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Jan Lorenz

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. Jan Lorenz & Christoph Brauer & Dirk A. Lorenz, 2016. "Rank-optimal weighting or "How to be best in the OECD Better Life Index?"," Papers 1608.04556, arXiv.org.

    Cited by:

    1. Jose Manuel Cordero & Cristina Polo & Javier Salinas-Jiménez, 2021. "Subjective Well-Being and Heterogeneous Contexts: A Cross-National Study Using Semi-Nonparametric Frontier Methods," Journal of Happiness Studies, Springer, vol. 22(2), pages 867-886, February.
    2. Koronakos, Gregory & Smirlis, Yiannis & Sotiros, Dimitris & Despotis, Dimitris K., 2020. "Assessment of OECD Better Life Index by incorporating public opinion," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    3. Jordi Paniagua & Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2020. "Asylum migration in OECD countries: In search of lost well-being," Working Papers 2008, Department of Applied Economics II, Universidad de Valencia.
    4. Thananon Buathong & Anna Dimitrova & Paolo Miguel M. Vicerra & Montakarn Chimmamee, 2021. "Years of Good Life: An illustration of a new well-being indicator using data for Thailand," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 19(1), pages 547-583.
    5. Fusco, Elisa, 2023. "Potential improvements approach in composite indicators construction: The Multi-directional Benefit of the Doubt model," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    6. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "OECD: One or Many? Ranking Countries with a Composite Well-Being Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 847-869, October.
    7. Peiró-Palomino, Jesús & Picazo-Tadeo, Andrés J. & Tortosa-Ausina, Emili, 2021. "Measuring well-being in Colombian departments. The role of geography and demography," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    8. Ilya Solntsev & Anatoly Vorobyev & Elnura Irmatova & Nikita Osokin, 2016. "Rating evaluation of sports development efficiency using statistical analysis: evidence from Russian football," Papers 1612.07543, arXiv.org.
    9. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "Assessing well-being in European regions. Does government quality matter?," Working Papers 2018/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    10. Greco, Salvatore & Ishizaka, Alessio & Resce, Giuliano & Torrisi, Gianpiero, 2017. "Is the Grass Always Greener on the Other Side of the fence? Composite Index of Well-Being Taking into Account the Local Relative Appreciations in Better Life Index," MPRA Paper 82718, University Library of Munich, Germany.
    11. Justin Ehrlich & Simon Medcalfe & Shane Sanders, 2021. "Composite Index Ranking of Economic Well-Being in U.S. Metropolitan Areas: How Prevalent are Rank Anomalies?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 543-562, September.
    12. Jesús Peiró‐Palomino & Andrés J. Picazo‐Tadeo & Vicente Rios, 2020. "Well‐being in European regions: Does government quality matter?," Papers in Regional Science, Wiley Blackwell, vol. 99(3), pages 555-582, June.
    13. Shunichi Hienuki & Kazuhiko Noguchi & Tadahiro Shibutani & Takahiro Saigo & Atsumi Miyake, 2019. "The Balance of Individual and Infrastructure Values in Decisions Regarding Advanced Science and Technology," Sustainability, MDPI, vol. 11(12), pages 1-15, June.
    14. Jesús Peiró-Palomino, 2019. "Regional well-being in the OECD," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(2), pages 195-218, June.
    15. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo & Vicente Rios, 2020. "Social Progress Around the World: Measurement, Evolution and Convergence," Working Papers 2006, Department of Applied Economics II, Universidad de Valencia.
    16. Luis Cesar Herrero-Prieto & Ivan Boal-San Miguel & Mafalda Mafalda Gomez-Vega, 2018. "Deep-Rooted Culture and Economic Development: Taking the Seven Deadly Sins to Build A Well-Being Composite Indicator," ACEI Working Paper Series AWP-04-2018, Association for Cultural Economics International, revised Jul 2018.
    17. Eni Dardha & Nicky Rogge, 2020. "How's Life in Your Region? Measuring Regional Material Living Conditions, Quality of Life and Subjective Well-Being in OECD Countries Using a Robust, Conditional Benefit-of-the-Doubt Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 1015-1073, October.
    18. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to OECD’s Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 917-954, June.
    19. Resce, Giuliano & Maynard, Diana, 2018. "What matters most to people around the world? Retrieving Better Life Index priorities on Twitter," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 61-75.
    20. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo & Emili Tortosa-Ausina, 2020. "The Geography of Well-being in Colombia," Working Papers 2020/03, Economics Department, Universitat Jaume I, Castellón (Spain).

  2. Michael Koenig & Jan Lorenz & Fabrizio Zilibotti, 2012. "Innovation vs. Imitation and the Evolution of Productivity Distributions," Discussion Papers 11-008, Stanford Institute for Economic Policy Research.

    Cited by:

    1. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia, 2019. "Concentration in international markets: evidence from US Imports," Economics Working Papers 1635, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Robert E. Lucas Jr. & Benjamin Moll, 2014. "Knowledge Growth and the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 122(1), pages 1-51.
    3. Jess Benhabib & 'Eric Brunet & Mildred Hager, 2020. "Innovation and imitation," Papers 2006.06315, arXiv.org, revised Aug 2020.
    4. Kjetil Storesletten & Bo Zhao & Fabrizio Zilibotti, 2019. "Business Cycle during Structural Change: Arthur Lewis' Theory from a Neoclassical Perspective," NBER Working Papers 26181, National Bureau of Economic Research, Inc.
    5. Sampson, Thomas, 2023. "Technology gaps, trade and income," LSE Research Online Documents on Economics 117370, London School of Economics and Political Science, LSE Library.
    6. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia, 2018. "Firms and Economic Performance: A View from Trade," Working Papers 1047, Barcelona School of Economics.
    7. Adetutu, Morakinyo O. & Ajayi, Victor, 2020. "The impact of domestic and foreign R&D on agricultural productivity in sub-Saharan Africa," World Development, Elsevier, vol. 125(C).
    8. Douglas Hanley & Ufuk Akcigit & Nicolas Serrano-Velarde, 2014. "Back to Basics: Basic Research Spillovers, Innovation Policy and Growth," Working Paper 535, Department of Economics, University of Pittsburgh, revised Jan 2014.
    9. Jangho Yang & Torsten Heinrich & Julian Winkler & Franc{c}ois Lafond & Pantelis Koutroumpis & J. Doyne Farmer, 2019. "Measuring productivity dispersion: a parametric approach using the L\'{e}vy alpha-stable distribution," Papers 1910.05219, arXiv.org, revised Apr 2022.
    10. Michele Battisti & Filippo Belloc & Massimo Del Gatto, 2012. "Unbundling Technology Adoption and TFP at the Firm Level. Do Intangibles Matter?," Working Paper series 71_12, Rimini Centre for Economic Analysis.
    11. Bircan, Cagatay & de Haas, R., 2015. "The Limits of Lending : Banks and Technology Adoption Across Russia," Discussion Paper 2015-011, Tilburg University, Center for Economic Research.
    12. Huang, Siyu & Shi, Yi & Chen, Qinghua & Li, Xiaomeng, 2022. "The growth path of high-tech industries: Statistical laws and evolution demands," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    13. Ufuk Akcigit & Murat Alp Celik & Jeremy Greenwood, 2013. "Buy, Keep or Sell: Economic Growth and the Market for Ideas," Economie d'Avant Garde Research Reports 21, Economie d'Avant Garde.
    14. Ezra Oberfield & Francisco Buera, 2016. "The Global Diffusion of Ideas," 2016 Meeting Papers 1538, Society for Economic Dynamics.
    15. Sampson, Thomas, 2014. "Dynamic selection: an idea flows theory of entry, trade and growth," LSE Research Online Documents on Economics 60363, London School of Economics and Political Science, LSE Library.
    16. Crinò, Rosario & Bonfiglioli, Alessandra & Gancia, Gino, 2021. "International Trade with Heterogeneous Firms: Theory and Evidence," CEPR Discussion Papers 16249, C.E.P.R. Discussion Papers.
    17. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2021. "Reconciling Models of Diffusion and Innovation: A Theory of the Productivity Distribution and Technology Frontier," Econometrica, Econometric Society, vol. 89(5), pages 2261-2301, September.
    18. David de la Croix & Matthias Doepke & Joel Mokyr, 2016. "Clans, Guilds, and Markets: Apprenticeship Institutions and Growth in the Pre-Industrial Economy," Working Papers 2016-008, Human Capital and Economic Opportunity Working Group.
    19. Leonidov, A. & Vasilyeva, E., 2020. "Schumpeterian evolution of firms' capital-labor ratio distribution," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 12-40.
    20. Jess Benhabib & Jesse Perla & Christopher Tonetti, 2014. "Catch-up and fall-back through innovation and imitation," Journal of Economic Growth, Springer, vol. 19(1), pages 1-35, March.
    21. Keiichi Kishi, 2016. "Technology Diffusion, Pareto Distribution, and Patent Policy," Discussion Papers in Economics and Business 16-31, Osaka University, Graduate School of Economics.
    22. Chen, Yi-Fan & Hsu, Wen-Tai & Peng, Shin-Kun, 2023. "Innovation, firm size distribution, and gains from trade," Theoretical Economics, Econometric Society, vol. 18(1), January.
    23. Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia, 2014. "Betting on exports: Trade and endogenous heterogeneity," Economics Working Papers 1460, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2016.
    24. Daniele Eckert Matzembacher & Rogério Leite Gonzales & Carlos S. V. Saldanha, 2019. "Can street entrepreneurs be Schumpeterian entrepreneurs? The case of food trucks as family firms in an emerging country," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 9(1), pages 1-24, December.
    25. Matthias Doepke & Joel Mokyr & David de la Croix, 2013. "Apprenticeship and Technological Progress in the Malthusian World," 2013 Meeting Papers 76, Society for Economic Dynamics.
    26. Charles I. Jones & Jihee Kim, 2018. "A Schumpeterian Model of Top Income Inequality," Journal of Political Economy, University of Chicago Press, vol. 126(5), pages 1785-1826.
    27. Lahr, Henry, 2023. "Fat tails in private equity fund returns: The smooth double Pareto distribution," International Review of Financial Analysis, Elsevier, vol. 86(C).
    28. Lafond, François, 2015. "Self-organization of knowledge economies," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 150-165.
    29. Has van Vlokhoven, 2023. "Diffusion of Ideas in Networks with Endogenous Search," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 269-311, July.
    30. Simon Alder & Lin Shao & Fabrizio Zilibotti, 2016. "Economic reforms and industrial policy in a panel of Chinese cities," Journal of Economic Growth, Springer, vol. 21(4), pages 305-349, December.
    31. Gregor Jarosch & Ezra Oberfield & Esteban Rossi-Hansberg, 2020. "Learning from Coworkers," Working Papers 2020-63, Princeton University. Economics Department..
    32. , & Lorenz, Jan & ,, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
    33. Jesse Perla & Christopher Tonetti, 2012. "Equilibrium Imitation and Growth," Working Papers 12-03, New York University, Leonard N. Stern School of Business, Department of Economics.
    34. Nguyen, Huong, 2016. "Does Proximity to Foreign Invested Firms Stimulate Productivity Growth of Domestic Firms? Firm-level Evidence from Vietnam," Papers 1001, World Trade Institute.
    35. Fabrizio Zilibotti, 2017. "Growing and Slowing Down Like China," Journal of the European Economic Association, European Economic Association, vol. 15(5), pages 943-988.
    36. Zhang, Yiran, 2021. "Quantitative Assessment on Frictions in Technology Market," MPRA Paper 109470, University Library of Munich, Germany.
    37. Lee, Velma & Viale, Ariel M., 2023. "Total factor productivity in East Asia under ambiguity," Economic Modelling, Elsevier, vol. 121(C).
    38. Polterovich, V., 2017. "The Theory of Endogenous Economic Growth and Equations of Mathematical Physics," Journal of the New Economic Association, New Economic Association, vol. 34(2), pages 193-201.
    39. Michael König & Zheng Michael Song & Kjetil Storesletten & Fabrizio Zilibotti, 2020. "From Imitation to Innovation: Where Is all that Chinese R&D Going?," NBER Working Papers 27404, National Bureau of Economic Research, Inc.
    40. Moen, Espen R. & Heggedal, Tom-Reiel & Preugschat, Edgar, 2014. "Productivity Spillovers Through Labor Mobility," CEPR Discussion Papers 9850, C.E.P.R. Discussion Papers.
    41. Long, Yingzi & Cai, Dapeng, 2023. "Why do governments subsidize R&D-Intensive foreign direct investment?," Economic Modelling, Elsevier, vol. 129(C).
    42. Duffy, John & Ralston, Jason, 2020. "Innovate versus imitate: Theory and experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 727-751.
    43. Jayanthakumaran, Kankesu & Bari, Mohammad Tariful, 2021. "Resource boom and non-resource firms: Mongolia 2007 and 2011," Resources Policy, Elsevier, vol. 74(C).
    44. König, Michael D. & Rogers, Tim, 2023. "Endogenous technology cycles in dynamic R&D networks," European Economic Review, Elsevier, vol. 158(C).
    45. Erzo G. J. Luttmer, 2015. "An Assignment Model of Knowledge Diffusion and Income Inequality," Staff Report 509, Federal Reserve Bank of Minneapolis.
    46. Slivko, Olga, 2012. "Innovation strategies of German firms: The effect of competition and intellectual property protection," ZEW Discussion Papers 12-089, ZEW - Leibniz Centre for European Economic Research.
    47. Erzo G. J. Luttmer, 2012. "Eventually, noise and imitation implies balanced growth," Working Papers 699, Federal Reserve Bank of Minneapolis.
    48. Chih-Sheng Hsieh & Michael D. König & Xiaodong Liu, 2012. "Network formation with local complements and global substitutes: the case of R&D networks," ECON - Working Papers 217, Department of Economics - University of Zurich, revised Feb 2017.
    49. Polterovich, Victor, 2017. "Теория Эндогенного Экономического Роста И Уравнения Математической Физики [The theory of endogenous economic growth and equations of mathematical physics]," MPRA Paper 78622, University Library of Munich, Germany.
    50. Nyeong Seon Son & Jung Hur, 2022. "An empirical study of firm productivity growth based on the dynamic selection model: Effects on the recent decline in Korean exports," Contemporary Economic Policy, Western Economic Association International, vol. 40(1), pages 190-203, January.
    51. Kishi, Keiichi, 2019. "Technology diffusion, innovation size, and patent policy," European Economic Review, Elsevier, vol. 118(C), pages 382-410.
    52. Krishna Dasaratha, 2019. "Innovation and Strategic Network Formation," Papers 1911.06872, arXiv.org, revised Mar 2022.
    53. Heggedal, Tom-Reiel & Moen, Espen R. & Preugschat, Edgar, 2017. "Productivity spillovers through labor mobility in search equilibrium," Journal of Economic Theory, Elsevier, vol. 169(C), pages 551-602.
    54. Michael König & Kjetil Storesletten & Zheng Song & Fabrizio Zilibotti, 2022. "From Imitation to Innovation: Where Is All That Chinese R&D Going?," Econometrica, Econometric Society, vol. 90(4), pages 1615-1654, July.
    55. Staley, Mark, 2015. "Firm Growth and Selection in a Finite Economy," MPRA Paper 67291, University Library of Munich, Germany.
    56. Staley, Mark, 2018. "The Knowledge-Diffusion Bottleneck in Economic Growth and Development," MPRA Paper 87255, University Library of Munich, Germany.
    57. Lafond, François & Farmer, J. Doyne & Koutroumpis, Pantelis & Winkler, Julian & Heinrich, Torsten & Yang, Jangho, 2019. "Measuring productivity dispersion: a parametric approach using the Lévy alpha-stable distribution," INET Oxford Working Papers 2019-14, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    58. Olivier Gallay & Fariba Hashemi & Max-Olivier Hongler, 2019. "Imitation, Proximity, And Growth — A Collective Swarm Dynamics Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-43, August.
    59. Kishi, Keiichi & Okada, Keisuke, 2021. "The impact of trade liberalization on productivity distribution under the presence of technology diffusion and innovation," Journal of International Economics, Elsevier, vol. 128(C).

  3. Jan Lorenz & Stefano Battiston & Frank Schweitzer, 2009. "Systemic Risk in a Unifying Framework for Cascading Processes on Networks," Papers 0907.5325, arXiv.org, revised Jan 2010.

    Cited by:

    1. Pawe{l} Sieczka & Didier Sornette & Janusz A. Ho{l}yst, 2010. "The Lehman Brothers Effect and Bankruptcy Cascades," Papers 1002.1070, arXiv.org, revised Sep 2011.
    2. Erhan Bayraktar & Gaoyue Guo & Wenpin Tang & Yuming Paul Zhang, 2022. "Systemic robustness: a mean-field particle system approach," Papers 2212.08518, arXiv.org, revised Aug 2023.
    3. Paolo Giudici & Laura Parisi, 2016. "Bail in or Bail out? The Atlante example from a systemic risk perspective," DEM Working Papers Series 124, University of Pavia, Department of Economics and Management.
    4. Jan Lorenz & Stefano Battiston & Frank Schweitzer, "undated". "Systemic Risk in a Unifying Framework for Cascading Processes on Networks," Working Papers CCSS-09-011, ETH Zurich, Chair of Systems Design.
    5. Gogas, Periklis & Papadimitriou, Theophilos & Matthaiou, Maria, 2014. "A novel Banking Supervision Method using the Minimum Dominating Set," DUTH Research Papers in Economics 1-2014, Democritus University of Thrace, Department of Economics.
    6. Paolo Giudici & Laura Parisi, 2016. "CoRisk: measuring systemic risk through default probability contagion," DEM Working Papers Series 116, University of Pavia, Department of Economics and Management.
    7. Andreas Joseph & Stephan Joseph & Guanrong Chen, 2013. "Cross-border Portfolio Investment Networks and Indicators for Financial Crises," Papers 1306.0215, arXiv.org, revised Jan 2014.
    8. Aymeric Vié & Alfredo J. Morales, 2021. "How Connected is Too Connected? Impact of Network Topology on Systemic Risk and Collapse of Complex Economic Systems," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1327-1351, April.
    9. Paolo Giudici & Laura Parisi, 2018. "CoRisk: Credit Risk Contagion with Correlation Network Models," Risks, MDPI, vol. 6(3), pages 1-19, September.
    10. Kobayashi, Teruyoshi, 2014. "A model of financial contagion with variable asset returns may be replaced with a simple threshold model of cascades," Economics Letters, Elsevier, vol. 124(1), pages 113-116.
    11. Teruyoshi Kobayashi & Kohei Hasui, 2013. "Efficient immunization strategies to prevent financial contagion," Papers 1308.0652, arXiv.org, revised Dec 2013.
    12. Mehmet Ziya Gorpe & Giovanni Covi & Christoffer Kok, 2019. "CoMap: Mapping Contagion in the Euro Area Banking Sector," IMF Working Papers 2019/102, International Monetary Fund.
    13. Gualdi, Stanislao & Tarzia, Marco & Zamponi, Francesco & Bouchaud, Jean-Philippe, 2015. "Tipping points in macroeconomic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 29-61.
    14. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    15. F. Schweitzer & D. Garcia, 2010. "An agent-based model of collective emotions in online communities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 533-545, October.
    16. Hossein Dastkhan & Naser Shams Gharneh, 2019. "Simulation of Contagion in the Stock Markets Using Cross-Shareholding Networks: A Case from an Emerging Market," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1071-1101, March.
    17. Frank Schweitzer & Giorgio Fagiolo & Didier Sornette & Fernando Vega-Redondo & Douglas R. White, 2009. "Economic Networks: What Do We Know And What Do We Need To Know?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 12(04n05), pages 407-422.
    18. Sam Langfield & Kimmo Soramäki, 2016. "Interbank Exposure Networks," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 3-17, January.
    19. Ellinas, Christos & Allan, Neil & Johansson, Anders, 2016. "Project systemic risk: Application examples of a network model," International Journal of Production Economics, Elsevier, vol. 182(C), pages 50-62.
    20. Claudio J. Tessone & Antonios Garas & Beniamino Guerra & Frank Schweitzer, "undated". "How big is too big? Critical Shocks for Systemic Failure Cascades," Working Papers ETH-RC-12-015, ETH Zurich, Chair of Systems Design.
    21. Rebekka Burkholz & Matt V. Leduc & Antonios Garas & Frank Schweitzer, 2015. "Systemic risk in multiplex networks with asymmetric coupling and threshold feedback," Papers 1506.06664, arXiv.org.
    22. Wang, Jianwei & Sun, Enhui & Xu, Bo & Li, Peng & Ni, Chengzhang, 2016. "Abnormal cascading failure spreading on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 695-701.
    23. Xing, Lizhi & Guan, Jun & Dong, Xianlei & Wu, Shan, 2018. "Understanding the competitive advantage of TPP-related nations from an econophysics perspective: Influence caused by China and the United States," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 164-184.
    24. Wang, Jianwei & Cai, Lin & Xu, Bo & Li, Peng & Sun, Enhui & Zhu, Zhiguo, 2016. "Out of control: Fluctuation of cascading dynamics in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1231-1243.
    25. Paolo Giudici & Laura Parisi, 2019. "Bail-In or Bail-Out? Correlation Networks to Measure the Systemic Implications of Bank Resolution," Risks, MDPI, vol. 7(1), pages 1-25, January.
    26. Christos Ellinas & Neil Allan & Anders Johansson, 2016. "Exploring Structural Patterns Across Evolved and Designed Systems: A Network Perspective," Systems Engineering, John Wiley & Sons, vol. 19(3), pages 179-192, May.
    27. Iris Lucas & Michel Cotsaftis & Cyrille Bertelle, 2018. "Self-Organization, Resilience and Robustness of Complex Systems Through an Application to Financial Market from an Agent-Based Approach," Post-Print hal-02114928, HAL.
    28. Didier Wernli & Lucas Böttcher & Flore Vanackere & Yuliya Kaspiarovich & Maria Masood & Nicolas Levrat, 2023. "Understanding and governing global systemic crises in the 21st century: A complexity perspective," Global Policy, London School of Economics and Political Science, vol. 14(2), pages 207-228, May.
    29. Jayles, Bertrand & Cheong, Siew Ann & Herrmann, Hans J., 2022. "Modeling the resilience of social networks to lockdowns regarding the dynamics of meetings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    30. Paolo Giudici & Peter Sarlin & Alessandro Spelta, 2016. "The multivariate nature of systemic risk: direct and common exposures," DEM Working Papers Series 118, University of Pavia, Department of Economics and Management.
    31. Aymeric Vi'e & Alfredo J. Morales, 2019. "How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems," Papers 1912.09814, arXiv.org.
    32. Rebekka Burkholz & Hans J. Herrmann & Frank Schweitzer, 2018. "Explicit size distributions of failure cascades redefine systemic risk on finite networks," Papers 1802.03286, arXiv.org.
    33. Josselin Garnier & George Papanicolaou & Tzu-Wei Yang, 2012. "Large deviations for a mean field model of systemic risk," Papers 1204.3536, arXiv.org, revised Aug 2012.
    34. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    35. Giudici, Paolo & Abu-Hashish, Iman, 2019. "What determines bitcoin exchange prices? A network VAR approach," Finance Research Letters, Elsevier, vol. 28(C), pages 309-318.
    36. Safarzyńska, Karolina & van den Bergh, Jeroen C.J.M., 2017. "Integrated crisis-energy policy: Macro-evolutionary modelling of technology, finance and energy interactions," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 119-137.
    37. Schweitzer, Frank, 2021. "Social percolation revisited: From 2d lattices to adaptive networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    38. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
    39. Sergey Nadtochiy & Mykhaylo Shkolnikov, 2017. "Particle systems with singular interaction through hitting times: application in systemic risk modeling," Papers 1705.00691, arXiv.org.
    40. Jean-Philippe Bouchaud, 2012. "Crises and collective socio-economic phenomena: simple models and challenges," Papers 1209.0453, arXiv.org, revised Dec 2012.
    41. Frank Schweitzer & Giona Casiraghi & Mario V. Tomasello & David Garcia, 2020. "Fragile, yet resilient: Adaptive decline in a collaboration network of firms," Papers 2011.13369, arXiv.org.
    42. Leonidas Sandoval Junior, 2014. "Dynamics in two networks based on stocks of the US stock market," Papers 1408.1728, arXiv.org, revised Aug 2014.
    43. Sandoval, Leonidas Junior, 2013. "To lag or not to lag? How to compare indices of stock markets that operate at different times," Insper Working Papers wpe_319, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    44. Galvan, Giulio & Agarwal, Jitendra, 2020. "Assessing the vulnerability of infrastructure networks based on distribution measures," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    45. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    46. Ying Chen & Paolo Giudici & Branka Hadji Misheva & Simon Trimborn, 2020. "Lead Behaviour in Bitcoin Markets," Risks, MDPI, vol. 8(1), pages 1-14, January.
    47. Imen Bedoui-Belghith & Slaheddine Hallara & Faouzi Jilani, 2023. "Crisis transmission degree measurement under crisis propagation model," SN Business & Economics, Springer, vol. 3(1), pages 1-27, January.
    48. Christos Ellinas & Christos Nicolaides & Naoki Masuda, 2022. "Mitigation strategies against cascading failures within a project activity network," Journal of Computational Social Science, Springer, vol. 5(1), pages 383-400, May.
    49. Paolo Giudici & Laura Parisi, 2015. "Modeling Systemic Risk with Correlated Stochastic Processes," DEM Working Papers Series 110, University of Pavia, Department of Economics and Management.
    50. Mario Eboli & Bulent Ozel & Andrea Teglio & Andrea Toto, 2023. "Connectivity, centralisation and ‘robustness-yet-fragility’ of interbank networks," Annals of Finance, Springer, vol. 19(2), pages 169-200, June.

  4. Jan Lorenz & Fabian Paetzel & Frank Schweitzer, "undated". "Redistribution spurs growth by using a portfolio effect on risky human capital," Working Papers ETH-RC-12-018, ETH Zurich, Chair of Systems Design.

    Cited by:

    1. Frank Schweitzer & Luca Verginer & Giacomo Vaccario, 2020. "Should The Government Reward Cooperation? Insights From An Agent-Based Model Of Wealth Redistribution," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 23(07), pages 1-19, November.
    2. Du, Jinming, 2019. "Redistribution promotes cooperation in spatial public goods games under aspiration dynamics," Applied Mathematics and Computation, Elsevier, vol. 363(C), pages 1-1.
    3. Liebmann, Thomas & Kassberger, Stefan & Hellmich, Martin, 2017. "Sharing and growth in general random multiplicative environments," European Journal of Operational Research, Elsevier, vol. 258(1), pages 193-206.

Articles

  1. Jan Lorenz & Christoph Brauer & Dirk Lorenz, 2017. "Rank-Optimal Weighting or “How to be Best in the OECD Better Life Index?”," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(1), pages 75-92, October.
    See citations under working paper version above.
  2. Takasumi Kurahashi-Nakamura & Michael Mäs & Jan Lorenz, 2016. "Robust Clustering in Generalized Bounded Confidence Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-7.

    Cited by:

    1. Christos Mavridis & Nikolas Tsakas, 2021. "Social Capital, Communication Channels and Opinion Formation," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 56(4), pages 635-678, May.
    2. Khalil, Nagi, 2021. "Approach to consensus in models of continuous-opinion dynamics: A study inspired by the physics of granular gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    3. Weimer, Christopher W. & Miller, J.O. & Hill, Raymond R. & Hodson, Douglas D., 2022. "An opinion dynamics model of meta-contrast with continuous social influence forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    4. Baumann, Fabian & Sokolov, Igor M. & Tyloo, Melvyn, 2020. "A Laplacian approach to stubborn agents and their role in opinion formation on influence networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    5. Francisco J. León-Medina & Jordi Tena-Sánchez & Francisco J. Miguel, 2020. "Fakers becoming believers: how opinion dynamics are shaped by preference falsification, impression management and coherence heuristics," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 385-412, April.
    6. Lipiecki, Arkadiusz & Sznajd-Weron, Katarzyna, 2022. "Polarization in the three-state q-voter model with anticonformity and bounded confidence," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    7. Thomas Feliciani & Andreas Flache & Michael Mäs, 2021. "Persuasion without polarization? Modelling persuasive argument communication in teams with strong faultlines," Computational and Mathematical Organization Theory, Springer, vol. 27(1), pages 61-92, March.
    8. Takesue, Hirofumi, 2023. "Relative opinion similarity leads to the emergence of large clusters in opinion formation models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).

  3. , & Lorenz, Jan & ,, 2016. "Innovation vs. imitation and the evolution of productivity distributions," Theoretical Economics, Econometric Society, vol. 11(3), September.
    See citations under working paper version above.
  4. J. Lorenz & S. Battiston & F. Schweitzer, 2009. "Systemic risk in a unifying framework for cascading processes on networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 441-460, October.
    See citations under working paper version above.
  5. J. Lorenz, 2009. "Universality in movie rating distributions," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(2), pages 251-258, September.

    Cited by:

    1. F. Schweitzer & D. Garcia, 2010. "An agent-based model of collective emotions in online communities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 533-545, October.
    2. David Godes & José C. Silva, 2012. "Sequential and Temporal Dynamics of Online Opinion," Marketing Science, INFORMS, vol. 31(3), pages 448-473, May.
    3. Andreas Flache & Michael Mäs & Thomas Feliciani & Edmund Chattoe-Brown & Guillaume Deffuant & Sylvie Huet & Jan Lorenz, 2017. "Models of Social Influence: Towards the Next Frontiers," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(4), pages 1-2.

  6. Diemo Urbig & Jan Lorenz & Heiko Herzberg, 2008. "Opinion Dynamics: the Effect of the Number of Peers Met at Once," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-4.

    Cited by:

    1. Jalili, Mahdi, 2013. "Social power and opinion formation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 959-966.
    2. François Rebaudo & Verónica Crespo-Pérez & Jean-François Silvain & Olivier Dangles, 2011. "Agent-Based Modeling of Human-Induced Spread of Invasive Species in Agricultural Landscapes: Insights from the Potato Moth in Ecuador," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(3), pages 1-7.
    3. Juliette Rouchier & Emily Tanimura, 2016. "Learning with Communication Barriers Due to Overconfidence. What a "Model-To-Model Analysis" Can Add to the Understanding of a Problem," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(2), pages 1-7.
    4. Iris Lorscheid & Matthias Meyer, 2021. "Toward a better understanding of team decision processes: combining laboratory experiments with agent-based modeling," Journal of Business Economics, Springer, vol. 91(9), pages 1431-1467, November.

  7. Jan Lorenz & Diemo Urbig, 2007. "About The Power To Enforce And Prevent Consensus By Manipulating Communication Rules," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 251-269.

    Cited by:

    1. Rainer Hegselmann & Stefan König & Sascha Kurz & Christoph Niemann & Jörg Rambau, 2015. "Optimal Opinion Control: The Campaign Problem," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-18.

  8. Lorenz, Jan, 2006. "Continuous Opinion Dynamics of Multidimensional Allocation Problems under Bounded Confidence. More dimensions lead to better chances for consensus," European Journal of Economic and Social Systems, Lavoisier, vol. 19(2), pages 213-227.

    Cited by:

    1. Shane T. Mueller & Yin-Yin Sarah Tan, 2018. "Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization," Journal of Computational Social Science, Springer, vol. 1(1), pages 15-48, January.
    2. Marco D'Errico & Gulnur Muradoglu & Silvana Stefani & Giovanni Zambruno, 2014. "Opinion Dynamics and Price Formation: a Nonlinear Network Model," Papers 1408.0308, arXiv.org.

  9. Jan Lorenz, 2006. "Consensus Strikes Back in the Hegselmann-Krause Model of Continuous Opinion Dynamics Under Bounded Confidence," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-8.

    Cited by:

    1. Benjamin Cabrera & Björn Ross & Daniel Röchert & Felix Brünker & Stefan Stieglitz, 2021. "The influence of community structure on opinion expression: an agent-based model," Journal of Business Economics, Springer, vol. 91(9), pages 1331-1355, November.
    2. Shane T. Mueller & Yin-Yin Sarah Tan, 2018. "Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization," Journal of Computational Social Science, Springer, vol. 1(1), pages 15-48, January.
    3. Patrick Groeber & Frank Schweitzer & Kerstin Press, 2009. "How Groups Can Foster Consensus: The Case of Local Cultures," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(2), pages 1-4.
    4. Mehrdad Agha Mohammad Ali Kermani & Reza Ghesmati & Masoud Jalayer, 2018. "Opinion-Aware Influence Maximization: How To Maximize A Favorite Opinion In A Social Network?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-27, September.
    5. Marco D'Errico & Gulnur Muradoglu & Silvana Stefani & Giovanni Zambruno, 2014. "Opinion Dynamics and Price Formation: a Nonlinear Network Model," Papers 1408.0308, arXiv.org.
    6. Rainer Hegselmann & Stefan König & Sascha Kurz & Christoph Niemann & Jörg Rambau, 2015. "Optimal Opinion Control: The Campaign Problem," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-18.

  10. Lorenz, Jan, 2005. "A stabilization theorem for dynamics of continuous opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 217-223.

    Cited by:

    1. Luo, Yun & Li, Yuke & Sun, Chudi & Cheng, Chun, 2022. "Adapted Deffuant–Weisbuch model with implicit and explicit opinions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    2. Michel Grabisch & Agnieszka Rusinowska, 2011. "A model of influence based on aggregation functions," Documents de travail du Centre d'Economie de la Sorbonne 11058, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    3. Emmanuel Maruani & Michel Grabisch & Agnieszka Rusinowska, 2012. "A study of the dynamic of influence through differential equations," PSE - Labex "OSE-Ouvrir la Science Economique" halshs-00699012, HAL.
    4. Michel Grabisch & Agnieszka Rusinowska, 2016. "Determining influential models," Post-Print halshs-01318081, HAL.
    5. Berno Buechel & Tim Hellmann & Stefan Kölßner, 2014. "Opinion Dynamics and Wisdom under Conformity," Working Papers 2014.51, Fondazione Eni Enrico Mattei.
    6. Hou, Jian & Li, Wenshan & Jiang, Mingyue, 2021. "Opinion dynamics in modified expressed and private model with bounded confidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    7. Christos Mavridis & Nikolas Tsakas, 2021. "Social Capital, Communication Channels and Opinion Formation," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 56(4), pages 635-678, May.
    8. Diemo Urbig & Jan Lorenz & Heiko Herzberg, 2008. "Opinion Dynamics: the Effect of the Number of Peers Met at Once," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-4.
    9. 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.
    10. Michel Grabisch & Agnieszka Rusinowska, 2011. "A model of influence with a continuum of actions," Post-Print hal-00666821, HAL.
    11. Büchel, Berno & Hellmann, Tim & Pichler, Michael, 2016. "The Dynamics of Continuous Cultural Traits in Social Networks," Center for Mathematical Economics Working Papers 457, Center for Mathematical Economics, Bielefeld University.
    12. Khalil, Nagi, 2021. "Approach to consensus in models of continuous-opinion dynamics: A study inspired by the physics of granular gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    13. Zhengzheng Pan & Robert P. Gilles, 2010. "Naive Learning and Game Play in a Dual Social Network Framework," Economics Working Papers 10-01, Queen's Management School, Queen's University Belfast.
    14. Michel Grabisch & Agnieszka Rusinowska, 2010. "Iterating influence between players in a social network," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00543840, HAL.
    15. Zhang, Jiangbo & Hong, Yiguang, 2013. "Opinion evolution analysis for short-range and long-range Deffuant–Weisbuch models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5289-5297.
    16. Rainer Hegselmann & Ulrich Krause, 2006. "Truth and Cognitive Division of Labour: First Steps Towards a Computer Aided Social Epistemology," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(3), pages 1-10.
    17. Michel Grabisch & Agnieszka Rusinowska, 2015. "Lattices in Social Networks with Influence," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-18.
    18. Anja Prummer & Jan-Peter Siedlarek, 2016. "Community Leaders and the Preservation of Cultural Traits," Working Papers 806, Queen Mary University of London, School of Economics and Finance.
    19. Michel Grabisch & Antoine Mandel & Agnieszka Rusinowska & Emily Tanimura, 2015. "Strategic influence in social networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01158168, HAL.
    20. Prummer, Anja & Siedlarek, Jan-Peter, 2014. "Institutions And The Preservation Of Cultural Traits," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 470, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    21. Michel Grabisch & Agnieszka Rusinowska, 2016. "Determining models of influence," PSE-Ecole d'économie de Paris (Postprint) hal-01387480, HAL.
    22. Li-Xin Wang, 2016. "Modeling Stock Price Dynamics with Fuzzy Opinion Networks," Papers 1602.06213, arXiv.org.
    23. Feldheim, Naomi Dvora & Feldheim, Ohad Noy, 2020. "Convergence of the quantile admission process with veto power," Stochastic Processes and their Applications, Elsevier, vol. 130(7), pages 4294-4325.
    24. Akylai Taalaibekova, 2018. "Opinion formation in social networks," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 28(2), pages 85-108.
    25. Steven Kivinen & Norovsambuu Tumennasan, 2016. "Consensus in Social Networks: Revisited," Working Papers daleconwp2016-05, Dalhousie University, Department of Economics.
    26. Daron Acemoglu & Asuman Ozdaglar, 2011. "Opinion Dynamics and Learning in Social Networks," Dynamic Games and Applications, Springer, vol. 1(1), pages 3-49, March.
    27. M. T. Agieva & A. V. Korolev & G. A. Ougolnitsky, 2020. "Modeling and Simulation of Impact and Control in Social Networks with Application to Marketing," Mathematics, MDPI, vol. 8(9), pages 1-28, September.
    28. Marco D'Errico & Gulnur Muradoglu & Silvana Stefani & Giovanni Zambruno, 2014. "Opinion Dynamics and Price Formation: a Nonlinear Network Model," Papers 1408.0308, arXiv.org.
    29. Kevin JS. Zollman, 2012. "Social network structure and the achievement of consensus," Politics, Philosophy & Economics, , vol. 11(1), pages 26-44, February.
    30. Phillip Monin & Richard Bookstaber, 2017. "Information Flows, the Accuracy of Opinions, and Crashes in a Dynamic Network," Staff Discussion Papers 17-01, Office of Financial Research, US Department of the Treasury.
    31. Ionel Popescu & Tushar Vaidya, 2019. "Averaging plus Learning Models and Their Asymptotics," Papers 1904.08131, arXiv.org, revised Jul 2023.
    32. Pan, Zhengzheng, 2010. "Trust, influence, and convergence of behavior in social networks," Mathematical Social Sciences, Elsevier, vol. 60(1), pages 69-78, July.
    33. Rainer Hegselmann & Stefan König & Sascha Kurz & Christoph Niemann & Jörg Rambau, 2015. "Optimal Opinion Control: The Campaign Problem," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-18.
    34. Xi Chen & Xiao Zhang & Yong Xie & Wei Li, 2017. "Opinion Dynamics of Social-Similarity-Based Hegselmann–Krause Model," Complexity, Hindawi, vol. 2017, pages 1-12, December.
    35. 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.
    36. Merlone, U. & Radi, D., 2014. "Reaching consensus on rumors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 260-271.
    37. Jiangbo Zhang, 2019. "Opinion limits study for the multi-selection bounded confidence model," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-14, January.
    38. Zhengzheng Pan, 2012. "Opinions and Networks: How Do They Effect Each Other," Computational Economics, Springer;Society for Computational Economics, vol. 39(2), pages 157-171, February.
    39. 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.
    40. Phillip J. Monin & Richard Bookstaber, 2021. "Information flows and crashes in dynamic social networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 471-495, July.

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