complicated because they interact. Existing methods either simply assume one factor given, based on heuristic assumptions, or invoke complicating extraneous factors, such as risk, that generate extra biases. The authors introduce a method for measuring discounting (and then quality of life) that involves no extraneous factors and that avoids distorting interactions. Their method is considerably simpler and more realistic for subjects than existing methods. It is entirely choice based and thus can be founded on economic rationality requirements. An experiment demonstrates the feasibility of this method and its advantages over classical methods.
    Medical Decision Making 06/2012; 32(4):583-93. DOI:10.1177/0272989X12451654 · 2.27 Impact Factor
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    ABSTRACT: In a large representative sample, we measure ambiguity attitudes and investigate their relation with stock market participation. Our tractable measurement of the general population’s ambiguity attitudes is made possible by a simplification of the recently introduced source method. In addition to ambiguity aversion, the results from our representative sample confirm a-insensitivity, a new component of ambiguity attitudes recently found in laboratory studies. A-insensitivity means that people do not sufficiently discriminate between different levels of likelihood, often treating them as fifty-fifty. Contrary to common expectation, ambiguity aversion, when measured using classical stimuli, is not significantly associated with stock market participation, except for those subjects who perceive stock returns as highly ambiguous. A-insensitivity, however, is negatively related to both stock market participation and private business ownership. These surprising findings can be explained by reference dependent ambiguity. Our results show the empirical relevance of a-insensitivity and reference dependence for real-world economic decisions.
    SSRN Electronic Journal 06/2012; DOI:10.2139/ssrn.1876580
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    Aurélien Baillon · Laure Cabantous · Peter P. Wakker
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    ABSTRACT: Two experiments show that violations of expected utility due to ambiguity, found in general decision experiments, also affect belief aggregation. Hence we use modern ambiguity theories to analyze belief aggregation, thus obtaining more refined and empirically more valid results than traditional theories can provide. We can now confirm more reliably that conflicting (heterogeneous) beliefs where some agents express certainty are processed differently than informationally equivalent imprecise homogeneous beliefs. We can also investigate new phenomena related to ambiguity. For instance, agents who express certainty receive extra weight (a cognitive effect related to ambiguity-generated insensitivity) and generate extra preference value (source preference; a motivational effect related to ambiguity aversion). Hence, incentive compatible belief elicitations that prevent manipulation are especially warranted when agents express certainty. For multiple prior theories of ambiguity, our findings imply that the same prior probabilities can be treated differently in different contexts, suggesting an interest of corresponding generalizations.
    Journal of Risk and Uncertainty 04/2012; 44(2):115-147. DOI:10.1007/s11166-012-9140-x · 1.53 Impact Factor
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    Han Bleichrodt · Jason N · Martin Filko · Peter P. Wakker
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    ABSTRACT: Utility independence is a central condition in multiattribute utility theory, where attributes of outcomes are aggregated in the context of risk. The aggregation of attributes in the absence of risk is studied in conjoint measurement. In conjoint measurement, standard sequences have been widely used to empirically measure and test utility functions, and to theoretically analyze them. This paper shows that utility independence and standard sequences are closely related: utility independence is equivalent to a standard sequence invariance condition when applied to risk. This simple relation between two widely used conditions in adjacent fields of research is surprising and useful. It facilitates the testing of utility independence because standard sequences are flexible and can avoid cancelation biases that affect direct tests of utility independence. Extensions of our results to nonexpected utility models can now be provided easily. We discuss applications to the measurement of quality-adjusted life-years (QALY) in the health domain.
    Journal of Mathematical Psychology 12/2011; 55(6):1-25. DOI:10.1016/j.jmp.2011.08.001 · 1.81 Impact Factor
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    ABSTRACT: This paper finds preference reversals in measurements of ambiguity aversion, even if psychological and informational circumstances are kept constant. The reversals are of a fundamentally different nature than the reversals found before because they cannot be explained by context-dependent weightings of attributes. We offer an explanation based on Sugden's random-reference theory, with different elicitation methods generating different random reference points. Then measurements of ambiguity aversion that use willingness to pay are confounded by loss aversion and hence overestimate ambiguity aversion. This paper was accepted by Teck Ho, decision analysis.
    Management Science 07/2011; 57(7):1320-1333. DOI:10.2307/25835778 · 2.52 Impact Factor

Publication Stats

6k Citations
203.59 Total Impact Points

Institutions

  • 1994–2015
    • Erasmus Universiteit Rotterdam
      • Department of Economics
      Rotterdam, South Holland, Netherlands
  • 2008
    • Université de Cergy-Pontoise
      95001 CEDEX, Ile-de-France, France
  • 2004–2007
    • Maastricht University
      • • Department of Economics
      • • Department of Quantitative Economics
      Maastricht, Provincie Limburg, Netherlands
  • 2006
    • Kent State University
      • Department of Economics
      Kent, OH, United States
  • 2000–2006
    • University of Amsterdam
      • Department of Economics
      Amsterdamo, North Holland, Netherlands
  • 1998–2004
    • Leiden University Medical Centre
      • Department of Medical Decision Making
      Leyden, South Holland, Netherlands
  • 1970–2002
    • Tilburg University
      • CentER for Research in Economics and Business " CentER"
      Tilburg, North Brabant, Netherlands
  • 1970–1997
    • Leiden University
      Leyden, South Holland, Netherlands
  • 1990–1996
    • Duke University
      • Fuqua School of Business
      Durham, North Carolina, United States
  • 1985–1996
    • Radboud University Nijmegen
      • Department of Mathematics
      Nymegen, Gelderland, Netherlands
  • 1995
    • Stanford University
      • Department of Psychology
      Stanford, California, United States
  • 1989
    • Centraal Bureau voor de Statistiek
      's-Gravenhage, South Holland, Netherlands
  • 1988
    • Tel Aviv University
      Tell Afif, Tel Aviv, Israel