Relevant bibliographies by topics / Time preferences

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Time preferences'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Time preferences"

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Miao, Bin, and Songfa Zhong. "Comment on “Risk Preferences Are Not Time Preferences”: Separating Risk and Time Preference." American Economic Review 105, no. 7 (2015): 2272–86. http://dx.doi.org/10.1257/aer.20131183.

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Andreoni and Sprenger (2012a,b) observe that utility functions are distinct for risk and time preferences, and show that their findings are consistent with a preference for certainty. We revisit this question in an enriched experimental setting in which subjects make intertemporal decisions under different risk conditions. The observed choice behavior supports a separation between risk attitude and intertemporal substitution rather than a preference for certainty. We further show that several models, including Epstein and Zin (1989); Chew and Epstein (1990); and Halevy (2008) exhibit such a se
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Andreoni, James, and Charles Sprenger. "Risk Preferences Are Not Time Preferences." American Economic Review 102, no. 7 (2012): 3357–76. http://dx.doi.org/10.1257/aer.102.7.3357.

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Risk and time are intertwined. The present is known while the future is inherently risky. This is problematic when studying time preferences since uncontrolled risk can generate apparently present-biased behavior. We systematically manipulate risk in an intertemporal choice experiment. Discounted expected utility performs well with risk, but when certainty is added common ratio predictions fail sharply. The data cannot be explained by prospect theory, hyperbolic discounting, or preferences for resolution of uncertainty, but seem consistent with a direct preference for certainty. The data sugge
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Kim, Chanwoo, Joonhyeok Lee, Eunwoo Kim, and Kyungjae Lee. "Time-Varying Preference Bandits for Robot Behavior Personalization." Applied Sciences 14, no. 23 (2024): 11002. http://dx.doi.org/10.3390/app142311002.

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Robots are increasingly employed in diverse services, from room cleaning to coffee preparation, necessitating an accurate understanding of user preferences. Traditional preference-based learning allows robots to learn these preferences through iterative queries about desired behaviors. However, these methods typically assume static human preferences. In this paper, we challenge this static assumption by considering the dynamic nature of human preferences and introduce the discounted preference bandit method to manage these changes. This algorithm adapts to evolving human preferences and suppor
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Rauer, Erik, Samik Basu, and Vasant Honavar. "Checking Consistency of CP-Theory Preferences in Polynomial Time." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 14 (2025): 15126–33. https://doi.org/10.1609/aaai.v39i14.33659.

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We investigate the problem of checking the consistency of qualitative preferences expressed in CP-theory. This problem is PSPACE-Complete even when the preferences are locally consistent or the preference variables have binary domain. We present a new sufficient condition for consistency of preferences and show that the condition can be checked in polynomial time in settings of practical relevance (locally consistent or binary domain preference variables). We further show how the resulting sufficient condition can be used to efficiently identify a subset of outcomes that are non-dominated with
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Zhou, Yinglian, and Jifeng Chen. "Time Series Geographic Social Network Dynamic Preference Group Query." International Journal of Information Systems in the Service Sector 13, no. 4 (2021): 18–39. http://dx.doi.org/10.4018/ijisss.2021100102.

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Driven by experience and social impact of the new life, user preferences continue to change over time. In order to make up for the shortcomings of existing geographic social network models that often cannot obtain user dynamic preferences, a time-series geographic social network model was constructed to detect user dynamic preferences, a dynamic preference value model was built for user dynamic preference evaluation, and a dynamic preferences group query (DPG) was proposed in this paper . In order to optimize the efficiency of the DPG query algorithm, the UTC-tree index user timing check-in re
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Chen, Shou, and Guangbing Li. "Time-Inconsistent Preferences, Retirement, and Increasing Life Expectancy." Mathematical Problems in Engineering 2019 (January 10, 2019): 1–9. http://dx.doi.org/10.1155/2019/8681471.

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We study consumption behavior, retirement decisions, and endogenous growth within a dynamic equilibrium when individuals have present-biased preferences. Compared to individual with exponential preferences, individual with hyperbolic preferences will choose to retire early for present-biased preferences but to delay retirement for the initial time preference rate. We extend the benchmark equilibrium model to age-dependent survival law and solve numerically the equilibrium effects. It shows that, at the same age, the consumption-capital ratio may have slightly positive effect on increasing life
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Cheung, Stephen L. "Comment on “Risk Preferences Are Not Time Preferences”: On the Elicitation of Time Preference under Conditions of Risk." American Economic Review 105, no. 7 (2015): 2242–60. http://dx.doi.org/10.1257/aer.20120946.

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Andreoni and Sprenger (2012a, b) report evidence that distinct utility functions govern choices under certainty and risk. I investigate the robustness of this result to the experimental design. I find that the effect disappears completely when a multiple price list instrument is used instead of a convex time budget design. Alternatively, the effect is reduced by half when sooner and later payment risks are realized using a single lottery instead of two independent lotteries. The result is thus at least partially driven by intertemporal diversification, supporting an explanation in terms of con
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BYKVIST, KRISTER. "All Time Preferences?" Theoria 65, no. 1 (2008): 36–54. http://dx.doi.org/10.1111/j.1755-2567.1999.tb00113.x.

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Cohen, Jonathan, Keith Marzilli Ericson, David Laibson, and John Myles White. "Measuring Time Preferences." Journal of Economic Literature 58, no. 2 (2020): 299–347. http://dx.doi.org/10.1257/jel.20191074.

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We review research that measures time preferences—i.e., preferences over intertemporal trade—offs. We distinguish between studies using financial flows, which we call “money earlier or later” (MEL) decisions, and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some fac
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Stamps, Arthur E. "Of Time and Preference: Temporal Stability of Environmental Preferences." Perceptual and Motor Skills 85, no. 3 (1997): 883–96. http://dx.doi.org/10.2466/pms.1997.85.3.883.

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Time is a central issue in discussions about art and in Berlyne's aesthetic theory. This article reports on the temporal stabilities of preferences for a novel and controversial building at three times after construction (2 years, 18 years, 23 years), and public preferences for 20 ordinary and noncontroversial buildings at three times over nine years. In all there were 5543 respondents. Analyses suggested that the initial response to the novel building was stable over the next 23 years, and the public responses for the 20 nonnovel buildings were stable over nine years. Implications for researc
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Dissertations / Theses on the topic "Time preferences"

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Rybáková, Nina. "Mezičasová volba osob romského etnika a většinové populace." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-75191.

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This thesis deals with the differences in time preferences, individual discount rates, among non-Romany (Czechs) and Romany ethnic group in the Czech Republic. Subjects of almost homogenous ethnic groups -- low income, low education, currently unemployed -- were subjected to experiments based on an in-depth questionnaire (Romany N = 35, N = 25 non-Romany). In addition to time preferences, their relationship with the socio-economic and demographic characteristics was inspected. The sub-tests showed a difference across ethnic groups in regard to the discounting models. Romany ethnic group is bet
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Shay, Nathan Michael. "Investigating Real-Time Employer-Based Ridesharing Preferences Based on Stated Preference Survey Data." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1471587439.

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Irvine, Alastair D. J. "Time preferences and the patient-doctor interaction." Thesis, University of Aberdeen, 2018. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=238373.

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Patients' non-adherence to treatment is a widespread phenomenon in healthcare. Time preferences (how individuals value outcomes over time) are one cause for non-adherence. Using quasi-hyperbolic discounting, two options in the future are weighted consistently. However, when the early option becomes available the weighting changes. This creates the potential for non-adherence. The agency relationship that exists between patients and doctors implies hidden information. When the patient's time preferences are hidden from the doctor, the doctor must choose how to recommend treatments. Exploring ho
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Preston, Charles. "Analysing Risk Preferences and Time Preferences with respect to Smoking Status and Smoking Intensity." Master's thesis, Faculty of Commerce, 2019. http://hdl.handle.net/11427/30954.

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Smoking is a leading cause of death worldwide, and thus the behavioural components need to be understood to mitigate the damage caused by the practice. The relationship between smoking and factors such as risk preferences and time preferences has been the subject of a growing body of literature. This paper evaluates experimental data from smokers and nonsmokers at the University of Cape Town collected in 2016 and 2017. Maximum likelihood estimation is used to estimate models of risk preferences and time preferences. The results highlight that smokers are less risk averse than non-smokers; that
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Chang, Hualei. "Continuous-time principal-agent problems with behavioral preferences." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526551.

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Licata, David. "Time-Varying Preferences, Risk Premia, and Tobin Constraints." Thesis, University of California, Irvine, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3669381.

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<p> The first chapter of my thesis explores monetary policy in a New Keynesian model with Markov-switching risk aversion. The second considers the implications for the macroeconomic and financial properties of an RBC model of the presence of habit formation. The third examines the result of adding the ``Tobin constraint" that shares equal the capital stock to a benchmark RBC mdoel. The underlying theme of these endeavors is rendering macroeconomic models more realistic via the introduction of time-varying preferences, non-linear modelling, and financial frictions.</p>
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Monteiro, Goncalo. "The growth process under time non-separable preferences /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/7384.

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Shores, Kindal Alayne. "The relationship of time perspective to time allocation, recreation experience preferences, and wellness." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4397.

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Time perspective, as measured with the Zimbardo Time Perspective Inventory (ZTPI), has been empirically linked to many behaviors including health behaviors, time spent with family and friends, and career decisions. This dissertation research builds on investigations of time perspective by testing hypotheses about the relationship between each of Zimbardo’s five time perspectives with residual time allocation, recreation experience preferences, and health and life satisfaction. Using a short questionnaire and time diary data, the relationship between how individuals frame time in the prese
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Cosma, Andrei Claudiu. "Real-Time Individual Thermal Preferences Prediction Using Visual Sensors." Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=13422566.

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<p> The thermal comfort of a building&rsquo;s occupants is an important aspect of building design. Providing an increased level of thermal comfort is critical given that humans spend the majority of the day indoors, and that their well-being, productivity, and comfort depend on the quality of these environments. In today&rsquo;s world, Heating, Ventilation, and Air Conditioning (HVAC) systems deliver heated or cooled air based on a fixed operating point or target temperature; individuals or building managers are able to adjust this operating point through human communication of dissatisfaction
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Pan, Jinrui. "Time and risk preferences : theoretical models for individual decision making." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/time-and-risk-preferences-theoretical-models-for-individual-decision-making(7cab3f50-870f-4c91-931b-5b98b96ee81e).html.

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Thesis submitted by Jinrui Pan for the Degree of Doctor of Philosophy in the University of Manchester, and entitled, “Time and Risk Preferences: Theoretical Models and Applications.” Date of submission 2014.This thesis makes contributions to two important areas of behavioural economics, namely individual decision making over time and under risk. Following the Introduction, Chapter 2 presents a new discounting function for analysing intertemporal choice. Liminal discounting, the model developed here, generalises exponential discounting in a parsimonious way. It allows for well-known departures,
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Books on the topic "Time preferences"

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Epstein, Larry G. Habits, interdependent preferences and time preference. Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1991.

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Rubinstein, Ariel. Renegotiation-proof implementation and time preferences. Suntory-Toyota International Centre for Economics and Related Disciplines, 1990.

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Drago, Francesco. Career consequences of hyperbolic time preferences. IZA, 2006.

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Klochko, Marianna A. Endogenous time preferences in social networks. Edward Elgar Pub., 2005.

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1942-, Ordeshook Peter C., ed. Endogenous time preferences in social networks. Edward Elgar Pub., 2006.

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Heaton, John. The interaction between time-nonseparable preferences and time aggregation. Sloan School of Management, Massachusetts Institute of Technology, 1990.

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Heaton, John. The interaction between time-nonseparable preferences and time aggregaton [i.e. aggregation]. Sloan School of Management, Massachusetts Institute of Technology, 1991.

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Lilja, Reija. Working time preferences at different phases of life. Office for Official Publications of the European Communities, 2001.

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Fagan, Colette. Gender, employment and working time preferences in Europe. Office for Official Publications of the European Communities, 2001.

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Gollier, Christian. Collective investment decision making with heterogeneous time preferences. National Bureau of Economic Research, 2003.

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Book chapters on the topic "Time preferences"

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Gerber, Anke. "Collective Time Preferences." In The Future of Economic Design. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18050-8_52.

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Vind, Karl. "Preferences over time." In Independence, Additivity, Uncertainty. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-24757-9_17.

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Ghisellini, Fabrizio, and Beryl Y. Chang. "Time and Preferences." In Behavioral Economics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75205-1_7.

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Pinto da Costa, Joaquim. "Weighted Clustering of Time Series." In Rankings and Preferences. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48344-2_6.

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Pinto da Costa, Joaquim. "A Weighted Principal Component Analysis (WPCA2) for Time Series Data." In Rankings and Preferences. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-48344-2_5.

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Sung, Jaeyoung. "Contracting in Continuous Time: Time-Additive Preferences." In Contract Theory: Discrete- and Continuous-Time Models. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5487-2_12.

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Sung, Jaeyoung. "Contracting in Continuous Time: Time-Multiplicative Preferences." In Contract Theory: Discrete- and Continuous-Time Models. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5487-2_5.

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Eisenführ, Franz, Martin Weber, and Thomas Langer. "Time preferences under certain expectations." In Rational Decision Making. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-02851-9_11.

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Miller, Kristie. "Do Time Biased Preferences Matter?" In The Normative Status of Time Bias. Routledge, 2024. http://dx.doi.org/10.4324/9781003528814-2.

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von Weizsäcker, Carl Christian. "Theorem 2 for the Continuous Time Model (Real-World Model)." In Freedom and Adaptive Preferences. Routledge, 2024. http://dx.doi.org/10.4324/9781032726410-19.

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Conference papers on the topic "Time preferences"

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Zhang, Mozhi, Pengyu Wang, Chenkun Tan, et al. "MetaAlign: Align Large Language Models with Diverse Preferences during Inference Time." In Findings of the Association for Computational Linguistics: NAACL 2025. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.findings-naacl.324.

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Maier, Alina, Mirabela Ioana Lupu, Cristina Maria Canja, Cristina Padureanu, Vasile Padureanu, and Alex Stefan Olaru. "MANAGE THE CREATION AND PRESENTATION OF BEVERAGE MENUS IN FOODSERVICE OPERATIONS." In 11th SWS International Scientific Conferences on SOCIAL SCIENCES - ISCSS 2024. SGEM WORLD SCIENCE, 2024. https://doi.org/10.35603/sws.iscss.2024/s04/31.

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Creating a beverage menu requires a meticulous approach based on a solid understanding of customer preferences, current industry trends and the operational capabilities of the foodservice establishment. Menu presentation should be clear, concise and attractive to facilitate quick understanding of available options and to promote sales. One of the key points emphasized is that beverage menus are not just product listings, but true communication and marketing tools. They must reflect the identity and concept of the establishment, respond to the needs and preferences of customers, but also inspir
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Venable, K. Brent. "Temporal Preferences." In 2011 Eighteenth International Symposium on Temporal Representation and Reasoning (TIME). IEEE, 2011. http://dx.doi.org/10.1109/time.2011.24.

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Mouhoub, M., and A. Sukpan. "Conditional and Composite Temporal Constraints with Preferences." In Thirteenth International Symposium on Temporal Representation and Reasoning (TIME'06). IEEE, 2006. http://dx.doi.org/10.1109/time.2006.10.

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Qi, Lianyong, Yuwen Liu, Weiming Liu, et al. "Counterfactual User Sequence Synthesis Augmented with Continuous Time Dynamic Preference Modeling for Sequential POI Recommendation." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/255.

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With the proliferation of Location-based Social Networks (LBSNs), user check-in data at Points-of-Interest (POIs) has surged, offering rich insights into user preferences. However, sequential POI recommendation systems always face two pivotal challenges. A challenge lies in the difficulty of modeling time in a discrete space, which fails to accurately capture the dynamic nature of user preferences. Another challenge is the inherent sparsity and noise in continuous POI recommendation, which hinder the recommendation process. To address these challenges, we propose counterfactual user sequence s
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Iwamura, Koji, Hitoshi Hayashi, Yoshitaka Tanimizu, and Nobuhiro Sugimura. "A Human Oriented Real-Time Scheduling for Autonomous Distributed Manufacturing System: Control of Preferences of Human Operators Aimed at Improving Productivity." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7183.

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A real-time scheduling method considering human operators has been proposed to generate suitable production schedules for human operators, manufacturing equipment and jobs real-timely in the autonomous distributed manufacturing systems (ADMSs). The proposed scheduling method gives the higher priorities to the human operators, and generates the production schedules based on preference values, in order to improve the human operator’s motivation. It was shown, through case studies, that the proposed real-time scheduling method is effective to satisfy the preferences of the human operators. Howeve
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Seimetz, Valentin, Rebecca Eifler, and Jörg Hoffmann. "Learning Temporal Plan Preferences from Examples: An Empirical Study." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/572.

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Temporal plan preferences are natural and important in a variety of applications. Yet users often find it difficult to formalize their preferences. Here we explore the possibility to learn preferences from example plans. Focusing on one preference at a time, the user is asked to annotate examples as good/bad. We leverage prior work on LTL formula learning to extract a preference from these examples. We conduct an empirical study of this approach in an oversubscription planning context, using hidden target formulas to emulate the user preferences. We explore four different methods for generatin
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Csáji, Gergely. "Popular and Dominant Matchings with Uncertain and Multimodal Preferences." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/303.

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We study the Popular Matching (PM) problem in multiple models, where the preferences of the agents in the instance may change or may be unknown or uncertain. In particular, we study an Uncertainty model, where each agent has a possible set of preference lists, a Multilayer model, where there are layers of preference profiles, and a Robust popularity model, where any agent may move some other agents up or down some places in his preference list. Our goal is always to find a matching that is popular in any possible preference profile. We study both one-sided (only one class of the agents have pr
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Dong, Andy, Tomonori Honda, and Maria C. Yang. "Time-Based Modeling of Linguistic Preference to Preferential Probability." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47074.

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In this paper, we present a method to estimate the likely concept a committee of designers will select given their verbalized preferences toward each alternative. In order to perform this estimation, we present a new method of preference elicitation based on natural language. First, we show a way to model preference in the natural language of appraisal, which describes the degree of intensity and the uncertainty of preference based upon gradable semantic resources to express appraisals. We then show a way to map linguistic appraisals into probability distribution functions. Finally, we present
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Lutkenhouse, Thomas, Michael L. Nelson, and Johan Bollen. "Distributed, real-time computation of community preferences." In the sixteenth ACM conference. ACM Press, 2005. http://dx.doi.org/10.1145/1083356.1083374.

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Reports on the topic "Time preferences"

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Cohen, Jonathan, Keith Marzilli Ericson, David Laibson, and John Myles White. Measuring Time Preferences. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22455.

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Andreoni, James, Michael Kuhn, and Charles Sprenger. On Measuring Time Preferences. National Bureau of Economic Research, 2013. http://dx.doi.org/10.3386/w19392.

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Andreoni, James, and Charles Sprenger. Risk Preferences Are Not Time Preferences: Discounted Expected Utility with a Disproportionate Preference for Certainty. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16348.

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Bradford, David, Charles Courtemanche, Garth Heutel, Patrick McAlvanah, and Christopher Ruhm. Time Preferences and Consumer Behavior. National Bureau of Economic Research, 2014. http://dx.doi.org/10.3386/w20320.

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Brownback, Andy, Alex Imas, and Michael Kuhn. Time Preferences and Food Choice. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31726.

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Andreoni, James, and Charles Sprenger. Estimating Time Preferences from Convex Budgets. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w16347.

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Newell, Richard, and Juha Siikamaki. Individual Time Preferences and Energy Efficiency. National Bureau of Economic Research, 2015. http://dx.doi.org/10.3386/w20969.

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Grenadier, Steven, and Neng Wang. Investment Under Uncertainty and Time-Inconsistent Preferences. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/w12042.

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Agranov, Marina, Jeongbin Kim, and Leeat Yariv. Coordination with Differential Time Preferences: Experimental Evidence. National Bureau of Economic Research, 2023. http://dx.doi.org/10.3386/w31288.

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Clark, Robert, Robert Hammond, Christelle Khalaf, and Melinda Sandler Morrill. Planning for Retirement? The Importance of Time Preferences. National Bureau of Economic Research, 2017. http://dx.doi.org/10.3386/w23501.

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