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on Utility Models and Prospect Theory |
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Issue of 2023‒09‒11
ten papers chosen by |
| By: | Caliari, Daniele |
| Abstract: | Behavioural welfare economics provides tools to elicit welfare preferences when individuals use nonstandard behavioural models. Current proposals either require assumptions on the models or elicit preferences that become coarser and coarser as the dataset grows. We propose an informational property [Informational Responsiveness] that solves the coarseness problem and, as the dataset grows, characterizes the family of welfare preference elicitation tools that elicit the underlying utility function of a broad family of stochastic models, denoted as preference monotonic models. As such, we argue that Informational Responsiveness is an important property of preference elicitation tools. We then test our property in an experiment in which participants first face a sequence of questions regarding time and risk outcomes and second report their preferences over a subset of the alternatives. We find that preference elicitation tools that satisfy our requirement provide a significantly better match between the elicited and the reported welfare relation. |
| Keywords: | Behavioural Welfare economics, Bounded rationality, Stochastic choice, Revealed preference |
| JEL: | D0 D6 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wzbeoc:spii2023303&r=upt |
| By: | Karen Mulligan; Drishti Baid; Jason N. Doctor; Charles E. Phelps; Darius N. Lakdawalla |
| Abstract: | Recent research has documented a link between consumer risk preferences over health and the willingness to pay (WTP) for medical technologies. However, the absence of empirical health risk preference estimates so far limits the implementation of this generalized risk-adjusted cost-effectiveness (GRACE) theory, which addresses several limitations of traditional cost-effectiveness analysis (CEA). To address this gap, we elicit from a nationally representative U.S. sample individual risk preference parameters over health-related quality of life (HRQoL) that shed light on health risk attitudes and enable GRACE valuation of medical technology. We find individuals exhibit risk-seeking preferences at low levels of health, switch to risk-averse preferences at health equal to 0.485 (measured on a zero to one scale), and become most risk-averse when their health is perfect (coefficient of relative risk aversion = 4.36). The risk preference estimates imply an empirical premium for disease severity: each unit of health is worth three times more to patients with serious health conditions (health equals 0.5) than those who are perfectly healthy. They also imply that traditional CEA overvalues treatments for the mildest diseases by more than a factor of two. Use of traditional CEA both overstimulates mild disease treatment innovation and underprovides severe disease treatment innovation. |
| JEL: | I11 I18 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31524&r=upt |
| By: | Daniel Reck; Arthur Seibold |
| Abstract: | Empirical evidence suggests that individuals often evaluate options relative to a reference point, especially seeking to avoid losses. We undertake the first welfare analysis under reference-dependent preferences. We characterize the welfare impact of changes in reference points and prices, decomposing these into direct and behavioral effects. The sign of direct and behavioral effects depends on the form of reference-dependent payoffs; which of these effects matter for welfare depends on whether reference dependence reflects a bias or a normative preference. We derive sufficient statistics formulas quantifying the social welfare effects of changes in reference points and prices in terms of estimable reduced-form parameters and normative judgments. We illustrate these findings with an empirical application to reference dependence exhibited in German workers’ retirement decisions. We find positive social welfare effects of increasing the Normal Retirement Age, but ambiguous effects of financial incentives to postpone retirement. |
| Keywords: | reference-dependent preferences, loss aversion, welfare, pension reform |
| JEL: | D91 D60 H55 J26 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2023_450&r=upt |
| By: | Sun, Tianyu; Tian, Liu |
| Abstract: | Abstract Demand saturation occurs along with economic development, but the theoretical basis for demand saturation is lacking. This study adds to literature by proposing a novel concept named utilization cost, which denotes the physical or mental burden incurred to obtain utility. Correspondingly, we distinguish between quantity and quality of consumption and construct a general utility function. With a generative decision procedure, the analysis shows that utilization costs help to explain the economic dynamics across development stages in terms of demand saturation. And, the long-term state of demand is affected by the properties of utilization costs, determining development directions. |
| Date: | 2023–07–24 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:95fdm&r=upt |
| By: | John V. Colias (Decision Analyst); Stella Park (AT&T); Elizabeth Horn (Decision Analyst) |
| Abstract: | In B2B markets, value-based pricing and selling has become an important alternative to discounting. This study outlines a modeling method that uses customer data (product offers made to each current or potential customer, features, discounts, and customer purchase decisions) to estimate a mixed logit choice model. The model is estimated via hierarchical Bayes and machine learning, delivering customer-level parameter estimates. Customer-level estimates are input into a nonlinear programming next-offer maximization problem to select optimal features and discount level for customer segments, where segments are based on loyalty and discount elasticity. The mixed logit model is integrated with economic theory (the random utility model), and it predicts both customer perceived value for and response to alternative future sales offers. The methodology can be implemented to support value-based pricing and selling efforts. Contributions to the literature include: (a) the use of customer-level parameter estimates from a mixed logit model, delivered via a hierarchical Bayes estimation procedure, to support value-based pricing decisions; (b) validation that mixed logit customer-level modeling can deliver strong predictive accuracy, not as high as random forest but comparing favorably; and (c) a nonlinear programming problem that uses customer-level mixed logit estimates to select optimal features and discounts. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.07830&r=upt |
| By: | Yu, Haoyang; Sun, Yutong; Liu, Yulin; Zhang, Luyao |
| Abstract: | Historically, gold and silver have played distinct roles in tra- ditional monetary systems. While gold has primarily been revered as a superior store of value, prompting individuals to hoard it, silver has com- monly been used as a medium of exchange. As the financial world evolves, the emergence of cryptocurrencies has introduced a new paradigm of value and exchange. However, the store-of-value characteristic of these digital assets remains largely uncharted. Charlie Lee, the founder of Lite- coin, once likened Bitcoin to gold and Litecoin to silver. To validate this analogy, our study employs several metrics, including unspent transac- tion outputs (UTXO), spent transaction outputs (STXO), Weighted Average Lifespan (WAL), CoinDaysDestroyed (CDD), and public on-chain transaction data. Furthermore, we’ve devised trading strategies centered around the Price-to-Utility (PU) ratio, offering a fresh perspective on crypto-asset valuation beyond traditional utilities. Our back-testing re- sults not only display trading indicators for both Bitcoin and Litecoin but also substantiate Lee’s metaphor, underscoring Bitcoin’s superior store-of-value proposition relative to Litecoin. We anticipate that our findings will drive further exploration into the valuation of crypto assets. For enhanced transparency and to promote future research, we’ve made our datasets available on Harvard Dataverse and shared our Python code on GitHub as open source. |
| Date: | 2023–07–31 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:t2fku&r=upt |
| By: | Ashraf Ghiye; Baptiste Barreau; Laurent Carlier; Michalis Vazirgiannis |
| Abstract: | Classical recommender systems often assume that historical data are stationary and fail to account for the dynamic nature of user preferences, limiting their ability to provide reliable recommendations in time-sensitive settings. This assumption is particularly problematic in finance, where financial products exhibit continuous changes in valuations, leading to frequent shifts in client interests. These evolving interests, summarized in the past client-product interactions, see their utility fade over time with a degree that might differ from one client to another. To address this challenge, we propose a time-dependent collaborative filtering algorithm that can adaptively discount distant client-product interactions using personalized decay functions. Our approach is designed to handle the non-stationarity of financial data and produce reliable recommendations by modeling the dynamic collaborative signals between clients and products. We evaluate our method using a proprietary dataset from BNP Paribas and demonstrate significant improvements over state-of-the-art benchmarks from relevant literature. Our findings emphasize the importance of incorporating time explicitly in the model to enhance the accuracy of financial product recommendation. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.01208&r=upt |
| By: | Benjamin Laufer; Jon Kleinberg; Hoda Heidari |
| Abstract: | Major advances in Machine Learning (ML) and Artificial Intelligence (AI) increasingly take the form of developing and releasing general-purpose models. These models are designed to be adapted by other businesses and agencies to perform a particular, domain-specific function. This process has become known as adaptation or fine-tuning. This paper offers a model of the fine-tuning process where a Generalist brings the technological product (here an ML model) to a certain level of performance, and one or more Domain-specialist(s) adapts it for use in a particular domain. Both entities are profit-seeking and incur costs when they invest in the technology, and they must reach a bargaining agreement on how to share the revenue for the technology to reach the market. For a relatively general class of cost and revenue functions, we characterize the conditions under which the fine-tuning game yields a profit-sharing solution. We observe that any potential domain-specialization will either contribute, free-ride, or abstain in their uptake of the technology, and we provide conditions yielding these different strategies. We show how methods based on bargaining solutions and sub-game perfect equilibria provide insights into the strategic behavior of firms in these types of interactions, and we find that profit-sharing can still arise even when one firm has significantly higher costs than another. We also provide methods for identifying Pareto-optimal bargaining arrangements for a general set of utility functions. |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2308.04399&r=upt |
| By: | Subhasish M. Chowdhury (Department of Economics, University of Sheffield, Sheffield S1 4DT, UK); Sang-Hyun Kim (School of Economics, Yonsei University, Seoul 03722, South Korea) |
| Abstract: | We introduce a spatial voting contest without the ‘one person, one vote’ restriction. Players exert costly effort to influence the policy and the outcome is obtained through an adjustment function. Players are heterogeneous in terms of the position in the policy line, disutility function, and the effort cost. In equilibrium, two groups endogenously emerge: players in one group try to implement more leftist policy, while those in the other group try more rightist one. Since the larger group suffers a more severe free-riding problem, the equilibrium policy converges to the center only when the larger group has a cost advantage. We demonstrate how the location of the center (i.e., the steady-state point) can be either median, or a mean of all points, or a mean of the extreme points, depending on the convexities of the utility and cost functions. This reflects some well-known results as special cases. We extend the model to an infinite horizon setting and show that the median outcome can be reached only under certain conditions. |
| Keywords: | Spatial Competition; Contest; Lobbying; Median Voter Theorem |
| JEL: | C72 D72 D74 D78 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:shf:wpaper:2023019&r=upt |
| By: | Caliari, Daniele |
| Abstract: | We challenge the standard definition of economic rationality as consistency by making use of a novel distinction between axioms of decision theory: consistency and preference axioms. We argue that this distinction has been overlooked by the literature and, as a result, evidence that consistency is a proxy of decision-making ability is often based on incorrect identification strategies. We conduct an experiment to investigate the factors that drive violations of consistency alone. While we find no evidence that consistency axioms are a proxy of decisionmaking ability, we provide suggestive evidence that some preference axioms are, confirming their potential role as confounding factors. Overall, our experimental evidence raises doubts about the choice of language that equates consistency with rationality in economics. |
| Keywords: | Decision Theory, Experimental Design, Consistency, Rationality |
| JEL: | D00 D90 D91 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wzbeoc:spii2023304&r=upt |