Uncertain discount and hyperbolic preferences

Pennesi, Daniele

doi:10.1007/s11238-017-9603-2

Cited by 7 publications

(4 citation statements)

References 43 publications

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“…Indeed, the literature provides other risk specifications and explanations of TI. For instance,Dasgupta and Maskin (2005) specified future risk based on the timing of an event, and explained that TI occurs through updating the risk over time Pennesi (2017). focused on the uncertainty of individuals' impatience, and explained TI through differences in sensitivity to delay between states.…”

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confidence: 99%

Does time inconsistency differ between gain and loss? An intra-personal comparison using a non-parametric elicitation method

Shiba

Shimizu

2019

Theory Decis

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Several studies on time preference have found time inconsistency in both gain and loss preferences. However, the relationship between the two within the same person remains unclear; that is, does an individual who demonstrates time inconsistency for gain outcomes do so for losses as well? This paper reports on individuals’ time inconsistency for gains and losses in a laboratory setting. To obtain a precise comparison of individuals’ time inconsistency for gains and losses, we used Rohde’s “DI (decreasing impatience)-index” (Manag Sci 65(4):1700–1716, 2018) and measured the level of time inconsistency, rather than merely identifying whether TI was present. This index represents how strongly a person exhibits present bias, and easily extends to the comparison between gain and loss preferences within the same person. Further, it allows the experiment to test for so-called future bias, which has been a focus area in recent time inconsistency literature. It is elicited through a non-parametric method, which avoids any specification errors in the analysis. Our findings are as follows: first, we found future bias in preferences for not only gains but also losses, and we confirmed that this tendency is consistent with previous findings on preferences for gains. Second, a positive correlation between time inconsistency for gains and losses was found at the individual level. Indeed, we could not find a significant difference between the two in most cases.

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confidence: 99%

Does time inconsistency differ between gain and loss? An intra-personal comparison using a non-parametric elicitation method

Shiba

Shimizu

2019

Theory Decis

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“…It appears that working with far distant futures we have to consider hyperbolic discounting as was noted in the paper [2]. Further motivations to study hyperbolic discount one can find in [20].…”

Section: Introductionmentioning

confidence: 98%

Long Run Control with Degenerate Observation

Stettner¹

2019

SIAM J. Control Optim.

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Controlled discrete time Markov processes are studied first with long run general discounting functional. It is shown that optimal strategies for average reward per unit time problem are also optimal for average generally discounting functional. Then long run risk sensitive reward functional with general discounting is considered. When risk factor is positive then optimal value of such reward functional is dominated by the reward functional corresponding to the long run risk sensitive control. In the case of negative risk factor we get an asymptotical result, which says that optimal average reward per unit time control is nearly optimal for long run risk sensitive reward functional with general discounting, assuming that risk factor is close to 0. For this purpose we show in Appendix upper estimates for large deviations of weighted empirical measures, which are of independent interest.

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“…On the other hand, in a similar way, when explicit risk is introduced to immediate rewards, the immediacy effect is almost eliminated just as if time delay is added. It is necessary to clarify that presently there is no consensus on this topic, while Pennesi [48] confirms that when the immediate payoff becomes uncertain, the immediacy effect disappears, Abdellaoui et al [35] claim that the immediacy effect persists under risk.…”

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confidence: 99%

Discounted and Expected Utility from the Probability and Time Trade-Off Model

Rambaud

Pérez

2020

Mathematics

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This paper shows the interaction between probabilistic and delayed rewards. In decisionmaking processes, the Expected Utility (EU) model has been employed to assess risky choices whereas the Discounted Utility (DU) model has been applied to intertemporal choices. Despite both models being different, they are based on the same theoretical principle: the rewards are assessed by taking into account the sum of their utilities and some similar anomalies have been revealed in both models. The aim of this paper is to characterize and consider particular cases of the Time Trade-Off (PPT) model and show that they correspond to the EU and DU models. Additionally, we will try to build a PTT model starting from a discounted and an expected utility model able to overcome the limitations pointed out by Baucells and Heukamp.On the other hand, the decision-making under uncertainty involves alternatives whose rewards differ in relation to the probability of being received (the choice between "a smaller reward, to be received with greater probability, and a larger one, but less likely") [3].Both kinds of decisions have been traditionally analyzed by using two main systems of calculation: the Discounted Utility model and the Expected Utility theory which describe the present value of delayed rewards and the actuarial value of risky rewards, respectively. Both models are simple, widely accepted, and with a similar structure, since they use the same theoretical principle: the rewards are assessed by the sum of their utilities [6,7]. In the decision-making process, individuals choose the alternative which maximizes their current utility value (denoted by U 0 ).As seen in Table 1, DU and EU are the basic models employed in the decision-making process which represent the rational choice over time and under risk, respectively.

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Uncertain discount and hyperbolic preferences

Cited by 7 publications

References 43 publications

Does time inconsistency differ between gain and loss? An intra-personal comparison using a non-parametric elicitation method

Does time inconsistency differ between gain and loss? An intra-personal comparison using a non-parametric elicitation method

Long Run Control with Degenerate Observation

Discounted and Expected Utility from the Probability and Time Trade-Off Model

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