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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

(10%) Google

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

Research output

as
Jump to: Working papers Articles

Working papers

  1. B. Douglas Bernheim & Daniel Björkegren & Jeffrey Naecker & Michael Pollmann, 2021. "Causal Inference from Hypothetical Evaluations," NBER Working Papers 29616, National Bureau of Economic Research, Inc.
  2. 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.
  3. Jeffrey Naecker, 2015. "The Lives of Others: Predicting Donations with Non-Choice Responses," Discussion Papers 15-021, Stanford Institute for Economic Policy Research.
  4. 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.
  5. 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. James Andreoni & Deniz Aydin & Blake Barton & B. Douglas Bernheim & Jeffrey Naecker, 2020. "When Fair Isn’t Fair: Understanding Choice Reversals Involving Social Preferences," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1673-1711.
  2. Christine L. Exley & Jeffrey K. Naecker, 2017. "Observability Increases the Demand for Commitment Devices," Management Science, INFORMS, vol. 63(10), pages 3262-3267, October.
  3. 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. Erik Schokkaert & Benoît Tarroux, 2021. "Empirical research on ethical preferences: how popular is prioritarianism?," Working Papers 2104, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    2. Falch, Ranveig, 2021. "How Do People Trade Off Resources Between Quick and Slow Learners?," Discussion Paper Series in Economics 5/2021, Norwegian School of Economics, Department of Economics.
    3. Andreoni, James & Serra-Garcia, Marta, 2021. "Time inconsistent charitable giving," Journal of Public Economics, Elsevier, vol. 198(C).
    4. 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.
    5. Gago, Andrés, 2021. "Reciprocity and uncertainty: When do people forgive?," Journal of Economic Psychology, Elsevier, vol. 84(C).
    6. Sandro Ambuehl & B. Douglas Bernheim, 2021. "Interpreting the will of the people: a positive analysis of ordinal preference aggregation," ECON - Working Papers 395, Department of Economics - University of Zurich.
    7. Guilherme Lichand & Juliette Thibaud, 2020. "Parent-bias," ECON - Working Papers 369, Department of Economics - University of Zurich, revised Jun 2022.
    8. Duell, Dominik & Valasek, Justin, 2019. "Political polarization and selection in representative democracies," Journal of Economic Behavior & Organization, Elsevier, vol. 168(C), pages 132-165.
    9. Nguyen, Cuong Viet, 2019. "The effect of inequality in stakes on sharing behavior: Evidence from an experimental study," Economics Letters, Elsevier, vol. 184(C).
    10. Sandro Ambuehl & B. Douglas Bernheim, 2021. "Interpreting the Will of the People - A Positive Analysis of Ordinal Preference Aggregation," CESifo Working Paper Series 9317, CESifo.
    11. Peter Andre, 2021. "Shallow Meritocracy: An Experiment on Fairness Views," ECONtribute Discussion Papers Series 115, University of Bonn and University of Cologne, Germany.

  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. Meyer, Christian Johannes & Tripodi, Egon, 2021. "Image concerns in pledges to give blood: Evidence from a field experiment," Journal of Economic Psychology, Elsevier, vol. 87(C).
    2. Le Yaouanq, Yves, 2015. "Anticipating Preference Reversal"," TSE Working Papers 15-585, Toulouse School of Economics (TSE).
    3. 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.
    4. Andreoni, James & Serra-Garcia, Marta, 2021. "Time inconsistent charitable giving," Journal of Public Economics, Elsevier, vol. 198(C).
    5. 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.
    6. James Andreoni & Marta Serra-Garcia, 2019. "The Pledging Puzzle: How Can Revocable Promises Increase Charitable Giving," CESifo Working Paper Series 7965, CESifo.
    7. Mohamed Abouaziza, 2022. "Farmer constraints and relational contracts: evidence from agricultural value chains in East Africa," Economics PhD Theses 0122, Department of Economics, University of Sussex Business School.
    8. Himmler, Oliver & Jaeckle, Robert & Weinschenk, Philipp, 2017. "Soft Commitments, Reminders and Academic Performance," MPRA Paper 76832, University Library of Munich, Germany.
    9. Fosgaard, Toke R. & Soetevent, Adriaan R., 2022. "I will donate later! A field experiment on cell phone donations to charity," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 549-565.
    10. Andrej Woerner, 2021. "Overcoming Time Inconsistency with a Matched Bet: Theory and Evidence from Exercising," CESifo Working Paper Series 9503, CESifo.
    11. 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.
    12. 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. James Andreoni & Deniz Aydin & Blake Barton & B. Douglas Bernheim & Jeffrey Naecker, 2020. "When Fair Isn’t Fair: Understanding Choice Reversals Involving Social Preferences," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1673-1711.
    See citations under working paper version above.
  2. Christine L. Exley & Jeffrey K. Naecker, 2017. "Observability Increases the Demand for Commitment Devices," Management Science, INFORMS, vol. 63(10), pages 3262-3267, October.
    See citations under working paper version above.
  3. 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. Shoshan, Vered & Hazan, Tamir & Plonsky, Ori, 2023. "BEAST-Net: Learning novel behavioral insights using a neural network adaptation of a behavioral model," OSF Preprints kaeny, Center for Open Science.
    5. 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.
    6. 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.
    7. Yongtong Shao & Tao Xiong & Minghao Li & Dermot Hayes & Wendong Zhang & Wei Xie, 2021. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1082-1098, May.
    8. John A. Clithero & Jae Joon Lee & Joshua Tasoff, 2019. "Supervised Machine Learning for Eliciting Individual Demand," Papers 1904.13329, arXiv.org, revised Feb 2021.
    9. Halko, Marja-Liisa & Lappalainen, Olli & Sääksvuori, Lauri, 2021. "Do non-choice data reveal economic preferences? Evidence from biometric data and compensation-scheme choice," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 87-104.
    10. Drew Fudenberg & Wayne Gao & Annie Liang, 2020. "How Flexible is that Functional Form? Quantifying the Restrictiveness of Theories," Papers 2007.09213, arXiv.org, revised Jan 2023.
    11. Zachary Breig, 2020. "Prediction and Model Selection in Experiments," The Economic Record, The Economic Society of Australia, vol. 96(313), pages 153-176, June.
    12. 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 5 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 (5) 2013-08-05 2015-06-20 2015-12-01 2018-12-17 2022-02-07. Author is listed
  2. NEP-DCM: Discrete Choice Models (1) 2013-08-05
  3. NEP-ECM: Econometrics (1) 2022-02-07
  4. NEP-EVO: Evolutionary Economics (1) 2018-12-17
  5. NEP-HPE: History & Philosophy of Economics (1) 2018-12-17
  6. NEP-ORE: Operations Research (1) 2022-02-07
  7. NEP-UPT: Utility Models & Prospect Theory (1) 2013-08-05

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