Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Jeffrey Naecker"'
Publikováno v:
Journal of Political Economy. 128:1673-1711
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d7af7bdbdae67135dabbf06e1df66ff
https://doi.org/10.1086/705549
https://doi.org/10.1086/705549
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54121d4ba33440d855ebf9e11938f16b
https://doi.org/10.2139/ssrn.3998789
https://doi.org/10.2139/ssrn.3998789
Using methods from machine learning to evaluate behavioral models of choice under risk and ambiguity
Publikováno v:
Journal of Economic Behavior & Organization. 133:373-384
How can behavioral science incorporate tools from machine learning (ML)? We propose that ML models can be used as upper bounds for the “explainable” variance in a given data set and thus serve as upper bounds for the potential power of a theory.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c7cf4bdb3507f7136dde85b701e213b
https://doi.org/10.1016/j.jebo.2016.08.017
https://doi.org/10.1016/j.jebo.2016.08.017
Publikováno v:
SSRN Electronic Journal.
How do people think about fairness in settings with uncertainty? One view holds that fairness requires equality of opportunity; another holds that it requires equality of outcomes. Relative to the resolution of uncertainty, the first view takes an ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b0615608ac1a251179bd99b4d057a0a
https://doi.org/10.2139/ssrn.2763318
https://doi.org/10.2139/ssrn.2763318
Autor:
Jeffrey Naecker
There is significant variation in the percentage of adults registered as organ donors across the United States. Some of this variation may be due to characteristics of the sign-up process, in particular the form that is used when state residents rene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::648bcfd67b87ec8d6d5fcc7c9a16ce6c
http://www-siepr.stanford.edu/repec/sip/15-021.pdf
http://www-siepr.stanford.edu/repec/sip/15-021.pdf
Publikováno v:
SSRN Electronic Journal.
How can behavioral scientists incorporate tools from machine learning (ML)? We propose that ML models can be used as upper bounds for the “explainable” variance in a given data set and thus serve as upper bounds for the potential power of a theor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb440789315fdc51c0607465f362d5cc
https://doi.org/10.2139/ssrn.2548564
https://doi.org/10.2139/ssrn.2548564
Publikováno v:
Journal of Political Economy. Dec2020, Vol. 128 Issue 12, p4679-4687. 9p.
Autor:
Jeffrey Naecker, Christine L. Exley
Publikováno v:
SSRN Electronic Journal.
Previous research often interprets the choice to restrict one’s future opportunity set as evidence for sophisticated time inconsistency. We propose an additional mechanism that may contribute to the demand for commitment technology: the desire to s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33c87148e9739202e75902a1ab491475
https://doi.org/10.2139/ssrn.2498145
https://doi.org/10.2139/ssrn.2498145
A central task in microeconomics is to predict choices in as-yet-unobserved situations (e.g., after some policy intervention). Standard approaches can prove problematic when sufficiently similar changes have not been observed or do not have observabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::b3027bfa1e6df81ecb4598d457fcdab6
http://www.nber.org/papers/w19269.pdf
http://www.nber.org/papers/w19269.pdf