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Dean Eckles

Personal Details

First Name:Dean
Middle Name:
Last Name:Eckles
Suffix:
RePEc Short-ID:pec52
[This author has chosen not to make the email address public]
http://deaneckles.com

Affiliation

Sloan School of Management
Massachusetts Institute of Technology (MIT)

Cambridge, Massachusetts (United States)
http://mitsloan.mit.edu/
RePEc:edi:ssmitus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Athey, Susan & Eckles, Dean & Imbens, Guido W., 2015. "Exact P-Values for Network Interference," Research Papers 3287, Stanford University, Graduate School of Business.

Articles

  1. Dean Eckles & Maurits Kaptein, 2019. "Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences," SAGE Open, , vol. 9(2), pages 21582440198, June.
  2. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
  3. Dean Eckles & Brett R. Gordon & Garrett A. Johnson, 2018. "Field studies of psychologically targeted ads face threats to internal validity," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(23), pages 5254-5255, June.
  4. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
  5. Eckles Dean & Karrer Brian & Ugander Johan, 2017. "Design and Analysis of Experiments in Networks: Reducing Bias from Interference," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-23, March.
  6. Kaptein, Maurits & Eckles, Dean, 2012. "Heterogeneity in the Effects of Online Persuasion," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 176-188.

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. Athey, Susan & Eckles, Dean & Imbens, Guido W., 2015. "Exact P-Values for Network Interference," Research Papers 3287, Stanford University, Graduate School of Business.

    Cited by:

    1. Athey, Susan & Luca, Michael, 2018. "Economists (and Economics) in Tech Companies," Research Papers 3735, Stanford University, Graduate School of Business.
    2. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: a Survey," AMSE Working Papers 1936, Aix-Marseille School of Economics, France.
    3. Cruces, Guillermo & Tortarolo, Dario & Vazquez-Bare, Gonzalo, 2024. "Design of Partial Population Experiments with an Application to Spillovers in Tax Compliance," IZA Discussion Papers 17256, Institute of Labor Economics (IZA).
    4. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    5. Toru Kitagawa & Guanyi Wang, 2021. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP28/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Michael Pollmann, 2020. "Causal Inference for Spatial Treatments," Papers 2011.00373, arXiv.org, revised Jan 2023.
    7. Kosuke Imai & Zhichao Jiang, 2020. "Identification and sensitivity analysis of contagion effects in randomized placebo‐controlled trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1637-1657, October.
    8. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 202010, University of California at Riverside, Department of Economics, revised Mar 2020.
    9. Evan Munro & Xu Kuang & Stefan Wager, 2021. "Treatment Effects in Market Equilibrium," Papers 2109.11647, arXiv.org, revised Jun 2024.
    10. Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
    11. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    12. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    13. Tadao Hoshino & Takahide Yanagi, 2021. "Causal Inference with Noncompliance and Unknown Interference," Papers 2108.07455, arXiv.org, revised Oct 2023.
    14. Silvia Noirjean & Marco Mariani & Alessandra Mattei & Fabrizia Mealli, 2020. "Exploiting network information to disentangle spillover effects in a field experiment on teens' museum attendance," Papers 2011.11023, arXiv.org, revised May 2022.
    15. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
    16. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2021.
    17. Bryan S. Graham, 2019. "Network Data," NBER Working Papers 26577, National Bureau of Economic Research, Inc.
    18. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    19. Han, Kevin & Basse, Guillaume & Bojinov, Iavor, 2024. "Population interference in panel experiments," Journal of Econometrics, Elsevier, vol. 238(1).
    20. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    21. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    22. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    23. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    24. Yuehao Bai & Azeem M. Shaikh & Max Tabord-Meehan, 2024. "A Primer on the Analysis of Randomized Experiments and a Survey of some Recent Advances," Papers 2405.03910, arXiv.org.
    25. Wooyong Jo & Sarang Sunder & Jeonghye Choi & Minakshi Trivedi, 2020. "Protecting Consumers from Themselves: Assessing Consequences of Usage Restriction Laws on Online Game Usage and Spending," Marketing Science, INFORMS, vol. 39(1), pages 117-133, January.
    26. Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Weintraub, 2020. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Papers 2002.05670, arXiv.org, revised Sep 2021.
    27. Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
    28. Vasiliki Koutra & Steven G. Gilmour & Ben M. Parker & Andrew Mead, 2023. "Design of Agricultural Field Experiments Accounting for both Complex Blocking Structures and Network Effects," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 526-548, September.
    29. Luofeng Liao & Yuan Gao & Christian Kroer, 2022. "Statistical Inference for Fisher Market Equilibrium," Papers 2209.15422, arXiv.org.
    30. Fafchamps, Marcel & Caeyers, Bet, 2020. "Exclusion bias and the estimation of peer effects," CEPR Discussion Papers 14386, C.E.P.R. Discussion Papers.
    31. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    32. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    33. Eckles Dean & Karrer Brian & Ugander Johan, 2017. "Design and Analysis of Experiments in Networks: Reducing Bias from Interference," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-23, March.
    34. Ariel Boyarsky & Hongseok Namkoong & Jean Pouget-Abadie, 2023. "Modeling Interference Using Experiment Roll-out," Papers 2305.10728, arXiv.org, revised Aug 2023.
    35. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
    36. Björkegren, Daniel & Karaca, Burak Ceyhun, 2022. "Network adoption subsidies: A digital evaluation of a rural mobile phone program in Rwanda," Journal of Development Economics, Elsevier, vol. 154(C).
    37. Tadao Hoshino & Takahide Yanagi, 2023. "Randomization Test for the Specification of Interference Structure," Papers 2301.05580, arXiv.org, revised Dec 2023.
    38. John McHale & Jason Harold & Jen-Chung Mei & Akhil Sasidharan & Anil Yadav, 2023. "Stars as catalysts: an event-study analysis of the impact of star-scientist recruitment on local research performance in a small open economy," Journal of Economic Geography, Oxford University Press, vol. 23(2), pages 343-369.
    39. Luofeng Liao & Christian Kroer, 2023. "Statistical Inference and A/B Testing for First-Price Pacing Equilibria," Papers 2301.02276, arXiv.org, revised Jun 2023.
    40. Guido W. Imbens, 2021. "Statistical Significance, p-Values, and the Reporting of Uncertainty," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 157-174, Summer.
    41. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
    42. Hannah Li & Geng Zhao & Ramesh Johari & Gabriel Y. Weintraub, 2021. "Interference, Bias, and Variance in Two-Sided Marketplace Experimentation: Guidance for Platforms," Papers 2104.12222, arXiv.org.
    43. Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Aug 2024.
    44. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    45. Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Y. Weintraub, 2022. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Management Science, INFORMS, vol. 68(10), pages 7069-7089, October.
    46. Vazquez-Bare, Gonzalo, 2023. "Identification and estimation of spillover effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 237(1).
    47. Vivek F. Farias & Andrew A. Li & Tianyi Peng & Andrew Zheng, 2022. "Markovian Interference in Experiments," Papers 2206.02371, arXiv.org, revised Jun 2022.
    48. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    49. Julius Owusu, 2023. "Randomization Inference of Heterogeneous Treatment Effects under Network Interference," Papers 2308.00202, arXiv.org, revised Jan 2024.
    50. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised Jun 2023.
    51. David M. Ritzwoller & Joseph P. Romano & Azeem M. Shaikh, 2024. "Randomization Inference: Theory and Applications," Papers 2406.09521, arXiv.org.
    52. Kitagawa, Toru & Wang, Guanyi, 2023. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," Journal of Econometrics, Elsevier, vol. 232(1), pages 109-131.
    53. Lina Zhang, 2020. "Spillovers of Program Benefits with Missing Network Links," Papers 2009.09614, arXiv.org, revised Aug 2024.
    54. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    55. Anish Agarwal & Sarah H. Cen & Devavrat Shah & Christina Lee Yu, 2022. "Network Synthetic Interventions: A Causal Framework for Panel Data Under Network Interference," Papers 2210.11355, arXiv.org, revised Oct 2023.
    56. Guillermo Cruces & Dario Tortarolo & Gonzalo Vazquez-Bare, 2022. "Design of two-stage experiments with an application to spillovers in tax compliance," IFS Working Papers W22/32, Institute for Fiscal Studies.
    57. Toru Kitagawa & Guanyi Wang, 2020. "Who should get vaccinated? Individualized allocation of vaccines over SIR network," CeMMAP working papers CWP59/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    58. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
    59. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    60. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings: separating definitions and assumptions," Papers 2103.06471, arXiv.org, revised Mar 2023.
    61. Nathan Kallus, 2023. "Treatment Effect Risk: Bounds and Inference," Management Science, INFORMS, vol. 69(8), pages 4579-4590, August.
    62. Xiaokang Luo & Tirthankar Dasgupta & Minge Xie & Regina Y. Liu, 2021. "Leveraging the Fisher randomization test using confidence distributions: Inference, combination and fusion learning," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(4), pages 777-797, September.
    63. Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
    64. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.
    65. Michael P. Leung & Pantelis Loupos, 2022. "Graph Neural Networks for Causal Inference Under Network Confounding," Papers 2211.07823, arXiv.org, revised Mar 2024.
    66. Chabé-Ferret, Sylvain & Reynaud, Arnaud & Tène, Eva, 2021. "Water Quality, Policy Diffusion Effects and Farmers’ Behavior," TSE Working Papers 21-1229, Toulouse School of Economics (TSE).
    67. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.

Articles

  1. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
    See citations under working paper version above.
  2. Dean Eckles & Brett R. Gordon & Garrett A. Johnson, 2018. "Field studies of psychologically targeted ads face threats to internal validity," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(23), pages 5254-5255, June.

    Cited by:

    1. Susan Athey & Kristen Grabarz & Michael Luca & Nils C. Wernerfelt, 2022. "Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines," NBER Working Papers 30273, National Bureau of Economic Research, Inc.
    2. Orazi, Davide C. & Johnston, Allen C., 2020. "Running field experiments using Facebook split test," Journal of Business Research, Elsevier, vol. 118(C), pages 189-198.
    3. Susan Athey & Kristen Grabarz & Michael Luca & Nils Wernerfelt, 2022. "The Effectiveness of Digital Interventions on COVID-19 Attitudes and Beliefs," Papers 2206.10214, arXiv.org.
    4. Christina Uhl & Nadia Abou Nabout & Klaus Miller, 2020. "How Much Ad Viewability is Enough? The Effect of Display Ad Viewability on Advertising Effectiveness," Papers 2008.12132, arXiv.org.
    5. Campbell, Colin & Sands, Sean & Treen, Emily & McFerran, Brent, 2021. "Fleeting, But Not Forgotten: Ephemerality as a Means to Increase Recall of Advertising," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 96-105.

  3. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.

    Cited by:

    1. Joël Cariolle & Yasmine Elkhateeb & Mathilde Maurel, 2024. "Misinformation technology: Internet use and political misperceptions in Africa," Post-Print hal-04423752, HAL.
    2. Jiménez Durán, Rafael & Muller, Karsten & Schwarz, Carlo, 2024. "The Effect of Content Moderation on Online and Offline Hate: Evidence from Germany’s NetzDG," CAGE Online Working Paper Series 701, Competitive Advantage in the Global Economy (CAGE).
    3. Oppermann, Daniel, 2021. "Corona protests in Germany: insights into a new movement," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 25-40.
    4. Cristian Vaccari & Augusto Valeriani, 2018. "Digital Political Talk and Political Participation: Comparing Established and Third Wave Democracies," SAGE Open, , vol. 8(2), pages 21582440187, June.
    5. Ekaterina Zhuravskaya & Maria Petrova & Ruben Enikolopov, 2020. "Political Effects of the Internet and Social Media," PSE-Ecole d'économie de Paris (Postprint) halshs-02491741, HAL.
    6. Fujiwara, Thomas & Muller, Karsten & Schwarz, Carlo, 2024. "The Effect of Social Media on Elections: Evidence from the United States," CAGE Online Working Paper Series 700, Competitive Advantage in the Global Economy (CAGE).
    7. Joël Cariolle & Yasmine Elkhateeb & Mathilde Maurel, 2022. "(Mis-)information technology: Internet use and perception of democracy in Africa," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03628023, HAL.
    8. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    9. Claire E. Robertson & Nicolas Pröllochs & Kaoru Schwarzenegger & Philip Pärnamets & Jay J. Bavel & Stefan Feuerriegel, 2023. "Negativity drives online news consumption," Nature Human Behaviour, Nature, vol. 7(5), pages 812-822, May.
    10. Adiyana Sharag-Eldin & Xinyue Ye & Brian Spitzberg & Ming-Hsiang Tsou, 2019. "The role of space and place in social media communication: two case studies of policy perspectives," Journal of Computational Social Science, Springer, vol. 2(2), pages 221-244, July.
    11. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Apr 2024.
    12. Tatiana Hajdúková, 2024. "Techniques for Manipulating Public Opinion in the Online Space During an Election Campaign as a Hybrid Threat," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 13, January.
    13. Pruethsan Sutthichaimethee & Danupon Ariyasajjakorn, 2021. "The Management Efficiency of the Sustainable Development Policy under Thailand s Energy Law: Enriching the SEM-based on the ARIMAXi model," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 472-482.
    14. Qing Xu & Joshua Yang & Michael R. Haupt & Mingxiang Cai & Matthew C. Nali & Tim K. Mackey, 2021. "Digital Surveillance to Identify California Alternative and Emerging Tobacco Industry Policy Influence and Mobilization on Facebook," IJERPH, MDPI, vol. 18(21), pages 1-12, October.

  4. Eckles Dean & Karrer Brian & Ugander Johan, 2017. "Design and Analysis of Experiments in Networks: Reducing Bias from Interference," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-23, March.

    Cited by:

    1. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    2. Yuchen Hu & Shuangning Li & Stefan Wager, 2021. "Average Direct and Indirect Causal Effects under Interference," Papers 2104.03802, arXiv.org, revised Jan 2022.
    3. Ruoxuan Xiong & Alex Chin & Sean J. Taylor, 2024. "Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs," Papers 2406.06768, arXiv.org.
    4. Christopher Harshaw & Fredrik Savje & Yitan Wang, 2022. "A Design-Based Riesz Representation Framework for Randomized Experiments," Papers 2210.08698, arXiv.org, revised Oct 2022.
    5. Shaina J. Alexandria & Michael G. Hudgens & Allison E. Aiello, 2023. "Assessing intervention effects in a randomized trial within a social network," Biometrics, The International Biometric Society, vol. 79(2), pages 1409-1419, June.
    6. Michael P. Leung, 2021. "Rate-Optimal Cluster-Randomized Designs for Spatial Interference," Papers 2111.04219, arXiv.org, revised Sep 2022.
    7. Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
    8. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    9. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    10. Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," PSE-Ecole d'économie de Paris (Postprint) hal-03098058, HAL.
    11. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
    12. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2021.
    13. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    14. Supriya Tiwari & Pallavi Basu, 2024. "Quasi-randomization tests for network interference," Papers 2403.16673, arXiv.org, revised Oct 2024.
    15. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
    16. Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
    17. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    18. Susan Athey & Dean Eckles & Guido W. Imbens, 2015. "Exact P-values for Network Interference," NBER Working Papers 21313, National Bureau of Economic Research, Inc.
    19. Davide Viviano & Lihua Lei & Guido Imbens & Brian Karrer & Okke Schrijvers & Liang Shi, 2023. "Causal clustering: design of cluster experiments under network interference," Papers 2310.14983, arXiv.org, revised Jan 2024.
    20. Miguel Godinho de Matos & Pedro Ferreira & Rodrigo Belo, 2018. "Target the Ego or Target the Group: Evidence from a Randomized Experiment in Proactive Churn Management," Marketing Science, INFORMS, vol. 37(5), pages 793-811, September.
    21. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.
    22. Ariel Boyarsky & Hongseok Namkoong & Jean Pouget-Abadie, 2023. "Modeling Interference Using Experiment Roll-out," Papers 2305.10728, arXiv.org, revised Aug 2023.
    23. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
    24. Evan Munro & David Jones & Jennifer Brennan & Roland Nelet & Vahab Mirrokni & Jean Pouget-Abadie, 2023. "Causal Estimation of User Learning in Personalized Systems," Papers 2306.00485, arXiv.org.
    25. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    26. Guillaume W Basse & Edoardo M Airoldi, 2018. "Model-assisted design of experiments in the presence of network-correlated outcomes," Biometrika, Biometrika Trust, vol. 105(4), pages 849-858.
    27. Vivek F. Farias & Andrew A. Li & Tianyi Peng & Andrew Zheng, 2022. "Markovian Interference in Experiments," Papers 2206.02371, arXiv.org, revised Jun 2022.
    28. David Holtz & Sinan Aral, 2020. "Limiting Bias from Test-Control Interference in Online Marketplace Experiments," Papers 2004.12162, arXiv.org.
    29. Nian Si, 2023. "Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach," Papers 2310.17496, arXiv.org, revised Apr 2024.
    30. Karlsson, Maria & Lundin, Mathias, 2016. "On statistical methods for labor market evaluation under interference between units," Working Paper Series 2016:24, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    31. Ozan Candogan & Chen Chen & Rad Niazadeh, 2024. "Correlated Cluster-Based Randomized Experiments: Robust Variance Minimization," Management Science, INFORMS, vol. 70(6), pages 4069-4086, June.
    32. Anish Agarwal & Sarah H. Cen & Devavrat Shah & Christina Lee Yu, 2022. "Network Synthetic Interventions: A Causal Framework for Panel Data Under Network Interference," Papers 2210.11355, arXiv.org, revised Oct 2023.
    33. Ali Goli & Anja Lambrecht & Hema Yoganarasimhan, 2024. "A Bias Correction Approach for Interference in Ranking Experiments," Marketing Science, INFORMS, vol. 43(3), pages 590-614, May.
    34. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings: separating definitions and assumptions," Papers 2103.06471, arXiv.org, revised Mar 2023.
    35. Sofrygin Oleg & van der Laan Mark J., 2017. "Semi-Parametric Estimation and Inference for the Mean Outcome of the Single Time-Point Intervention in a Causally Connected Population," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-35, March.
    36. Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
    37. Jinglong Zhao, 2024. "Experimental Design For Causal Inference Through An Optimization Lens," Papers 2408.09607, arXiv.org, revised Aug 2024.

  5. Kaptein, Maurits & Eckles, Dean, 2012. "Heterogeneity in the Effects of Online Persuasion," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 176-188.

    Cited by:

    1. Maurits Kaptein & Robin van Emden & Davide Iannuzzi, 2017. "Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    2. Blazevic, Vera & Wiertz, Caroline & Cotte, June & de Ruyter, Ko & Keeling, Debbie Isobel, 2014. "GOSIP in Cyberspace: Conceptualization and Scale Development for General Online Social Interaction Propensity," Journal of Interactive Marketing, Elsevier, vol. 28(2), pages 87-100.
    3. Meents, Selmar & Verhagen, Tibert & Merikivi, Jani & Weltevreden, Jesse, 2020. "Persuasive location-based messaging to increase store visits: An exploratory study of fashion shoppers," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    4. Dean Eckles & Maurits Kaptein, 2019. "Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences," SAGE Open, , vol. 9(2), pages 21582440198, June.
    5. Estrella Díaz & David Martín-Consuegra & Hooman Estelami, 2016. "A persuasive-based latent class segmentation analysis of luxury brand websites," Electronic Commerce Research, Springer, vol. 16(3), pages 401-424, September.
    6. Díaz, Estrella & Martín-Consuegra, David, 2016. "A latent class segmentation analysis of airlines based on website evaluation," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 20-40.
    7. Pappas, Ilias O. & Kourouthanassis, Panos E. & Giannakos, Michail N. & Chrissikopoulos, Vassilios, 2016. "Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions," Journal of Business Research, Elsevier, vol. 69(2), pages 794-803.
    8. Barnes, Stuart J. & Pressey, Andrew D., 2016. "Cyber-mavens and online flow experiences: Evidence from virtual worlds," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 285-296.

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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 3 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 (3) 2015-07-11 2015-09-05 2016-10-09
  2. NEP-NET: Network Economics (3) 2015-07-11 2015-09-05 2016-10-09
  3. NEP-ECM: Econometrics (1) 2015-07-11

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