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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

(50%) Becker Friedman Institute for Research in Economics
University of Chicago

Chicago, Illinois (United States)
http://bfi.uchicago.edu/
RePEc:edi:mfichus (more details at EDIRC)

(50%) Managerial Economics and Decision Sciences (MEDS)
Kellogg Graduate School of Management
Northwestern University

Evanston, Illinois (United States)
http://www.kellogg.northwestern.edu/meds/index.htm
RePEc:edi:menwuus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Pooya Molavi, 2019. "Macroeconomics with Learning and Misspecification: A General Theory and Applications," 2019 Meeting Papers 1584, Society for Economic Dynamics.

Articles

  1. Pooya Molavi & Alireza Tahbaz‐Salehi & Ali Jadbabaie, 2018. "A Theory of Non‐Bayesian Social Learning," Econometrica, Econometric Society, vol. 86(2), pages 445-490, March.
  2. Pooya Molavi & Ceyhun Eksin & Alejandro Ribeiro & Ali Jadbabaie, 2016. "Learning to Coordinate in Social Networks," Operations Research, INFORMS, vol. 64(3), pages 605-621, June.
  3. 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. Pooya Molavi, 2019. "Macroeconomics with Learning and Misspecification: A General Theory and Applications," 2019 Meeting Papers 1584, Society for Economic Dynamics.

    Cited by:

    1. George-Marios Angeletos & Chen Lian, 2020. "Confidence and the Propagation of Demand Shocks," NBER Working Papers 27702, National Bureau of Economic Research, Inc.
    2. Collard, Fabrice & Dellas, Harris & Angeletos, George-Marios, 2020. "Business Cycle Anatomy," TSE Working Papers 20-1065, Toulouse School of Economics (TSE).
    3. Karantounias, Anastasios G., 2023. "Doubts about the model and optimal policy," Journal of Economic Theory, Elsevier, vol. 210(C).
    4. Kfir Eliaz & Ran Spiegler & Yair Weiss, 2019. "Cheating with (Recursive) Models," Papers 1911.01251, arXiv.org.
    5. Esponda, Ignacio & Pouzo, Demian & Yamamoto, Yuichi, 2021. "Asymptotic behavior of Bayesian learners with misspecified models," Journal of Economic Theory, Elsevier, vol. 195(C).
    6. Kevin He & Jonathan Libgober, 2021. "Evolutionarily Stable (Mis)specifications:Theory and Applications," PIER Working Paper Archive 21-020, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    7. Iliopulos, Eleni & Perego, Erica & Sopraseuth, Thepthida, 2021. "International business cycles: Information matters," Journal of Monetary Economics, Elsevier, vol. 123(C), pages 19-34.
    8. Felix Kubler & Simon Scheidegger, 2021. "Uniformly Self-Justified Equilibria," Papers 2112.14054, arXiv.org.
    9. Peter Andre & Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2021. "Narratives about the Macroeconomy," CEBI working paper series 21-18, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    10. Javier Turen & Isaac Baley, 2025. "Lumpy Forecasts," Working Papers 1476, Barcelona School of Economics.
    11. Steiner, Jakub & Netzer, Nick & Robson, Arthur & Kocourek, Pavel, 2021. "Endogenous Risk Attitudes," CEPR Discussion Papers 16190, C.E.P.R. Discussion Papers.
    12. Anmol Bhandari & Jaroslav Borovička & Paul Ho, 2025. "Survey Data and Subjective Beliefs in Business Cycle Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 92(3), pages 1375-1437.
    13. Aniruddha Ghosh, 2024. "Robust Comparative Statics with Misspecified Bayesian Learning," Papers 2407.17037, arXiv.org, revised Mar 2025.
    14. George-Marios Angeletos & Zhen Huo & Karthik A. Sastry, 2020. "Imperfect Macroeconomic Expectations: Evidence and Theory," NBER Working Papers 27308, National Bureau of Economic Research, Inc.
    15. Alistair Macaulay, 2022. "Heterogeneous Information, Subjective Model Beliefs, and the Time-Varying Transmission of Shocks," CESifo Working Paper Series 9733, CESifo.
    16. Frick, Mira & , & Ishii, Yuhta, 2021. "Belief Convergence under Misspecified Learning: A Martingale Approach," CEPR Discussion Papers 16788, C.E.P.R. Discussion Papers.
    17. Barrero, Jose Maria, 2022. "The micro and macro of managerial beliefs," Journal of Financial Economics, Elsevier, vol. 143(2), pages 640-667.
    18. Peter Andre & Carlo Pizzinelli & Christopher Roth & Johannes Wohlfart, 2021. "Subjective Models of the Macroeconomy: Evidence From Experts and Representative Samples," ECONtribute Discussion Papers Series 119, University of Bonn and University of Cologne, Germany.
    19. J. Aislinn Bohren & Daniel N. Hauser, 2023. "Behavioral Foundations of Model Misspecification," PIER Working Paper Archive 23-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    20. Drew Fudenberg & Giacomo Lanzani & Philipp Strack, 2021. "Limit Points of Endogenous Misspecified Learning," Econometrica, Econometric Society, vol. 89(3), pages 1065-1098, May.
    21. Takeshi Murooka & Yuichi Yamamoto, 2021. "Misspecified Bayesian Learning by Strategic Players: First-Order Misspecification and Higher-Order Misspecification," OSIPP Discussion Paper 21E008, Osaka School of International Public Policy, Osaka University.
    22. Macaulay, Alistair & Song, Wenting, 2022. "Narrative-Driven Fluctuations in Sentiment: Evidence Linking Traditional and Social Media," MPRA Paper 113620, University Library of Munich, Germany.
    23. Gáti, Laura, 2022. "Monetary policy & anchored expectations: an endogenous gain learning model," Working Paper Series 2685, European Central Bank.
    24. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Belief Convergence under Misspecified Learning: A Martingale Approach," Cowles Foundation Discussion Papers 2235R3, Cowles Foundation for Research in Economics, Yale University, revised Apr 2022.
    25. Mira Frick & Ryota Iijima & Yuhta Ishii, 2020. "Stability and Robustness in Misspecified Learning Models," Cowles Foundation Discussion Papers 2235, Cowles Foundation for Research in Economics, Yale University.
    26. Yuliya Rychalovska & Sergey Slobodyan & Rafael Wouters, 2023. "Professional Survey Forecasts and Expectations in DSGE Models," CERGE-EI Working Papers wp766, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    27. Yingkai Li & Harry Pei, 2020. "Misspecified Beliefs about Time Lags," Papers 2012.07238, arXiv.org.
    28. Takeshi Murooka & Yuichi Yamamoto, 2021. "Multi-Player Bayesian Learning with Misspecified Models," OSIPP Discussion Paper 21E001, Osaka School of International Public Policy, Osaka University.
    29. Fudenberg, Drew & Lanzani, Giacomo, 2023. "Which misspecifications persist?," Theoretical Economics, Econometric Society, vol. 18(3), July.
    30. Ludwig, Alexander & Mankart, Jochen & Quintana, Jorge & Wiederholt, Mirko, 2024. "Heterogeneity in expectations and house price dynamics," SAFE Working Paper Series 432, Leibniz Institute for Financial Research SAFE.
    31. Fudenberg, Drew & Lanzani, Giacomo & Strack, Philipp, 2023. "Pathwise concentration bounds for Bayesian beliefs," Theoretical Economics, Econometric Society, vol. 18(4), November.

Articles

  1. Pooya Molavi & Alireza Tahbaz‐Salehi & Ali Jadbabaie, 2018. "A Theory of Non‐Bayesian Social Learning," Econometrica, Econometric Society, vol. 86(2), pages 445-490, March.

    Cited by:

    1. Fernandes, Marcos R., 2023. "Confirmation bias in social networks," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 59-76.
    2. Luca Paolo Merlino & Paolo Pin & Nicole Tabasso, 2023. "Debunking Rumors in Networks," ULB Institutional Repository 2013/365073, ULB -- Universite Libre de Bruxelles.
    3. Ghosh, Aniruddha & Khan, M. Ali, 2021. "On a diversity of perspectives and world views: Learning under Bayesian vis-á-vis DeGroot updating," Economics Letters, Elsevier, vol. 202(C).
    4. Miguel Risco, 2025. "Network effects on information acquisition by DeGroot updaters," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 79(1), pages 201-234, February.
    5. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    6. Florian Mudekereza, 2025. "Collective Intelligence in Dynamic Networks," Papers 2502.12660, arXiv.org, revised Jun 2025.
    7. Arieli, Itai & Babichenko, Yakov & Shlomov, Segev, 2021. "Virtually additive learning," Journal of Economic Theory, Elsevier, vol. 197(C).
    8. Polanski, Arnold & Vega-Redondo, Fernando, 2023. "Homophily and influence," Journal of Economic Theory, Elsevier, vol. 207(C).
    9. Crès, Hervé & Tvede, Mich, 2022. "Aggregation of opinions in networks of individuals and collectives," Journal of Economic Theory, Elsevier, vol. 199(C).
    10. Amir, Gideon & Arieli, Itai & Ashkenazi-Golan, Galit & Peretz, Ron, 2025. "Granular DeGroot dynamics – A model for robust naive learning in social networks," Journal of Economic Theory, Elsevier, vol. 223(C).
    11. Buechel Berno & Klößner, Stefan & Meng, Fanyuan & Nassar, Anis, 2022. "Misinformation due to asymmetric information sharing," FSES Working Papers 528, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    12. Wanying Huang & Philipp Strack & Omer Tamuz, 2021. "Learning in Repeated Interactions on Networks," Papers 2112.14265, arXiv.org, revised Jul 2024.
    13. 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.
    14. Cao, GangCheng & Fang, Debin & Wang, Pengyu, 2021. "The impacts of social learning on a real-time pricing scheme in the electricity market," Applied Energy, Elsevier, vol. 291(C).
    15. Mueller-Frank, Manuel, 2024. "As strong as the weakest node: The impact of misinformation in social networks," Journal of Economic Theory, Elsevier, vol. 215(C).
    16. Rapanos, Theodoros, 2023. "What makes an opinion leader: Expertise vs popularity," Games and Economic Behavior, Elsevier, vol. 138(C), pages 355-372.
    17. Li, Wei & Tan, Xu, 2021. "Cognitively-constrained learning from neighbors," Games and Economic Behavior, Elsevier, vol. 129(C), pages 32-54.
    18. Benedikt V. Meylahn & Arnoud V. den Boer & Michel Mandjes, 2023. "Trusting: Alone and together," Papers 2303.01921, arXiv.org, revised Feb 2024.
    19. Steven Kivinen & Norovsambuu Tumennasan, 2016. "Consensus in Social Networks: Revisited," Working Papers daleconwp2016-05, Dalhousie University, Department of Economics.
    20. Tsionas, Mike G., 2023. "Bayesian learning in performance. Is there any?," European Journal of Operational Research, Elsevier, vol. 311(1), pages 263-282.
    21. 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".
    22. Sebastiano Della Lena & Luca Paolo Merlino, 2021. "Group Identity, Social Learning and Opinion Dynamics," Papers 2110.07226, arXiv.org, revised May 2022.
    23. Glass, Catherine A. & Glass, David H., 2021. "Opinion dynamics of social learning with a conflicting source," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    24. Goutte, Maud-Rose, 2022. "Do actions speak louder than words? Evidence from microblogs," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    25. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    26. Pedersen, Lasse Heje, 2022. "Game on: Social networks and markets," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1097-1119.
    27. Ke, Shaowei & Wu, Brian & Zhao, Chen, 2024. "Learning from a black box," Journal of Economic Theory, Elsevier, vol. 221(C).
    28. Della Lena, Sebastiano, 2024. "The spread of misinformation in networks with individual and social learning," European Economic Review, Elsevier, vol. 168(C).
    29. Wang, Pengyu & Fang, Debin & Cao, GangCheng, 2022. "How social learning affects customer behavior under the implementation of TOU in the electricity retailing market," Energy Economics, Elsevier, vol. 106(C).
    30. Lou, Youcheng & Wang, Shouyang, 2021. "The equivalence of two rational expectations equilibrium economies with different approaches to processing neighbors’ information," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 93-105.
    31. Miguel Risco, 2023. "Network Effects on Information Acquisition by DeGroot Updaters," CRC TR 224 Discussion Paper Series crctr224_2023_420v2, University of Bonn and University of Mannheim, Germany.

  2. Pooya Molavi & Ceyhun Eksin & Alejandro Ribeiro & Ali Jadbabaie, 2016. "Learning to Coordinate in Social Networks," Operations Research, INFORMS, vol. 64(3), pages 605-621, June.

    Cited by:

    1. Furkan Sezer & Ceyhun Eksin, 2022. "Information Preferences of Individual Agents in Linear-Quadratic-Gaussian Network Games," Papers 2203.13056, arXiv.org.
    2. Hüning, Hendrik & Meub, Lukas, 2015. "Optimal public information dissemination: Introducing observational learning into a generalized beauty contest," University of Göttingen Working Papers in Economics 260, University of Goettingen, Department of Economics.
    3. Edward Anderson & David Gamarnik & Anton Kleywegt & Asuman Ozdaglar, 2016. "Preface to the Special Issue on Information and Decisions in Social and Economic Networks," Operations Research, INFORMS, vol. 64(3), pages 561-563, June.
    4. Hüning, Hendrik & Meub, Lukas, 2015. "Optimal public information dissemination: Introducing observational learning into a generalized beauty contest," HWWI Research Papers 169, Hamburg Institute of International Economics (HWWI).
    5. Furkan Sezer & Hossein Khazaei & Ceyhun Eksin, 2021. "Maximizing Social Welfare and Agreement via Information Design in Linear-Quadratic-Gaussian Games," Papers 2102.13047, arXiv.org, revised Feb 2023.
    6. Matthew O. Jackson & Brian W. Rogers & Yves Zenou, 2016. "Networks: An Economic Perspective," Papers 1608.07901, arXiv.org.
    7. Hüning, Hendrik & Meub, Lukas, 2016. "Optimal public information dissemination: Introducing multiplier effects into a generalized beauty contest," University of Göttingen Working Papers in Economics 260 [rev.], University of Goettingen, Department of Economics.

  3. 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. Liu, Ying & Fang, Aili, 2024. "Analysis of opinion evolution based on non-Bayesian social learning," Applied Mathematics and Computation, Elsevier, vol. 464(C).
    2. Edoardo Gallo & Alastair Langtry, 2020. "Social networks, confirmation bias and shock elections," Papers 2011.00520, arXiv.org.
    3. Comola, Margherita & Rusinowska, Agnieszka & Villeval, Marie Claire, 2024. "Competing for Influence in Networks through Strategic Targeting," IZA Discussion Papers 17315, Institute of Labor Economics (IZA).
    4. 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.
    5. Eger, Steffen, 2016. "Opinion dynamics and wisdom under out-group discrimination," Mathematical Social Sciences, Elsevier, vol. 80(C), pages 97-107.
    6. Berno Buechel & Tim Hellmann & Stefan Kölßner, 2014. "Opinion Dynamics and Wisdom under Conformity," Working Papers 2014.51, Fondazione Eni Enrico Mattei.
    7. 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", revised 2018.
    8. Khandelwal, Vatsal, 2024. "Learning in networks with idiosyncratic agents," Games and Economic Behavior, Elsevier, vol. 144(C), pages 225-249.
    9. Benjamin Golub & Stephen Morris, 2020. "Expectations, Networks, and Conventions," Papers 2009.13802, arXiv.org.
    10. Fernandes, Marcos R., 2023. "Confirmation bias in social networks," Mathematical Social Sciences, Elsevier, vol. 123(C), pages 59-76.
    11. Low, Nicholas Kah Yean & Melatos, Andrew, 2022. "Discerning media bias within a network of political allies and opponents: The idealized example of a biased coin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    12. Aislinn Bohren & Daniel Hauser, 2017. "Bounded Rationality And Learning: A Framwork and A Robustness Result," PIER Working Paper Archive 17-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 May 2017.
    13. Dasaratha, Krishna & He, Kevin, 2020. "Network structure and naive sequential learning," Theoretical Economics, Econometric Society, vol. 15(2), May.
    14. 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.
    15. 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.
    16. Seokbeom KWON & Kazuyuki MOTOHASHI, 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).
    17. Kawakami, Hajime, 2023. "Doob’s consistency of a non-Bayesian updating process," Statistics & Probability Letters, Elsevier, vol. 203(C).
    18. Arieli, Itai & Babichenko, Yakov & Shlomov, Segev, 2021. "Virtually additive learning," Journal of Economic Theory, Elsevier, vol. 197(C).
    19. Levy, Gilat & Razin, Ronny, 2018. "Information diffusion in networks with the Bayesian Peer Influence heuristic," LSE Research Online Documents on Economics 86554, London School of Economics and Political Science, LSE Library.
    20. Christoph Aymanns & Jakob Foerster & Co-Pierre Georg, 2017. "Fake News in Social Networks," Papers 1708.06233, arXiv.org.
    21. Matthew Ellman, 2017. "Online Social Networks: Approval by Design," Working Papers 17-18, NET Institute.
    22. Lu, Danning & Wang, Pengyu, 2024. "Dynamic pricing for new experience products in pre-sale mode with social learning," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    23. Amir, Gideon & Arieli, Itai & Ashkenazi-Golan, Galit & Peretz, Ron, 2025. "Granular DeGroot dynamics – A model for robust naive learning in social networks," Journal of Economic Theory, Elsevier, vol. 223(C).
    24. Buechel Berno & Klößner, Stefan & Meng, Fanyuan & Nassar, Anis, 2022. "Misinformation due to asymmetric information sharing," FSES Working Papers 528, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    25. Bar Ifrach & Costis Maglaras & Marco Scarsini, 2012. "Monopoly Pricing in the Presence of Social Learning," Working Papers 12-01, NET Institute, revised Sep 2012.
    26. 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.
    27. , & ,, 2015. "Information diffusion in networks through social learning," Theoretical Economics, Econometric Society, vol. 10(3), September.
    28. Ozan Candogan & Nicole Immorlica & Bar Light & Jerry Anunrojwong, 2022. "Social Learning under Platform Influence: Consensus and Persistent Disagreement," Papers 2202.12453, arXiv.org, revised Jun 2025.
    29. Daron Acemoglu & Asuman E. Ozdaglar & Alireza Tahbaz Salehi, 2015. "Networks, Shocks, and Systemic Risk," Levine's Bibliography 786969000000001187, UCLA Department of Economics.
    30. 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.
    31. Li, Wei & Tan, Xu, 2020. "Locally Bayesian learning in networks," Theoretical Economics, Econometric Society, vol. 15(1), January.
    32. 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.
    33. Azzimonti, Marina & Fernandes, Marcos, 2023. "Social media networks, fake news, and polarization," European Journal of Political Economy, Elsevier, vol. 76(C).
    34. Cao, GangCheng & Fang, Debin & Wang, Pengyu, 2021. "The impacts of social learning on a real-time pricing scheme in the electricity market," Applied Energy, Elsevier, vol. 291(C).
    35. Mueller-Frank, Manuel, 2024. "As strong as the weakest node: The impact of misinformation in social networks," Journal of Economic Theory, Elsevier, vol. 215(C).
    36. J. Aislinn Bohren & Daniel N. Hauser, 2021. "Learning with Heterogeneous Misspecfied Models: Characterization and Robustness," PIER Working Paper Archive 21-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    37. Aislinn Bohren & Daniel Hauser, 2018. "Social Learning with Model Misspeciification: A Framework and a Robustness Result," PIER Working Paper Archive 18-017, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jul 2018.
    38. Li, Wei & Tan, Xu, 2021. "Cognitively-constrained learning from neighbors," Games and Economic Behavior, Elsevier, vol. 129(C), pages 32-54.
    39. Steven Kivinen & Norovsambuu Tumennasan, 2016. "Consensus in Social Networks: Revisited," Working Papers daleconwp2016-05, Dalhousie University, Department of Economics.
    40. Francesco Drago & Friederike Mengel & Christian Traxler, 2020. "Compliance Behavior in Networks: Evidence from a Field Experiment," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 96-133, April.
    41. 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.
    42. Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2021. "Rational Groupthink," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(1), pages 621-668.
      • Matan Harel & Elchanan Mossel & Philipp Strack & Omer Tamuz, 2014. "Rational Groupthink," Papers 1412.7172, arXiv.org, revised Jun 2020.
    43. Huihui Ding & Marcus Pivato, 2021. "Deliberation and epistemic democracy," Post-Print hal-03637874, HAL.
    44. Luo, Xi & Gao, Yaru & Liu, Xiaojun & Sun, Yongkai & Li, Na & Liu, Jianghua, 2023. "ACHRA: A novel model to study the propagation of clean heating acceptance among rural residents based on social networks," Applied Energy, Elsevier, vol. 333(C).
    45. Mueller-Frank, Manuel, 2015. "Reaching Consensus in Social Networks," IESE Research Papers D/1116, IESE Business School.
    46. Li, He & Fang, Debin & Zhao, Chaoyang, 2024. "Retail competition among multi-type retail electric providers in social networks," Energy Economics, Elsevier, vol. 132(C).
    47. Matjaž Steinbacher & Mitja Steinbacher, 2019. "Opinion Formation with Imperfect Agents as an Evolutionary Process," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 479-505, February.
    48. Guodong Shi & Alexandre Proutiere & Mikael Johansson & John S. Baras & Karl H. Johansson, 2016. "The Evolution of Beliefs over Signed Social Networks," Operations Research, INFORMS, vol. 64(3), pages 585-604, June.
    49. Ionel Popescu & Tushar Vaidya, 2019. "Averaging plus Learning Models and Their Asymptotics," Papers 1904.08131, arXiv.org, revised Jul 2023.
    50. Sebastiano Della Lena & Luca Paolo Merlino, 2021. "Group Identity, Social Learning and Opinion Dynamics," Papers 2110.07226, arXiv.org, revised May 2022.
    51. Glass, Catherine A. & Glass, David H., 2021. "Opinion dynamics of social learning with a conflicting source," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    52. Ilan Lobel & Evan Sadler, 2013. "Preferences, Homophily, and Social Learning," Working Papers 13-01, NET Institute.
    53. Pooya Molavi & Ceyhun Eksin & Alejandro Ribeiro & Ali Jadbabaie, 2016. "Learning to Coordinate in Social Networks," Operations Research, INFORMS, vol. 64(3), pages 605-621, June.
    54. 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.
    55. Rajiv Sethi & Muhamet Yildiz, 2013. "Perspectives, Opinions, and Information Flows," Levine's Working Paper Archive 786969000000000934, David K. Levine.
    56. Fang, Aili, 2021. "The influence of communication structure on opinion dynamics in social networks with multiple true states," Applied Mathematics and Computation, Elsevier, vol. 406(C).
    57. Munther A. Dahleh & Alireza Tahbaz-Salehi & John N. Tsitsiklis & Spyros I. Zoumpoulis, 2016. "Technical Note—Coordination with Local Information," Operations Research, INFORMS, vol. 64(3), pages 622-637, June.
    58. Catherine A. Glass & David H. Glass, 2021. "Social Influence of Competing Groups and Leaders in Opinion Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 58(3), pages 799-823, October.
    59. 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.
    60. Saeed Badri & Bernd Heidergott & Ines Lindner, 2022. "Na?ve Learning in Social Networks with Fake News: Bots as a Singularity," Tinbergen Institute Discussion Papers 22-097/II, Tinbergen Institute.
    61. Maxim Raginsky & Angelia Nedić, 2016. "Online Discrete Optimization in Social Networks in the Presence of Knightian Uncertainty," Operations Research, INFORMS, vol. 64(3), pages 662-679, June.
    62. 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.
    63. 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.
    64. Fang, Aili & Wang, Lin & Wei, Xinjiang, 2019. "Social learning with multiple true states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 375-386.
    65. Della Lena, Sebastiano, 2024. "The spread of misinformation in networks with individual and social learning," European Economic Review, Elsevier, vol. 168(C).
    66. Wang, Pengyu & Fang, Debin & Cao, GangCheng, 2022. "How social learning affects customer behavior under the implementation of TOU in the electricity retailing market," Energy Economics, Elsevier, vol. 106(C).
    67. Xiyang Hu & Yan Huang & Beibei Li & Tian Lu, 2022. "Uncovering the Source of Machine Bias," Papers 2201.03092, arXiv.org.
    68. Gallo, E. & Langtry, A., 2020. "Social Networks, Confirmation Bias and Shock Elections," Cambridge Working Papers in Economics 2099, Faculty of Economics, University of Cambridge.
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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper 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-DGE: Dynamic General Equilibrium (1) 2019-09-30
  2. NEP-MAC: Macroeconomics (1) 2019-09-30

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