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{
    "pk": 27789,
    "title": "Noisy Time Preference",
    "subtitle": null,
    "abstract": "People’s desire to be patient or impatient can fluctuate from\nmoment to moment, yet little is known about the effects of\nvariability in time preference on intertemporal choice\nbehavior. We examine this issue through the lens of an\nexponential discounting model with noisy discount factors. We\nshow that such a model can generate decreasing patience over\ntime, accounting for behavioral patterns typically attributed to\nhyperbolic discounting, while also making reasonable\npredictions regarding violations of intertemporal dominance.\nAdditionally, two experiments reveal that many participants do\ndisplay noise in their discount factors, and that a noisy discount\nfactor model outperforms hyperbolic models in terms of\nquantitative fit. Ultimately the majority of participants are best\ndescribed by some type of exponential discounting model\n(with or without noisy discount factors). These results indicate\nthat it may not be necessary to assume alternate forms of non-\nexponential discounting, as long as the discount factors in an\nexponential model are permitted to vary at random. These\nresults also highlight the importance of allowing for different\nsources of noise in choice modeling.People’s desire to be patient or impatient can fluctuate from\nmoment to moment, yet little is known about the effects of\nvariability in time preference on intertemporal choice\nbehavior. We examine this issue through the lens of an\nexponential discounting model with noisy discount factors. We\nshow that such a model can generate decreasing patience over\ntime, accounting for behavioral patterns typically attributed to\nhyperbolic discounting, while also making reasonable\npredictions regarding violations of intertemporal dominance.\nAdditionally, two experiments reveal that many participants do\ndisplay noise in their discount factors, and that a noisy discount\nfactor model outperforms hyperbolic models in terms of\nquantitative fit. Ultimately the majority of participants are best\ndescribed by some type of exponential discounting model\n(with or without noisy discount factors). These results indicate\nthat it may not be necessary to assume alternate forms of non-\nexponential discounting, as long as the discount factors in an\nexponential model are permitted to vary at random. These\nresults also highlight the importance of allowing for different\nsources of noise in choice modeling.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "decision making"
        },
        {
            "word": "intertemporal choice"
        },
        {
            "word": "Noise"
        },
        {
            "word": "variability"
        },
        {
            "word": "Computational Modeling"
        }
    ],
    "section": "Publication-based-Talks",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/4d85z8pr",
    "frozenauthors": [
        {
            "first_name": "Lisheng",
            "middle_name": "",
            "last_name": "He",
            "name_suffix": "",
            "institution": "UPenn",
            "department": ""
        },
        {
            "first_name": "Sudeep",
            "middle_name": "",
            "last_name": "Bhatia",
            "name_suffix": "",
            "institution": "UPenn",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2018-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27789/galley/17429/download/"
        }
    ]
}