IDEAS home Printed from https://ideas.repec.org/f/pta824.html
   My authors  Follow this author

Omer Tamuz

Personal Details

First Name:Omer
Middle Name:
Last Name:Tamuz
Suffix:
RePEc Short-ID:pta824
[This author has chosen not to make the email address public]
http://tamuz.caltech.edu

Affiliation

Division of Social Sciences
California Institute of Technology

Pasadena, California (United States)
http://www.hss.caltech.edu/research/social-sciences-research
RePEc:edi:dscalus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Itai Arieli & Yakov Babichenko & Fedor Sandomirskiy & Omer Tamuz, 2020. "Feasible Joint Posterior Beliefs," Papers 2002.11362, arXiv.org, revised Dec 2020.
  2. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2019. "From Blackwell Dominance in Large Samples to Renyi Divergences and Back Again," Papers 1906.02838, arXiv.org, revised Sep 2020.
  3. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2018. "The Cost of Information: The Case of Constant Marginal Costs," Papers 1812.04211, arXiv.org, revised Feb 2023.
  4. Laurent Bartholdi & Wade Hann-Caruthers & Maya Josyula & Omer Tamuz & Leeat Yariv, 2018. "Equitable voting rules," Papers 1811.01227, arXiv.org, revised Aug 2020.
  5. Pathikrit Basu & Kalyan Chatterjee & Tetsuya Hoshino & Omer Tamuz, 2018. "Repeated Coordination with Private Learning," Papers 1809.00051, arXiv.org.
  6. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2018. "Stochastic Dominance Under Independent Noise," Papers 1807.06927, arXiv.org, revised May 2019.
  7. Wade Hann-Caruthers & Vadim V. Martynov & Omer Tamuz, 2017. "The speed of sequential asymptotic learning," Papers 1707.02689, arXiv.org, revised Nov 2017.
  8. Yakov Babichenko & Omer Tamuz, 2014. "Graphical potential games," Papers 1405.1481, arXiv.org, revised Mar 2016.
  9. Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2014. "Rational Groupthink," Papers 1412.7172, arXiv.org, revised Jun 2020.
  10. Elchanan Mossel & Manuel Mueller-Frank & Allan Sly & Omer Tamuz, 2012. "Social learning equilibria," Papers 1207.5895, arXiv.org, revised Sep 2019.
  11. Elchanan Mossel & Allan Sly & Omer Tamuz, 2012. "Strategic Learning and the Topology of Social Networks," Papers 1209.5527, arXiv.org, revised May 2015.
  12. Elchanan Mossel & Omer Tamuz, 2009. "Complete Characterization of Functions Satisfying the Conditions of Arrow's Theorem," Papers 0910.2465, arXiv.org, revised Apr 2011.

Articles

  1. Elchanan Mossel & Manuel Mueller‐Frank & Allan Sly & Omer Tamuz, 2020. "Social Learning Equilibria," Econometrica, Econometric Society, vol. 88(3), pages 1235-1267, May.
  2. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2020. "Stochastic Dominance under Independent Noise," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1877-1900.
  3. Hann-Caruthers, Wade & Martynov, Vadim V. & Tamuz, Omer, 2018. "The speed of sequential asymptotic learning," Journal of Economic Theory, Elsevier, vol. 173(C), pages 383-409.
  4. Babichenko, Yakov & Tamuz, Omer, 2016. "Graphical potential games," Journal of Economic Theory, Elsevier, vol. 163(C), pages 889-899.
  5. Benjamini, Itai & Chan, Siu-On & O’Donnell, Ryan & Tamuz, Omer & Tan, Li-Yang, 2016. "Convergence, unanimity and disagreement in majority dynamics on unimodular graphs and random graphs," Stochastic Processes and their Applications, Elsevier, vol. 126(9), pages 2719-2733.
  6. Elchanan Mossel & Allan Sly & Omer Tamuz, 2015. "Strategic Learning and the Topology of Social Networks," Econometrica, Econometric Society, vol. 83(5), pages 1755-1794, September.
  7. Finucane, Hilary & Tamuz, Omer & Yaari, Yariv, 2014. "Scenery reconstruction on finite abelian groups," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2754-2770.
  8. Elchanan Mossel & Omer Tamuz, 2012. "Complete characterization of functions satisfying the conditions of Arrow’s theorem," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 39(1), pages 127-140, June.

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. Itai Arieli & Yakov Babichenko & Fedor Sandomirskiy & Omer Tamuz, 2020. "Feasible Joint Posterior Beliefs," Papers 2002.11362, arXiv.org, revised Dec 2020.

    Cited by:

    1. P. Jean-Jacques Herings & Dominik Karos & Toygar T. Kerman, 2024. "Belief inducibility and informativeness," Theory and Decision, Springer, vol. 96(4), pages 517-553, June.
    2. Kevin He & Fedor Sandomirskiy & Omer Tamuz, 2022. "Private Private Information," PIER Working Paper Archive 22-004, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    3. Levy, Gilat & Moreno de Barreda, Inés & Razin, Ronny, 2022. "Persuasion with correlation neglect: a full manipulation result," LSE Research Online Documents on Economics 111551, London School of Economics and Political Science, LSE Library.

  2. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2019. "From Blackwell Dominance in Large Samples to Renyi Divergences and Back Again," Papers 1906.02838, arXiv.org, revised Sep 2020.

    Cited by:

    1. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2019. "From Blackwell Dominance in Large Samples to Renyi Divergences and Back Again," Papers 1906.02838, arXiv.org, revised Sep 2020.
    2. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    3. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "Monotone additive statistics," Papers 2102.00618, arXiv.org, revised Apr 2024.
    4. Andrew Kosenko, 2021. "Algebraic Properties of Blackwell's Order and A Cardinal Measure of Informativeness," Papers 2110.11399, arXiv.org.
    5. Frick, Mira & , & Ishii, Yuhta, 2021. "Welfare Comparisons for Biased Learning," CEPR Discussion Papers 16833, C.E.P.R. Discussion Papers.
    6. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "Monotone Additive Statistics," Working Papers 2021-36, Princeton University. Economics Department..
    7. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R2, Cowles Foundation for Research in Economics, Yale University, revised Jul 2022.

  3. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2018. "The Cost of Information: The Case of Constant Marginal Costs," Papers 1812.04211, arXiv.org, revised Feb 2023.

    Cited by:

    1. Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
    2. Bartosz Maćkowiak & Filip Matějka & Mirko Wiederholt, 2023. "Rational Inattention: A Review," SciencePo Working papers Main hal-03878692, HAL.
    3. Daniil Larionov & Hien Pham & Takuro Yamashita & Shuguang Zhu, 2022. "First Best Implementation With Costly Information Acquisition," CRC TR 224 Discussion Paper Series crctr224_2022_377, University of Bonn and University of Mannheim, Germany.
    4. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    5. Qianjun Lyu, 2024. "Optimal Refund Mechanism with Consumer Learning," Papers 2404.14927, arXiv.org.
    6. Skreta, Vasiliki & Giacomini, Raffaella & Gaglianone, Wagner & Issler, Joao, 2019. "Incentive-driven Inattention," CEPR Discussion Papers 13619, C.E.P.R. Discussion Papers.
    7. Dewan, Ambuj & Neligh, Nathaniel, 2020. "Estimating information cost functions in models of rational inattention," Journal of Economic Theory, Elsevier, vol. 187(C).
    8. Benjamin Hébert & Michael Woodford, 2021. "Neighborhood-Based Information Costs," American Economic Review, American Economic Association, vol. 111(10), pages 3225-3255, October.
    9. David Walker-Jones, 2019. "Rational Inattention and Perceptual Distance," Papers 1909.00888, arXiv.org, revised Dec 2019.
    10. Luca Braghieri, 2023. "Biased Decoding and the Foundations of Communication," CESifo Working Paper Series 10432, CESifo.
    11. Mark Whitmeyer, 2022. "Making Information More Valuable," Papers 2210.04418, arXiv.org, revised Jun 2024.
    12. Tommaso Denti & Massimo Marinacci & Aldo Rustichini, 2022. "Experimental Cost of Information," American Economic Review, American Economic Association, vol. 112(9), pages 3106-3123, September.
    13. Flynn, Joel P. & Sastry, Karthik A., 2023. "Strategic mistakes," Journal of Economic Theory, Elsevier, vol. 212(C).
    14. Roc Armenter & Michèle Müller-Itten & Zachary Strangebye, 2021. "Rational Inattention via Ignorance Equivalence," Working Papers 21-29, Federal Reserve Bank of Philadelphia.
    15. Peter Caradonna & Christopher P. Chambers, 2024. "Revealed Invariant Preference," Papers 2408.04573, arXiv.org.
    16. Benjamin M. Hébert & Michael Woodford, 2019. "Rational Inattention when Decisions Take Time," NBER Working Papers 26415, National Bureau of Economic Research, Inc.
    17. Shaofei Jiang, 2024. "Costly Persuasion by a Partially Informed Sender," Papers 2401.14087, arXiv.org, revised Aug 2024.
    18. Zhou, Jing, 2022. "Capital reallocation from the perspective of endogenous lemons markets and information cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).
    19. D'aniel Csaba, 2021. "Attention elasticities and invariant information costs," Papers 2105.07565, arXiv.org.
    20. Farzad Pourbabaee, 2021. "High Dimensional Decision Making, Upper and Lower Bounds," Papers 2105.00545, arXiv.org.
    21. Benjamin Davies, 2024. "Learning about a changing state," Papers 2401.03607, arXiv.org.
    22. Walker-Jones, David, 2023. "Rational inattention with multiple attributes," Journal of Economic Theory, Elsevier, vol. 212(C).
    23. Pourbabaee, Farzad, 2021. "High dimensional decision making, upper and lower bounds," Economics Letters, Elsevier, vol. 204(C).
    24. Mark Whitmeyer & Kun Zhang, 2022. "Buying Opinions," Papers 2202.05249, arXiv.org, revised Jul 2023.

  4. Pathikrit Basu & Kalyan Chatterjee & Tetsuya Hoshino & Omer Tamuz, 2018. "Repeated Coordination with Private Learning," Papers 1809.00051, arXiv.org.

    Cited by:

    1. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.

  5. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2018. "Stochastic Dominance Under Independent Noise," Papers 1807.06927, arXiv.org, revised May 2019.

    Cited by:

    1. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2019. "From Blackwell Dominance in Large Samples to Renyi Divergences and Back Again," Papers 1906.02838, arXiv.org, revised Sep 2020.
    2. Christopher P. Chambers & Federico Echenique, 2019. "Spherical Preferences," Papers 1905.02917, arXiv.org, revised Feb 2020.
    3. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "Monotone additive statistics," Papers 2102.00618, arXiv.org, revised Apr 2024.
    4. Marilyn Pease & Mark Whitmeyer, 2024. "How to Make an Action Better," Papers 2408.09294, arXiv.org, revised Sep 2024.
    5. Anderson, Robert M. & Duanmu, Haosui & Ghosh, Aniruddha & Khan, M. Ali, 2024. "On existence of Berk-Nash equilibria in misspecified Markov decision processes with infinite spaces," Journal of Economic Theory, Elsevier, vol. 217(C).
    6. Fabio Maccheroni & Massimo Marinacci & Ruodu Wang & Qinyu Wu, 2023. "Risk Aversion and Insurance Propensity," Papers 2310.09173, arXiv.org, revised Jul 2024.

  6. Wade Hann-Caruthers & Vadim V. Martynov & Omer Tamuz, 2017. "The speed of sequential asymptotic learning," Papers 1707.02689, arXiv.org, revised Nov 2017.

    Cited by:

    1. Itai Arieli & Moran Koren & Rann Smorodinsky, 2019. "The Implications of Pricing on Social Learning," Papers 1905.03452, arXiv.org.
    2. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    3. Yuval Peres & Miklos Z. Racz & Allan Sly & Izabella Stuhl, 2017. "How fragile are information cascades?," Papers 1711.04024, arXiv.org, revised Feb 2018.
    4. Bikhchandani, Sushil & Hirshleifer, David & Tamuz, Omer & Welch, Ivo, 2021. "Information Cascades and Social Learning," MPRA Paper 107927, University Library of Munich, Germany.
    5. Wanying Huang & Philipp Strack & Omer Tamuz, 2021. "Learning in Repeated Interactions on Networks," Papers 2112.14265, arXiv.org, revised Jul 2024.
    6. Annie Liang & Xiaosheng Mu, 2018. "Overabundant Information and Learning Traps," PIER Working Paper Archive 18-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 27 Mar 2018.
    7. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2017. "Fast and Slow Learning From Reviews," NBER Working Papers 24046, National Bureau of Economic Research, Inc.
    8. Ilai Bistritz & Nasimeh Heydaribeni & Achilleas Anastasopoulos, 2019. "Do Informational Cascades Happen with Non-myopic Agents?," Papers 1905.01327, arXiv.org, revised Jul 2022.
    9. Frick, Mira & , & Ishii, Yuhta, 2021. "Belief Convergence under Misspecified Learning: A Martingale Approach," CEPR Discussion Papers 16788, C.E.P.R. Discussion Papers.
    10. Xuanye Wang, 2021. "Fragility of Confounded Learning," Papers 2106.07712, arXiv.org.
    11. Arieli, Itai & Babichenko, Yakov & Smorodinsky, Rann, 2020. "Identifiable information structures," Games and Economic Behavior, Elsevier, vol. 120(C), pages 16-27.

  7. Yakov Babichenko & Omer Tamuz, 2014. "Graphical potential games," Papers 1405.1481, arXiv.org, revised Mar 2016.

    Cited by:

    1. Xinrong Yang & Zhenping Geng & Haitao Li, 2023. "Matrix-Based Method for the Analysis and Control of Networked Evolutionary Games: A Survey," Games, MDPI, vol. 14(2), pages 1-13, February.
    2. Simone Cerreia-Vioglio & Roberto Corrao & Giacomo Lanzani, 2020. "Robust Opinion Aggregation and its Dynamics," Working Papers 662, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Nikolaos Nagkoulis & Konstantinos L. Katsifarakis, 2022. "Using Game Theory to Assign Groundwater Pumping Schedules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(5), pages 1571-1586, March.
    4. Toru Kitagawa & Guanyi Wang, 2023. "Individualized Treatment Allocation in Sequential Network Games," Papers 2302.05747, arXiv.org, revised Jul 2024.

  8. Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2014. "Rational Groupthink," Papers 1412.7172, arXiv.org, revised Jun 2020.

    Cited by:

    1. Mira Frick & Ryota Iijima & Yuhta Ishii, 2021. "Learning Efficiency of Multi-Agent Information Structures," Cowles Foundation Discussion Papers 2299R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    2. Wanying Huang & Philipp Strack & Omer Tamuz, 2021. "Learning in Repeated Interactions on Networks," Papers 2112.14265, arXiv.org, revised Jul 2024.
    3. Parker, Owen N. & Mui, Rachel & Bhawe, Nachiket & Semadeni, Matthew, 2022. "Insight or ignorance: How collaborative history in a workgroup fits with project type to shape performance," Journal of Business Research, Elsevier, vol. 152(C), pages 154-167.
    4. Keppo, Jussi & Satopää, Ville A., 2024. "Bayesian herd detection for dynamic data," International Journal of Forecasting, Elsevier, vol. 40(1), pages 285-301.

  9. Elchanan Mossel & Manuel Mueller-Frank & Allan Sly & Omer Tamuz, 2012. "Social learning equilibria," Papers 1207.5895, arXiv.org, revised Sep 2019.

    Cited by:

    1. Michel Grabisch & Agnieszka Rusinowska, 2021. "A Survey on Nonstrategic Models of Opinion Dynamics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03167886, HAL.
    2. Arieli, Itai & Babichenko, Yakov & Shlomov, Segev, 2021. "Virtually additive learning," Journal of Economic Theory, Elsevier, vol. 197(C).
    3. Bikhchandani, Sushil & Hirshleifer, David & Tamuz, Omer & Welch, Ivo, 2021. "Information Cascades and Social Learning," MPRA Paper 107927, University Library of Munich, Germany.
    4. Enrique Urbano Arellano & Xinyang Wang, 2023. "Social Learning of General Rules," Papers 2310.15861, arXiv.org.
    5. Kevin He & Fedor Sandomirskiy & Omer Tamuz, 2022. "Private Private Information," PIER Working Paper Archive 22-004, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. Jérôme Mathis & Marcello Puca & Simone M. Sepe, 2021. "Deliberative Institutions and Optimality," CSEF Working Papers 614, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 09 Jun 2021.
    7. Emilien Macault, 2022. "Stochastic Consensus and the Shadow of Doubt," Papers 2201.12100, arXiv.org.
    8. Jan Hązła & Ali Jadbabaie & Elchanan Mossel & M. Amin Rahimian, 2021. "Bayesian Decision Making in Groups is Hard," Operations Research, INFORMS, vol. 69(2), pages 632-654, March.

  10. Elchanan Mossel & Allan Sly & Omer Tamuz, 2012. "Strategic Learning and the Topology of Social Networks," Papers 1209.5527, arXiv.org, revised May 2015.

    Cited by:

    1. Yi Li, 2020. "Internet Development and Structural Transformation: Evidence from China," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(1), pages 1-8.
    2. Ruoxi Ma & Shangguang Yang, 2023. "The Effect of Social Network on Controlled-Release Fertilizer Use: Evidence from Rice Large-Scale Farmers in Jiangsu Province, China," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    3. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    4. Itai Arieli & Fedor Sandomirskiy & Rann Smorodinsky, 2020. "On social networks that support learning," Papers 2011.05255, arXiv.org.
    5. Arieli, Itai & Babichenko, Yakov & Shlomov, Segev, 2021. "Virtually additive learning," Journal of Economic Theory, Elsevier, vol. 197(C).
    6. Itai Arieli & Yakov Babichenko & Ron Peretz & H. Peyton Young, 2018. "The Speed of Innovation Diffusion," Economics Papers 2018-W06, Economics Group, Nuffield College, University of Oxford.
    7. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Papers 1708.06233, arXiv.org.
    8. Aroon Narayanan, 2022. "Social learning via actions in bandit environments," Papers 2205.06107, arXiv.org.
    9. Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
    10. Abhijit Banerjee & Olivier Compte, 2022. "Consensus and Disagreement: Information Aggregation under (not so) Naive Learning," NBER Working Papers 29897, National Bureau of Economic Research, Inc.
    11. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Working Papers on Finance 1804, University of St. Gallen, School of Finance.
    12. Elchanan Mossel & Manuel Mueller‐Frank & Allan Sly & Omer Tamuz, 2020. "Social Learning Equilibria," Econometrica, Econometric Society, vol. 88(3), pages 1235-1267, May.
    13. Sanjeev Goyal, 2015. "Networks in Economics: A Perspective on the Literature," Cambridge Working Papers in Economics 1548, Faculty of Economics, University of Cambridge.
    14. Mira Frick & Ryota Iijima & Yuhta Ishii, 2019. "Misinterpreting Others and the Fragility of Social Learning," Cowles Foundation Discussion Papers 2160R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2020.
    15. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asuman Ozdaglar, 2017. "Fast and Slow Learning From Reviews," NBER Working Papers 24046, National Bureau of Economic Research, Inc.
    16. Rapanos, Theodoros, 2023. "What makes an opinion leader: Expertise vs popularity," Games and Economic Behavior, Elsevier, vol. 138(C), pages 355-372.
    17. Mueller-Frank, Manuel & Arieliy, Itai, 2015. "A General Model of Boundedly Rational Observational Learning: Theory and Experiment," IESE Research Papers D/1120, IESE Business School.
    18. Li, Wei & Tan, Xu, 2021. "Cognitively-constrained learning from neighbors," Games and Economic Behavior, Elsevier, vol. 129(C), pages 32-54.
    19. Krishna Dasaratha & Benjamin Golub & Nir Hak, 2018. "Learning from Neighbors about a Changing State," Papers 1801.02042, arXiv.org, revised Nov 2022.
    20. Yurij L. Katchanov & Yulia V. Markova, 2017. "The “space of physics journals”: topological structure and the Journal Impact Factor," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 313-333, October.
    21. Ciliberto, Federico & Cook, Emily & Williams, Jonathan, 2017. "Network Structure and Consolidation in the U.S. Airline Industry, 1990-2015," MPRA Paper 83885, University Library of Munich, Germany.
    22. Huihui Ding & Marcus Pivato, 2021. "Deliberation and epistemic democracy," Post-Print hal-03637874, HAL.
    23. Sebastiano Della Lena, 2019. "Non-Bayesian Social Learning and the Spread of Misinformation in Networks," Working Papers 2019:09, Department of Economics, University of Venice "Ca' Foscari".
    24. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg & Matthias Weber, 2022. "Fake News in Social Networks," Swiss Finance Institute Research Paper Series 22-58, Swiss Finance Institute.
    25. Arieli, Itai & Babichenko, Yakov & Peretz, Ron & Young, H. Peyton, 2020. "The speed of innovation diffusion in social networks," LSE Research Online Documents on Economics 102538, London School of Economics and Political Science, LSE Library.
    26. Xuanye Wang, 2021. "Fragility of Confounded Learning," Papers 2106.07712, arXiv.org.
    27. Ningyuan Chen & Anran Li & Kalyan Talluri, 2021. "Reviews and Self-Selection Bias with Operational Implications," Management Science, INFORMS, vol. 67(12), pages 7472-7492, December.
    28. Bahar, Gal & Arieli, Itai & Smorodinsky, Rann & Tennenholtz, Moshe, 2020. "Multi-issue social learning," Mathematical Social Sciences, Elsevier, vol. 104(C), pages 29-39.
    29. Arieli, Itai & Koren, Moran & Smorodinsky, Rann, 2022. "The implications of pricing on social learning," Theoretical Economics, Econometric Society, vol. 17(4), November.
    30. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2016. "Networks: An Economic Perspective," Papers 1608.07901, arXiv.org.
    31. Schwarz, Marco A., 2017. "The Impact of Social Media On Belief Formation," Rationality and Competition Discussion Paper Series 57, CRC TRR 190 Rationality and Competition.
    32. Jan Hązła & Ali Jadbabaie & Elchanan Mossel & M. Amin Rahimian, 2021. "Bayesian Decision Making in Groups is Hard," Operations Research, INFORMS, vol. 69(2), pages 632-654, March.
    33. Camilo García-Jimeno & Angel Iglesias & Pinar Yildirim, 2018. "Women, Rails and Telegraphs: An Empirical Study of Information Diffusion and Collective Action," NBER Working Papers 24495, National Bureau of Economic Research, Inc.
    34. Pena, Paul John & Lim, Dickson, 2019. "Learning With Friends: A Theoretical Note On The Role of Network Externalities In Human Capital Models For The New Industry," MPRA Paper 100172, University Library of Munich, Germany.
    35. Teddy Lazebnik & Svetlana Bunimovich-Mendrazitsky & Shai Ashkenazi & Eugene Levner & Arriel Benis, 2022. "Early Detection and Control of the Next Epidemic Wave Using Health Communications: Development of an Artificial Intelligence-Based Tool and Its Validation on COVID-19 Data from the US," IJERPH, MDPI, vol. 19(23), pages 1-17, November.

  11. Elchanan Mossel & Omer Tamuz, 2009. "Complete Characterization of Functions Satisfying the Conditions of Arrow's Theorem," Papers 0910.2465, arXiv.org, revised Apr 2011.

    Cited by:

    1. Juan Candeal, 2013. "Invariance axioms for preferences: applications to social choice theory," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 41(3), pages 453-471, September.
    2. Maurice Salles, 2014. "‘Social choice and welfare’ at 30: its role in the development of social choice theory and welfare economics," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 42(1), pages 1-16, January.
    3. Nicolas Gabriel Andjiga & Issofa Moyouwou & Monge Kleber Kamdem Ouambo, 2017. "Avoiding Majority Dissatisfaction on a Series of Majority Decisions," Group Decision and Negotiation, Springer, vol. 26(3), pages 453-471, May.
    4. Salvador Barberà & Dolors Berga & Bernardo Moreno & Antonio Nicolò, 2021. "Pairwise Justifiable Changes in Collective Choices," Working Papers 1256, Barcelona School of Economics.

Articles

  1. Elchanan Mossel & Manuel Mueller‐Frank & Allan Sly & Omer Tamuz, 2020. "Social Learning Equilibria," Econometrica, Econometric Society, vol. 88(3), pages 1235-1267, May.
    See citations under working paper version above.
  2. Luciano Pomatto & Philipp Strack & Omer Tamuz, 2020. "Stochastic Dominance under Independent Noise," Journal of Political Economy, University of Chicago Press, vol. 128(5), pages 1877-1900.
    See citations under working paper version above.
  3. Hann-Caruthers, Wade & Martynov, Vadim V. & Tamuz, Omer, 2018. "The speed of sequential asymptotic learning," Journal of Economic Theory, Elsevier, vol. 173(C), pages 383-409.
    See citations under working paper version above.
  4. Babichenko, Yakov & Tamuz, Omer, 2016. "Graphical potential games," Journal of Economic Theory, Elsevier, vol. 163(C), pages 889-899.
    See citations under working paper version above.
  5. Benjamini, Itai & Chan, Siu-On & O’Donnell, Ryan & Tamuz, Omer & Tan, Li-Yang, 2016. "Convergence, unanimity and disagreement in majority dynamics on unimodular graphs and random graphs," Stochastic Processes and their Applications, Elsevier, vol. 126(9), pages 2719-2733.

    Cited by:

    1. Berkowitz, Ross & Devlin, Pat, 2022. "Central limit theorem for majority dynamics: Bribing three voters suffices," Stochastic Processes and their Applications, Elsevier, vol. 146(C), pages 187-206.
    2. Chellig, Jordan & Durbac, Calina & Fountoulakis, Nikolaos, 2022. "Best response dynamics on random graphs," Games and Economic Behavior, Elsevier, vol. 131(C), pages 141-170.
    3. Syngjoo Choi & Sanjeev Goyal & Frederic Moisan & Yu Yang Tony To, 2023. "Learning in Networks: An Experiment on Large Networks with Real-World Features," Management Science, INFORMS, vol. 69(5), pages 2778-2787, May.
    4. Amir, Gideon & Baldasso, Rangel & Beilin, Nissan, 2023. "Majority dynamics and the median process: Connections, convergence and some new conjectures," Stochastic Processes and their Applications, Elsevier, vol. 155(C), pages 437-458.

  6. Elchanan Mossel & Allan Sly & Omer Tamuz, 2015. "Strategic Learning and the Topology of Social Networks," Econometrica, Econometric Society, vol. 83(5), pages 1755-1794, September.
    See citations under working paper version above.
  7. Finucane, Hilary & Tamuz, Omer & Yaari, Yariv, 2014. "Scenery reconstruction on finite abelian groups," Stochastic Processes and their Applications, Elsevier, vol. 124(8), pages 2754-2770.

    Cited by:

    1. Hildebrand, Martin, 2017. "A condition for distinguishing sceneries on non-abelian groups," Stochastic Processes and their Applications, Elsevier, vol. 127(7), pages 2339-2345.
    2. Gross, Renan, 2024. "Brownian motion can feel the shape of a drum," Stochastic Processes and their Applications, Elsevier, vol. 167(C).

  8. Elchanan Mossel & Omer Tamuz, 2012. "Complete characterization of functions satisfying the conditions of Arrow’s theorem," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 39(1), pages 127-140, June.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Journal Pages, Weighted by Recursive Impact Factor

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 7 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-MIC: Microeconomics (5) 2018-10-01 2018-12-24 2019-01-07 2019-09-02 2020-03-16. Author is listed
  2. NEP-CDM: Collective Decision-Making (3) 2018-10-01 2018-11-19 2018-12-24
  3. NEP-DES: Economic Design (2) 2018-11-19 2018-12-24
  4. NEP-EXP: Experimental Economics (2) 2018-10-01 2019-09-02
  5. NEP-GTH: Game Theory (2) 2018-10-01 2020-03-16
  6. NEP-POL: Positive Political Economics (2) 2018-11-19 2018-12-24
  7. NEP-UPT: Utility Models and Prospect Theory (1) 2018-08-27

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Omer Tamuz should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.