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Pooya Molavi

Personal Details

First Name:Pooya
Middle Name:
Last Name:Molavi
Suffix:
RePEc Short-ID:pmo980
[This author has chosen not to make the email address public]

Affiliation

Economics Department
Massachusetts Institute of Technology (MIT)

Cambridge, Massachusetts (United States)
http://econ-www.mit.edu/

: (617) 253-3361
(617) 253-1330
50 Memorial Drive, E52-391, Cambridge, MA 02142
RePEc:edi:edmitus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ali Jadbabaie & Pooya Molavi & Alvaro Sandroni & Alireza Tahbaz-Salehi, 2009. "Non-Bayesian Social Learning, Third Version," PIER Working Paper Archive 11-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 05 Aug 2011.

Articles

  1. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.

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. Ali Jadbabaie & Pooya Molavi & Alvaro Sandroni & Alireza Tahbaz-Salehi, 2009. "Non-Bayesian Social Learning, Third Version," PIER Working Paper Archive 11-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 05 Aug 2011.

    Cited by:

    1. Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
    2. Bar Ifrach & Costis Maglaras & Marco Scarsini, 2012. "Monopoly Pricing in the Presence of Social Learning," Working Papers 12-01, NET Institute, revised Sep 2012.
    3. Fang, Aili & Wang, Lin & Zhao, Jiuhua & Wang, Xiaofan, 2013. "Chaos in social learning with multiple true states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5786-5792.

Articles

  1. Jadbabaie, Ali & Molavi, Pooya & Sandroni, Alvaro & Tahbaz-Salehi, Alireza, 2012. "Non-Bayesian social learning," Games and Economic Behavior, Elsevier, vol. 76(1), pages 210-225.

    Cited by:

    1. Kwon, Seokbeom & Motohashi, Kazuyuki, 2017. "How institutional arrangements in the National Innovation System affect industrial competitiveness: A study of Japan and the U.S. with multiagent simulation," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 221-235.
    2. Eger, Steffen, 2016. "Opinion dynamics and wisdom under out-group discrimination," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 97-107.
    3. Berno Buechel & Tim Hellmann & Stefan Kölßner, 2014. "Opinion Dynamics and Wisdom under Conformity," Working Papers 2014.51, Fondazione Eni Enrico Mattei.
    4. Pietro Dindo & Filippo Massari, 2017. "The Wisdom of the Crowd in Dynamic Economies," Working Papers 2017:17, Department of Economics, University of Venice "Ca' Foscari".
    5. Mueller-Frank, Manuel, 2015. "Reaching Consensus in Social Networks," IESE Research Papers D/1116, IESE Business School.
    6. Battiston, Pietro & Stanca, Luca, 2015. "Boundedly rational opinion dynamics in social networks: Does indegree matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 400-421.
    7. KWON Seokbeom & MOTOHASHI Kazuyuki, 2015. "How Institutional Arrangements in the National Innovation System Affect Industrial Competitiveness: A study of Japan and the United States with multiagent simulation," Discussion papers 15065, Research Institute of Economy, Trade and Industry (RIETI).
    8. Krishna Dasaratha & Kevin He, 2017. "Network Structure and Naive Sequential Learning," Papers 1703.02105, arXiv.org, revised Jun 2018.
    9. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Papers 1708.06233, arXiv.org.
    10. Ilan Lobel & Evan Sadler, 2013. "Preferences, Homophily, and Social Learning," Working Papers 13-01, NET Institute.
    11. Matthew Ellman, 2017. "Online Social Networks: Approval by Design," Working Papers 17-18, NET Institute.
    12. 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.
    13. Rajiv Sethi & Muhamet Yildiz, 2013. "Perspectives, Opinions, and Information Flows," Levine's Working Paper Archive 786969000000000934, David K. Levine.
    14. Lobel, Ilan & Sadler, Evan, 2015. "Information diffusion in networks through social learning," Theoretical Economics, Econometric Society, vol. 10(3), September.
    15. Daron Acemoglu & Asuman E. Ozdaglar & Alireza Tahbaz Salehi, 2015. "Networks, Shocks, and Systemic Risk," Levine's Bibliography 786969000000001187, UCLA Department of Economics.
    16. Fu, Guiyuan & Zhang, Weidong & Li, Zhijun, 2015. "Opinion dynamics of modified Hegselmann–Krause model in a group-based population with heterogeneous bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 558-565.
    17. Pietro Battiston & Luca Stanca, 2014. "Boundedly Rational Opinion Dynamics in Directed Social Networks: Theory and Experimental Evidence," Working Papers 267, University of Milano-Bicocca, Department of Economics, revised Jan 2014.
    18. Golub Benjamin & Jackson Matthew O., 2012. "Does Homophily Predict Consensus Times? Testing a Model of Network Structure via a Dynamic Process," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-31, September.
    19. Francesco Drago & Friederike Mengel & Christian Traxler, 2015. "Compliance Behavior in Networks: Evidence from a Field Experiment," CSEF Working Papers 419, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    20. Wang, Huanjing & Shang, Lihui, 2015. "Opinion dynamics in networks with common-neighbors-based connections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 180-186.
    21. Krishna Dasaratha & Benjamin Golub & Nir Hak, 2018. "Bayesian Social Learning in a Dynamic Environment," Papers 1801.02042, arXiv.org.
    22. Liu, Qipeng & Wang, Xiaofan, 2013. "Social learning with bounded confidence and heterogeneous agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2368-2374.
    23. Tomasz Makarewicz, 2017. "Contrarian Behavior, Information Networks and Heterogeneous Expectations in an Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 231-279, August.
    24. Bohren, Aislinn & Hauser, Daniel, 2017. "Bounded Rationality And Learning: A Framework and A Robustness Result," CEPR Discussion Papers 12036, C.E.P.R. Discussion Papers.

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