Modeling certainty equivalents for imprecise gambles

Budescu, David V.; Kuhn, Kristine M.; Kramer, Karen M.; Johnson, Timothy R.

doi:10.1016/s0749-5978(02)00014-6

Cited by 63 publications

(76 citation statements)

References 30 publications

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“…Hence, stakeholders do not always choose alternatives that maximize their expected utility. Aversion to ambiguity exists in many application areas, including health, environment, negotiation, and more (Becker and Brownson 1964, Curley and Yates 1985, Hogarth and Kunreuther 1989, Kuhn and Budescu 1996, Budescu et al 2002.…”

Section: Limitations Of Expected Utility Maximization Framework In Anmentioning

confidence: 99%

Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

Singh¹,

Reed²,

Keller³

2015

E&S

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ABSTRACT. Managing ecosystems with deeply uncertain threshold responses and multiple decision makers poses nontrivial decision analytical challenges. The problem is imbued with deep uncertainties because decision makers do not know or cannot converge on a single probability density function for each key parameter, a perfect model structure, or a single adequate objective. The existing literature on managing multistate ecosystems has generally followed a normative decision-making approach based on expected utility maximization (MEU). This approach has simple and intuitive axiomatic foundations, but faces at least two limitations. First, a prespecified utility function is often unable to capture the preferences of diverse decision makers. Second, decision makers' preferences depart from MEU in the presence of deep uncertainty. Here, we introduce a framework that allows decision makers to pose multiple objectives, explore the trade-offs between potentially conflicting preferences of diverse decision makers, and to identify strategies that are robust to deep uncertainties. The framework, referred to as many-objective robust decision making (MORDM), employs multiobjective evolutionary search to identify trade-offs between strategies, re-evaluates their performance under deep uncertainty, and uses interactive visual analytics to support the selection of robust management strategies. We demonstrate MORDM on a stylized decision problem posed by the management of a lake in which surpassing a pollution threshold causes eutrophication. Our results illustrate how framing the lake problem in terms of MEU can fail to represent key trade-offs between phosphorus levels in the lake and expected economic benefits. Moreover, the MEU strategy deteriorates severely in performance for all objectives under deep uncertainties. Alternatively, the MORDM framework enables the discovery of strategies that balance multiple preferences and perform well under deep uncertainty. This decision analytic framework allows the decision makers to select strategies with a better understanding of their expected trade-offs (traditional uncertainty) as well as their robustness (deep uncertainty).

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Section: Limitations Of Expected Utility Maximization Framework In Anmentioning

confidence: 99%

Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

Singh¹,

Reed²,

Keller³

2015

E&S

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“…3.1 A Measure for Ambiguity Attitudes Budescu et al (2002) develop a measure for ambiguity attitudes of decision makers, based on a generalized version of Prospect Theory (Kahneman and Tversky, 1979), with the addition of a well-defined parameter to accommodate decision makers' attitudes towards ambiguous probabilities. In this study, decision makers are asked to evaluate through certainty equivalents (CE), 16 a prospect, P , that yields $x, with probability p, and $y, otherwise.…”

Section: Theorymentioning

confidence: 99%

“…In Budescu et al (2002) study, it is assumed that the same parameters and functions that describe decision makers responses to precise prospects, also describe their responses to the ambiguous prospects. Thus, ambiguity is operationalized through probability intervals, [p, p], where p is the lower bound of the interval, and p is the upper bound of the interval 17 .…”

Section: Theorymentioning

confidence: 99%

Over-Confidence and Entrepreneurial Choice Under Ambiguity

Shyti

2013

SSRN Journal

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Entrepreneurship studies have attributed to overconfidence decisions to start a new venture. Many decision situations, through which overconfidence is measured, entail some degrees of uncertainty (e.g., related to own skill or to competition). The aspect of uncertainty is largely neglected in overconfidence studies or entrepreneurial research. Both uncertainty and overconfidence influence individuals' likelihood perceptions. Nevertheless, these two aspects are seldom jointly investigated, and the little evidence provides inconclusive results. In this study, we experimentally investigate how uncertainty, as a property of the situation, and overconfidence, as a characteristic of decision makers' beliefs, influence choice behavior. Our findings with Executive MBA participants show that overconfident decision makers choose less uncertain options for low-likelihood outcomes and more uncertain options for high likelihood outcomes, contrary to neutralconfidence decision makers, which choices are in line with standard Prospect Theory predictions.

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“…Their usefulness for studying ambiguity has recently been recognized (Budescu et al 2002;Hollard et al 2010;Kahn and Sarin 1988;Viscusi and Magat 1992). Given a fixed r, we can define matching probabilities m i (p) and m c (p) as the matching probabilities for I-and C-ambiguity (details follow below).…”

Section: Properties Of Matching Probabilities (Ambiguity Attitude)mentioning

confidence: 99%

Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories

2012

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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.

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Modeling certainty equivalents for imprecise gambles

Cited by 63 publications

References 30 publications

Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

Many-objective robust decision making for managing an ecosystem with a deeply uncertain threshold response

Over-Confidence and Entrepreneurial Choice Under Ambiguity

Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories

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