ABM documentation and odd protocol in economics: a bibliometric analysis. (English) Zbl 07843156
Summary: Since the first agent-based models (ABM), the scientific community has been interested in making not only the results of computational models understandable but also the modeling description, to facilitate their replication. The form that has been adopted to a greater extent has been the ODD (Overview, Design concepts, and Details) protocol, which provides a generic structure for its documentation. This protocol provides a way to clearly explain the procedures and interactions of the complex systems to be analyzed, with applications that have spread across different disciplines. This study presents a bibliometric analysis using Scopus database of the articles that emerged from the first publication of this protocol in 2006. The results show that the use of this form of documenting has grown in Economics, but its participation remains stable in relative terms. Results also show that the top journal both in number of articles and impact is JASSS, but it is not observed that there is a greater dissemination toward specific Economics journals or that it is used for a greater number of topics. Finally, it is found that there is a common core in Economics’ ABM literature, with a bias toward methodological articles in the articles that follow the ODD protocol while there is a bias towards articles on economic models in those that do not follow this protocol.
MSC:
| 91-XX | Game theory, economics, finance, and other social and behavioral sciences |
References:
| [1] | Ahmad, N., Menegaki, A. N. and Al-Muharrami, S., Systematic literature review of tourism growth nexus: An overview of the literature and a content analysis of 100 most influential papers, J. Econ. Surv.34 [2020] 1068-1110. |
| [2] | An, L., Modeling human decisions in coupled human and natural systems: Review of agent-based models, Ecol. Modell.229 [2012] 25-36. |
| [3] | Aria, M. and Cuccurullo, C., Bibliometrix: An R-tool for comprehensive science mapping analysis, J. Informetr.11 [2017] 959-975. |
| [4] | Arthur, W. B., Competing technologies, increasing returns, and lock-in by historical events, Econ. J.99 [1989] 116-131. |
| [5] | Arthur, W. B., Complexity and the Economy, (Oxford University Press, 2013). |
| [6] | Axelrod, R., The Evolution of Cooperation (Basic Books, 1984). |
| [7] | Axelrod, R., The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Vol. 3 (Princeton University Press, 1997). |
| [8] | Bankes, S., Lempert, R. and Popper, S., Making computational social science effective: Epistemology, methodology, and technology, Soc. Sci. Comput. Rev.20 [2002] 377-388. |
| [9] | Berger, T., Agent-based spatial models applied to agriculture: A simulation tool for technology diffusion, resource use changes and policy analysis, Agric. Econ.25 [2001] 245-260. |
| [10] | Blaug, M., The formalist revolution of the 1950s, J. Hist. Econ. Thought25 [2003] 145-156. |
| [11] | Blaug, M., The trade-off between rigor and relevance: Sraffian economics as a case in point, Hist. Polit. Econ.41 [2009] 219-247. |
| [12] | Blondel, V. D., Guillaume, J.-L., Lambiotte, R. and Lefebvre, E., Fast unfolding of communities in large networks, J. Stat. Mech. Theory Exp.2008 [2008] P10008. · Zbl 1459.91130 |
| [13] | Bonabeau, E., Agent-based modeling: Methods and techniques for simulating human systems, Proc. Natl. Acad. Sci.99 [2002] 7280-7287. |
| [14] | Bookstaber, R. and Kirman, A., Modeling a heterogeneous world, in Handbook of Computational Economics, Vol. 4 (Elsevier, 2018), pp. 769-795. |
| [15] | Bradford, S. C., Sources of information on specific subjects, Engineering137 [1934] 85-86. |
| [16] | Callon, M., Courtial, J.-P., Turner, W. A. and Bauin, S., From translations to problematic networks: An introduction to co-word analysis, Information (Int. Soc. Sci. Council)22 [1983] 191-235. |
| [17] | Cartwright, N., The Vanity of Rigour in Economics: Theoretical Models and Galilean Experiments (Cambridge University Press, 2007), p. 217-235. |
| [18] | Cecconi, F., Campenni, M., Andrighetto, G. and Conte, R., What do agent-based and equation-based modelling tell us about social conventions: The clash between ABM and EBM in a congestion game framework, J. Artif. Soc. Soc. Simul.13 [2010] 6. |
| [19] | Chen, S.-H. and Wang, S. G., Emergent complexity in agent-based computational economics, J. Econ. Surv.25 [2011] 527-546. |
| [20] | Cincotti, S., Raberto, M. and Teglio, A., Credit money and macroeconomic instability in the agent-based model and simulator EURACE, Econ.4 [2010] 1-32. |
| [21] | Colander, D., Föllmer, H., Haas, A., Goldberg, M., Juselius, K., Kirman, A., Lux, T. and Sloth, B., The financial crisis and the systemic failure of academic economics, in Lessons from the Financial Crisis (Citeseer, 2010), pp. 427-436. |
| [22] | Collins, A., Petty, M., Vernon-Bido, D. and Sherfey, S., A call to arms: Standards for agent-based modeling and simulation, J. Artif. Soc. Soc. Simul.18 [2015] 12. |
| [23] | Davis, J. B., Agent-based modelings open methodology approach: Simulation, reflexivity, and abduction, Econ. Hist. Method. Philos.8 [2018] 509-529. |
| [24] | Davis, J. B., Specialization, fragmentation, and pluralism in economics, The European J. Hist. Econ. Thought26 [2019] 271-293. |
| [25] | de Solla, P. D. J., Networks of scientific papers, Science149 [1965] 510-515. |
| [26] | Delli Gatti, D., Desiderio, S., Gaffeo, E., Cirillo, P. and Gallegati, M., Macroeconomics from the Bottom-Up, Vol. 1 (Springer Science & Business Media, 2011). · Zbl 1269.91001 |
| [27] | Dosi, G., Fagiolo, G., Napoletano, M. and Roventini, A., Income distribution, credit and fiscal policies in an agent-based Keynesian model, J. Econ. Dyn. Control37 [2013] 1598-1625. · Zbl 1327.91048 |
| [28] | Dosi, G., Fagiolo, G., Napoletano, M., Roventini, A. and Treibich, T., Fiscal and monetary policies in complex evolving economies, J. Econ. Dyn. Control52 [2015] 166-189. · Zbl 1402.91438 |
| [29] | Dosi, G., Fagiolo, G. and Roventini, A., Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles, J. Econ. Dyn. Control34 [2010] 1748-1767. · Zbl 1231.91324 |
| [30] | Ellegaard, O. and Wallin, J. A., The bibliometric analysis of scholarly production: How great is the impact?, Scientometrics105 [2015] 1809-1831. |
| [31] | Elsner, W., Complexity economics as heterodoxy: Theory and policy, J. Econ. Issues51 [2017] 939-978. |
| [32] | Epstein, J. M. and Axtell, R., Growing Artificial Societies: Social Science from the Bottom Up (Brookings Institution Press, 1996). |
| [33] | Fagiolo, G. and Roventini, A., Macroeconomic policy in DSGE and agent-based models redux: New developments and challenges ahead, J. Artif. Soc. Soc. Simul.20 [2017] 1-37. |
| [34] | Farmer, J. D. and Foley, D., The economy needs agent-based modelling, Nature460 [2009] 685-686. |
| [35] | Garibay, I., Gunaratne, C., Yousefi, N. and Scheinert, S., The agent-based model canvas: A modeling lingua franca for computational social science, in Social-Behavioral Modeling for Complex Systems (Wiley, 2019), pp. 521-544. |
| [36] | Gear, C., Eppel, E. and Koziol-Mclain, J., Advancing complexity theory as a qualitative research methodology, Int. J. Qual. Methods17 [2018] 1609406918782557. |
| [37] | Gilbert, N., Agent-Based social simulation: Dealing with complexity, The Complex Systems Network of Excellence9 [2004] 1-14. |
| [38] | Gilbert, N., Agent-Based Models, Vol. 153 (Sage Publications, 2008). |
| [39] | Girvan, M. and Newman, M. E., Community structure in social and biological networks, Proc. Natl. Acad. Sci.99 [2002] 7821-7826. · Zbl 1032.91716 |
| [40] | Grimm, V.et al., A standard protocol for describing individual-based and agent-based models, Ecol. Modell.198 [2006] 115-126. |
| [41] | Grimm, V., Berger, U., DeAngelis, D. L., Polhill, J. G., Giske, J. and Railsback, S. F., The ODD protocol: A review and first update, Ecol. Modell.221 [2010] 2760-2768. |
| [42] | Grimm, V., Polhill, G. and Touza, J., Documenting social simulation models: The ODD protocol as a standard, in Simulating Social Complexity (Springer, 2013), pp. 349-365. |
| [43] | Grimm, V.et al., The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism, J. Artif. Soc. Soc. Simul.23 [2020] 7-26. |
| [44] | Hauke, J., Achter, S. and Meyer, M., Theory development via replicated simulations and the added value of standards, J. Artif. Soc. Soc. Simul.23 [2020] 12-30. |
| [45] | Hauke, J., Lorscheid, I. and Meyer, M., Recent development of social simulation as reflected in JASSS between 2008 and 2014: A citation and co-citation analysis, J. Artif. Soc. Soc. Simul.20 [2017] 1-5. |
| [46] | Holland, J. H. and Miller, J. H., Artificial adaptive agents in economic theory, Am. Econ. Rev.81 [1991] 365-370. |
| [47] | Janssen, M. A., Pritchard, C. and Lee, A., On code sharing and model documentation of published individual and agent-based models, Environ. Modell. Softw.134 [2020] 104873. |
| [48] | Keynes, J. M., The General Theory of Employment, Interest, and Money (Macmillan, London, 1936). · Zbl 1407.91006 |
| [49] | Kirman, A., The economic crisis is a crisis for economic theory, CESifo Econ. Stud.56 [2010] 498-535. |
| [50] | Kirman, A. P., Whom or what does the representative individual represent?J. Econ. Perspect.6 [1992] 117-136. |
| [51] | Lazear, E. P., Economic imperialism, Quart. J. Econ.115 [2000] 99-146. · Zbl 0963.91511 |
| [52] | LeBaron, B. and Tesfatsion, L., Modeling macroeconomies as open-ended dynamic systems of interacting agents, Am. Econ. Rev.98 [2008] 246-250. |
| [53] | Matthews, R. B., Gilbert, N. G., Roach, A., Polhill, J. G. and Gotts, N. M., Agent-based land-use models: A review of applications, Landsc. Ecol.22 [2007] 1447-1459. |
| [54] | Mitchell, M., Complexity: A Guided Tour (Oxford University Press, 2009). · Zbl 1215.00003 |
| [55] | Müller, B., Bohn, F., Dreßler, G., Groeneveld, J., Klassert, C., Martin, R., Schlüter, M., Schulze, J., Weise, H. and Schwarz, N., Describing human decisions in agent-based models-ODD \(+\) D, an extension of the ODD protocol, Environ. Modell. Softw.48 [2013] 37-48. |
| [56] | Nelson, R. R. and Winter, S., An Evolutionary Theory of Economic Change (Harvard University Press, 1982). |
| [57] | Newman, M. E. J., Modularity and community structure in networks, Proc. Natl. Acad. Sci.103 [2006] 8577-8582. |
| [58] | Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J. and Deadman, P., Multi-agent systems for the simulation of land-use and land-cover change: A review, Ann. Assoc. Am. Geogr.93 [2003] 314-337. |
| [59] | Parunak, H. V. D., Savit, R. and Riolo, R. L., Agent-based modeling vs. equation-based modeling: A case study and users guide, in International Workshop on Multi-Agent Systems and Agent-Based Simulation (Springer, 1998), pp. 10-25. |
| [60] | Polhill, J. G., ODD updated, J. Artif. Soc. Soc. Simul.13 [2010] 9. |
| [61] | R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria (2020), https://www.R-project.org/. |
| [62] | Richiardi, M., Leombruni, R., Saam, N. J. and Sonnessa, M., A common protocol for agent-based social simulation, J. Artif. Soc. Soc. Simul.9 [2006] 15. |
| [63] | Schelling, T. C., Dynamic models of segregation, J. Math. Sociol.1 [1971] 143-186. · Zbl 1355.91061 |
| [64] | Schelling, T. C., Micromotives and Macrobehavior (WW Norton & Company, 1978). |
| [65] | Simon, H. A., A behavioral model of rational choice, Quart. J. Econ.69 [1955] 99-118. |
| [66] | Small, H., Co-citation in the scientific literature: A new measure of the relationship between two documents, J. Am. Soc. Inform. Sci.24 [1973] 265-269. |
| [67] | Squazzoni, F., The impact of agent-based models in the social sciences after 15 years of incursions, Hist. Econ. Ideas18 [2010] 197-233. |
| [68] | Squazzoni, F. and Casnici, N., Is social simulation a social science outstation? A bibliometric analysis of the impact of JASSS, J. Artif. Soc. Soc. Simul.16 [2013] 10. |
| [69] | Squazzoni, F., Jager, W. and Edmonds, B., Social simulation in the social sciences: A brief overview, Soc. Sci. Comput. Rev.32 [2014] 279-294. |
| [70] | Tesfatsion, L., Agent-based computational economics: Growing economies from the bottom up, Artif. Life8 [2002] 55-82. |
| [71] | Tesfatsion, L., Agent-based computational economics: A constructive approach to economic theory, in Handbook of Computational Economics, Vol. 2 (Elsevier, 2006), pp. 831-880. · Zbl 1143.91300 |
| [72] | Tesfatsion, L. and Judd, K. L., Handbook of Computational Economics: Agent-Based Computational Economics (Elsevier, 2006). · Zbl 1143.91300 |
| [73] | Wei, G., A bibliometric analysis of the top five economics journals during 2012-2016, J. Econ. Surv.33 [2019] 25-59. |
| [74] | White, H. D. and McCain, K. W., Visualizing a discipline: An author co-citation analysis of information science, 1972-1995, J. Am. Soc. Inform. Sci.49 [1998] 327-355. |
| [75] | Wilensky, U., Netlogo. Evanston, IL: Center for connected learning and computer-based modeling, Northwestern University (1999). |
| [76] | Windrum, P., Fagiolo, G. and Moneta, A., Empirical validation of agent-based models: Alternatives and prospects, J. Artif. Soc. Soc. Simul.10 [2007] 8. |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
