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Jeffrey Naecker

Personal Details

First Name:Jeffrey
Middle Name:Kendell
Last Name:Naecker
Suffix:
RePEc Short-ID:pna439
[This author has chosen not to make the email address public]
http://jeffnaecker.com
Twitter: @jnaecker
Terminal Degree:2015 Department of Economics; Stanford University (from RePEc Genealogy)

Affiliation

Google

https://research.google/
Mountain View, CA

Research output

as
Jump to: Working papers Articles

Working papers

  1. James Andreoni & Deniz Aydin & Blake Barton & B. Douglas Bernheim & Jeffrey Naecker, 2018. "When Fair Isn't Fair: Understanding Choice Reversals Involving Social Preferences," NBER Working Papers 25257, National Bureau of Economic Research, Inc.
  2. Jeffrey Naecker, 2015. "The Lives of Others: Predicting Donations with Non-Choice Responses," Discussion Papers 15-021, Stanford Institute for Economic Policy Research.
  3. Christine L. Exley & Jeffrey K. Naecker, 2015. "Observability Increases the Demand for Commitment Devices," Harvard Business School Working Papers 16-064, Harvard Business School, revised Mar 2016.
  4. B. Douglas Bernheim & Daniel Bjorkegren & Jeffrey Naecker & Antonio Rangel, 2013. "Non-Choice Evaluations Predict Behavioral Responses to Changes in Economic Conditions," NBER Working Papers 19269, National Bureau of Economic Research, Inc.

Articles

  1. Peysakhovich, Alexander & Naecker, Jeffrey, 2017. "Using methods from machine learning to evaluate behavioral models of choice under risk and ambiguity," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 373-384.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. James Andreoni & Deniz Aydin & Blake Barton & B. Douglas Bernheim & Jeffrey Naecker, 2018. "When Fair Isn't Fair: Understanding Choice Reversals Involving Social Preferences," NBER Working Papers 25257, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ranveig Falch, 2021. "How Do People Trade Off Resources Between Quick and Slow Learners?," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2021_04, Max Planck Institute for Research on Collective Goods.
    2. James Berry & Rebecca Dizon-Ross & Maulik Jagnani, 2020. "Not Playing Favorites: An Experiment on Parental Fairness Preferences," Working Papers 2020-06, Becker Friedman Institute for Research In Economics.
    3. Guilherme Lichand & Juliette Thibaud, 2020. "Parent-bias," ECON - Working Papers 369, Department of Economics - University of Zurich.
    4. Duell, Dominik & Valasek, Justin, 2019. "Political polarization and selection in representative democracies," Journal of Economic Behavior & Organization, Elsevier, vol. 168(C), pages 132-165.
    5. Nguyen, Cuong Viet, 2019. "The effect of inequality in stakes on sharing behavior: Evidence from an experimental study," Economics Letters, Elsevier, vol. 184(C).

  2. Jeffrey Naecker, 2015. "The Lives of Others: Predicting Donations with Non-Choice Responses," Discussion Papers 15-021, Stanford Institute for Economic Policy Research.

    Cited by:

    1. John A. Clithero & Jae Joon Lee & Joshua Tasoff, 2019. "Supervised Machine Learning for Eliciting Individual Demand," Papers 1904.13329, arXiv.org, revised Feb 2021.

  3. Christine L. Exley & Jeffrey K. Naecker, 2015. "Observability Increases the Demand for Commitment Devices," Harvard Business School Working Papers 16-064, Harvard Business School, revised Mar 2016.

    Cited by:

    1. Le Yaouanq, Yves, 2015. "Anticipating Preference Reversal"," TSE Working Papers 15-585, Toulouse School of Economics (TSE).
    2. Frank Schilbach, 2019. "Alcohol and Self-Control: A Field Experiment in India," American Economic Review, American Economic Association, vol. 109(4), pages 1290-1322, April.
    3. Che-Wei Liu & Guodong (Gordon) Gao & Ritu Agarwal, 2019. "Unraveling the “Social” in Social Norms: The Conditioning Effect of User Connectivity," Information Systems Research, INFORMS, vol. 30(4), pages 1272-1295, April.
    4. James Andreoni & Marta Serra-Garcia, 2019. "The Pledging Puzzle: How Can Revocable Promises Increase Charitable Giving," CESifo Working Paper Series 7965, CESifo.
    5. Himmler, Oliver & Jaeckle, Robert & Weinschenk, Philipp, 2017. "Soft Commitments, Reminders and Academic Performance," MPRA Paper 76832, University Library of Munich, Germany.
    6. Segovia, Michelle S. & Palma, Marco A. & Nayga, Rodolfo M., 2020. "Can episodic future thinking affect food choices?," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 371-389.
    7. Mariana Carrera & Heather Royer & Mark Stehr & Justin Sydnor & Dmitry Taubinsky, 2019. "Who Chooses Commitment? Evidence and Welfare Implications," NBER Working Papers 26161, National Bureau of Economic Research, Inc.

  4. B. Douglas Bernheim & Daniel Bjorkegren & Jeffrey Naecker & Antonio Rangel, 2013. "Non-Choice Evaluations Predict Behavioral Responses to Changes in Economic Conditions," NBER Working Papers 19269, National Bureau of Economic Research, Inc.

    Cited by:

    1. Raj Chetty, 2015. "Behavioral Economics and Public Policy: A Pragmatic Perspective," American Economic Review, American Economic Association, vol. 105(5), pages 1-33, May.
    2. Diane Coyle & Leonard Nakamura, 2019. "Towards a Framework for Time Use, Welfare and Household-centric Economic Measurement," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-01, Economic Statistics Centre of Excellence (ESCoE).
    3. John A. Clithero & Jae Joon Lee & Joshua Tasoff, 2019. "Supervised Machine Learning for Eliciting Individual Demand," Papers 1904.13329, arXiv.org, revised Feb 2021.
    4. Bart Los & Marcel P. Timmer, 2018. "Measuring Bilateral Exports of Value Added: A Unified Framework," NBER Working Papers 24896, National Bureau of Economic Research, Inc.

Articles

  1. Peysakhovich, Alexander & Naecker, Jeffrey, 2017. "Using methods from machine learning to evaluate behavioral models of choice under risk and ambiguity," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 373-384.

    Cited by:

    1. Daniele Guariso, 2018. "Terrorist Attacks and Immigration Rhetoric: A Natural Experiment on British MPs," Working Paper Series 1218, Department of Economics, University of Sussex Business School.
    2. Richard J. Arend, 2020. "Strategic decision-making under ambiguity: a new problem space and a proposed optimization approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1231-1251, November.
    3. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," NBER Working Papers 25200, National Bureau of Economic Research, Inc.
    4. Jon Kleinberg & Annie Liang & Sendhil Mullainathan, 2017. "The Theory is Predictive, but is it Complete? An Application to Human Perception of Randomness," PIER Working Paper Archive 18-010, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Aug 2017.
    5. Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    6. John A. Clithero & Jae Joon Lee & Joshua Tasoff, 2019. "Supervised Machine Learning for Eliciting Individual Demand," Papers 1904.13329, arXiv.org, revised Feb 2021.
    7. Yongtong Shao & Minghao Li & Dermot J. Hayes & Wendong Zhang & Tao Xiong & Wei Xie, 2020. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," Center for Agricultural and Rural Development (CARD) Publications 20-wp607, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    8. Drew Fudenberg & Wayne Gao & Annie Liang, 2020. "How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories," Papers 2007.09213, arXiv.org.
    9. Zachary Breig, 2020. "Prediction and Model Selection in Experiments," The Economic Record, The Economic Society of Australia, vol. 96(313), pages 153-176, June.
    10. Drew Fudenberg & Jon Kleinberg & Annie Liang & Sendhil Mullainathan, 2019. "Measuring the Completeness of Theories," Papers 1910.07022, arXiv.org.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-EXP: Experimental Economics (4) 2013-08-05 2015-06-20 2015-12-01 2018-12-17. Author is listed
  2. NEP-DCM: Discrete Choice Models (1) 2013-08-05. Author is listed
  3. NEP-EVO: Evolutionary Economics (1) 2018-12-17. Author is listed
  4. NEP-HPE: History & Philosophy of Economics (1) 2018-12-17. Author is listed
  5. NEP-UPT: Utility Models & Prospect Theory (1) 2013-08-05. Author is listed

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