Complex Systems in Finance and Econometrics

2011 Edition
| Editors: Robert A. Meyers (Editor-in-Chief)

Agent Based Models in Economics and Complexity

  • Mauro Gallegati
  • Matteo G. Richiardi
Reference work entry

Article Outline


Definition of the Subject


Some Limits of the Mainstream Approach

The Economics of Complexity

Additional Features of Agent-Based Models

An Ante Litteram Agent-Based Model: Thomas Schelling's Segregation Model

The Development of Agent-Based Modeling

A Recursive System Representation of Agent-Based Models

Analysis of Model Behavior

Validation and Estimation

The Role of Economic Policy

Future Directions



Price Vector Micro Model Artificial Data Mainstream Economic Dynamic Stochastic General Equilibrium 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.


  1. 1.
    Allen PM, Engelen G, Sanglier M (1986) Towards a general dynamic model of the spatial evolution of urban systems. In: Hutchinson B, Batty M (eds) Advances in urban systems modelling. North‐Holland, Amsterdam, pp 199–220Google Scholar
  2. 2.
    Anderson PW (1972) More is different. Science 177:4047Google Scholar
  3. 3.
    Anderson PW (1997) Some thoughts about distribution in economics. In: Arthur WB, Durlaf SN, Lane D (eds) The economy as an evolving complex system II. Addison‐Wesley, ReadingGoogle Scholar
  4. 4.
    Anderson PW, Arrow K, Pines D (eds) (1988) The economy as an evolving complex system. Addison‐Wesley, RedwoodGoogle Scholar
  5. 5.
    Aoki M (1996) New approaches to macroeconomic modelling: evolutionary stochastic dynamics, multiple equilibria, and externalities as field effects. Cambridge University Press, CambridgeGoogle Scholar
  6. 6.
    Aoki M (2002) Modeling aggregate behaviour and fluctuations in economics. Cambridge University Press, CambridgeGoogle Scholar
  7. 7.
    Aoki M, Yoshikawa H (2006) Reconstructing macroeconomics. Cambridge University Press, CambridgeGoogle Scholar
  8. 8.
    Aoki M, Yoshikawa H (2007) Non-self‐averaging in economic models. Economics Discussion Papers No. 2007-49, Kiel Institute for the World EconomyGoogle Scholar
  9. 9.
    Arrow KJ (1959) Towards a theory of price adjustment. In: Abramovits M (ed) Allocation of economic resources. Stanford University Press, StanfordGoogle Scholar
  10. 10.
    Arrow KJ (1963) Social choice and individual values, 2nd edn. Yale University Press, New HavenGoogle Scholar
  11. 11.
    Arrow KJ (1964) The role of securities in the optimal allocation of risk‐bearing. Rev Econ Stud 31:91–96Google Scholar
  12. 12.
    Arrow KJ (1971) A utilitarian approach to the concept of equality in public expenditures. Q J Econ 85(3):409–415Google Scholar
  13. 13.
    Arrow KJ (1994) Methodological individualism and social knowledge. Am Econ Rev 84:1–9Google Scholar
  14. 14.
    Arrow KJ, Debreu G (1954) Existence of an equilibrium for a competitive economy. Econometrica 22:265–290Google Scholar
  15. 15.
    Arthur WB (2000) Complexity and the economy. In: Colander D (ed) The complexity vision and the teaching of economics. Edward Elgar, NorthamptonGoogle Scholar
  16. 16.
    Arthur WB (2006) Out‐of‐equilibrium economics and agent-based modeling. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics, vol 2: Agent-Based Computational Economics, ch 32. North‐Holland, Amsterdam, pp 1551–1564Google Scholar
  17. 17.
    Arthur WB, Durlauf S, Lane D (eds) (1997) The economy as an evolving complex system II. Addison‐Wesley, ReadingGoogle Scholar
  18. 18.
    Askenazi M, Burkhart R, Langton C, Minar N (1996) The swarm simulation system: A toolkit for building multi-agent simulations. Santa Fe Institute, Working Paper, no. 96-06-042Google Scholar
  19. 19.
    Axelrod R (1997) Advancing the art of simulation in the social sciences. In: Conte R, Hegselmann R, Terna P (eds) Simulating social phenomena. Springer, Berlin, pp 21–40Google Scholar
  20. 20.
    Axtell RL (2000) Why agents? On the varied motivations for agent computing in the social sciences. Proceedings of the Workshop on Agent Simulation: Applications, Models and Tools. Argonne National Laboratory, ChicagoGoogle Scholar
  21. 21.
    Axtell RL (2001) Zipf distribution of US firm sizes. Science 293:1818–1820Google Scholar
  22. 22.
    Axtell RL, Gallegati M, Palestrini A (2006) Common components in firms' growth and the scaling puzzle. Available at SSRN:
  23. 23.
    Bak P (1997) How nature works. The science of self‐organized criticality. Oxford University Press, OxfordGoogle Scholar
  24. 24.
    Batten DF (2000) Discovering artificial economics. Westview Press, BoulderGoogle Scholar
  25. 25.
    Barone E (1908) Il ministro della produzione nello stato collettivista. G Econ 267–293, 391–414Google Scholar
  26. 26.
    Beinhocker ED (2006) The origin of wealth: Evolution, complexity, and the radical remaking of economics. Harvard Business School Press, CambridgeGoogle Scholar
  27. 27.
    Bénabou R (1996) Heterogeneity, stratification and growth: Macroeconomic implications of community structure and school finance. Am Econ Rev 86:584–609Google Scholar
  28. 28.
    Blanchard OJ, Kiyotaki N (1987) Monopolistic competition and the effects of aggregate demand. Am Econ Rew 77:647–666Google Scholar
  29. 29.
    Blume L, Durlauf S (eds) (2006) The economy as an evolving complex system, III. Current perspectives and future directions. Oxford University Press, OxfordGoogle Scholar
  30. 30.
    Blundell R, Stoker TM (2005) Heterogeneity and aggregation. J Econ Lit 43:347–391Google Scholar
  31. 31.
    Bowles S (1998) Endogenous preferences: The cultural consequences of markets and other economic institutions. J Econ Lit 36:75–111Google Scholar
  32. 32.
    Brock WA (1999) Scaling in economics: a reader's guide. Ind Corp Change 8(3):409–446Google Scholar
  33. 33.
    Brock WA, Colander D (2000) Complexity and policy. In: Colander D (ed) The complexity vision and the teaching of economics. Edward Elgar, NorthamptonGoogle Scholar
  34. 34.
    Brock WA, Durlauf SN (2001) Discrete choice with social interactions. Rev Econ Stud 68:235–260Google Scholar
  35. 35.
    Brock WA, Durlauf SN (2005) Social interactions and macroeconomics. UW‐Madison, SSRI Working Papers n.5Google Scholar
  36. 36.
    Caballero RJ (1992) A Fallacy of composition. Am Econ Rev 82:1279–1292Google Scholar
  37. 37.
    Calafati AG (2007) Milton Friedman's epistemology UPM working paper n.270Google Scholar
  38. 38.
    Caldarelli G (2006) Scale-free networks. Complex webs in nature and technology. Oxford University Press, OxfordGoogle Scholar
  39. 39.
    Clower RW (1965) The keynesian counterrevolution: A theoretical appraisal. In: Hahn F, Brechling F (eds) The theory of interst rates. Macmillan, LondonGoogle Scholar
  40. 40.
    Cohen A, Harcourt G (2003) What ever happened to the Cambridge capital theory controversies. J Econ Perspect 17:199–214Google Scholar
  41. 41.
    Cole HL, Mailath GJ, Postlewaite A (1992) Social norms, savings behaviour, and growth. J Political Econ 100(6):1092–1125Google Scholar
  42. 42.
    Cooper RW (1999) Coordination games: Complementarities and macroeconomics. Cambridge University Press, CambridgeGoogle Scholar
  43. 43.
    Crutchfield J (1994) Is anything ever new? Considering emergence. In: Cowan G, Pines D, Meltzer D (eds) Complexity: Metaphors, models, and reality. Addison‐Wesley, Reading, pp 515–537Google Scholar
  44. 44.
    Davis JB (2006) The turn in economics: Neoclassical dominance to mainstream pluralism? J Inst Econ 2(1):1–20Google Scholar
  45. 45.
    Debreu G (1959) The theory of value. Wiley, New YorkGoogle Scholar
  46. 46.
    Debreu G (1974) Excess demand functions. J Math Econ 1:15–23Google Scholar
  47. 47.
    De Masi G, Fujiwara Y, Gallegati M, Greenwald B, Stiglitz JE (2008) Empirical evidences of credit networks in Japan. mimeoGoogle Scholar
  48. 48.
    Delli Gatti D, Di Guilmi C, Gaffeo E, Gallegati M, Giulioni G, Palestrini A (2004) Business cycle fluctuations and firms' size distribution dynamics. Adv Complex Syst 7(2):1–18Google Scholar
  49. 49.
    Delli Gatti D, Di Guilmi C, Gaffeo E, Gallegati M, Giulioni G, Palestrini A (2005) A new approach to business fluctuations: Heterogeneous interacting agents, scaling laws and financial fragility. J Econ Behav Organ 56(4):489–512Google Scholar
  50. 50.
    Denzau AT, North DC (1994) Shared mental models: Ideologies and institutions. Kyklos 47(1):3–31Google Scholar
  51. 51.
    Descartes R (1637) Discours de la méthode pour bien conduire sa raison, et chercher la verité dans les sciences, tr. Discourse on Method and Meditations. The Liberal Arts Press, 1960, New YorkGoogle Scholar
  52. 52.
    Dorogovtsev SN, Mendes JFF (2003) Evolution of networks from biological nets to the internet and the WWW. Oxford University Press, OxfordGoogle Scholar
  53. 53.
    Di Guilmi C, Gallegati M, Landini S (2007) Economic dynamics with financial fragility and mean-field interaction: a model. arXiv:0709.2083Google Scholar
  54. 54.
    Durlauf SN (1993) Nonergodic economic growth. Rev Econ Stud 60:349–366Google Scholar
  55. 55.
    Durlauf SN (1997) What should policymakers know about economic complexity? Wash Q 21(1):157–165Google Scholar
  56. 56.
    Durlauf SN, Young HP (2001) Social dynamics. The MIT Press, CambridgeGoogle Scholar
  57. 57.
    Edgeworth FY (1925) The pure theory of monopoly In: Papers relating to political economy. McMillan, LondonGoogle Scholar
  58. 58.
    Epstein JM (1999) Agent-based computational models and generative social science. Complexity 4:41–60Google Scholar
  59. 59.
    Epstein JM (2006) Remarks on the foundations of agent-based generative social science. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics. Agent-based computational economics, vol 2, ch 34. North‐Holland, Amsterdam, pp 1585–1604Google Scholar
  60. 60.
    Epstein JM (2006) Generative social science: Studies in agent-based computational modeling. Princeton University Press, New YorkGoogle Scholar
  61. 61.
    Epstein JM, Axtell RL (1996) Growing artificial societies: Social science from the bottom up. The MIT Press, CambridgeGoogle Scholar
  62. 62.
    Fagiolo G, Moneta A, Windrum P (2007) A critical guide to empirical validation of agent-based models in economics: Methodologies, procedures, and open problems. Comput Econ 30:195–226Google Scholar
  63. 63.
    Farley R (1986) The residential segregation of blacks from whites: Trends, causes, and consequences. In: US Commission on Civil Rights, Issues in housing discrimination. US Commission on Civil RightsGoogle Scholar
  64. 64.
    Feller W (1957) An introduction to probability. Theory and its applications. Wiley, New YorkGoogle Scholar
  65. 65.
    Finch J, Orillard M (eds) (2005) Complexity and the economy: Implications for economy policy. Edward Elgar, CheltenhamGoogle Scholar
  66. 66.
    Flach PA, Kakas AC (eds) (2000) Abduction and induction. Essays on their relation and integration. Kluwer, DordrechtGoogle Scholar
  67. 67.
    Flake GW (1998) The computational beauty of nature. The MIT Press, CambridgeGoogle Scholar
  68. 68.
    Foellmer H (1974) Random economies with many interacting agents. J Math Econ 1:51–62Google Scholar
  69. 69.
    Forni M, Lippi M (1997) Aggregation and the micro‐foundations of microeconomics. Oxford University Press, OxfordGoogle Scholar
  70. 70.
    Frazer J (1995) An evolutionary architecture. Architectural Association Publications, LondonGoogle Scholar
  71. 71.
    Friedman M (1953) Essays in positive economics. University of Chicago Press, ChicagoGoogle Scholar
  72. 72.
    Fujiwara Y (2006) Proceedings of the 9th Joint Conference on Information Sciences (JCIS), Advances in Intelligent Systems Research Series. Available at
  73. 73.
    Gabaix X (2008) Power laws in Economics and Finance, 11 Sep 2008. Available at SSRN:
  74. 74.
    Gaffeo E, Gallegati M, Palestrini A (2003) On the size distribution of firms, additional evidence from the G7 countries. Phys A 324:117–123Google Scholar
  75. 75.
    Gaffeo E, Russo A, Catalano M, Gallegati M, Napoletano M (2007) Industrial dynamics, fiscal policy and R&D: Evidence from a computational experiment. J Econ Behav Organ 64:426–447Google Scholar
  76. 76.
    Gallegati M (1993) Composition effects and economic fluctuations. Econ Lett 44(1–2):123–126Google Scholar
  77. 77.
    Gallegati M, Delli Gatti D, Gaffeo E, Giulioni G, Palestrini A (2008) Emergent macroeconomics. Springer, BerlinGoogle Scholar
  78. 78.
    Gallegati M, Palestrini A, Delli Gatti D, Scalas E (2006) Aggregation of heterogeneous interacting agents: The variant representative agent framework. J Econ Interact Coord 1(1):5–19Google Scholar
  79. 79.
    Gilbert N (ed) (1999) Computer simulation in the social sciences, vol 42. Sage, Thousand OaksGoogle Scholar
  80. 80.
    Gilbert N, Terna P (2000) How to build and use agent-based models in social science. Mind Soc 1:57–72Google Scholar
  81. 81.
    Gilbert N, Troitzsch K (2005) Simulation for the social scientist. Open University Press, BuckinghamGoogle Scholar
  82. 82.
    Gintis H (2007) The dynamics of general equilibrium. Econ J 117:1280–1309Google Scholar
  83. 83.
    Glaeser E, Sacerdote B, Scheinkman J (1996) Crime and social interactions. Q J Econ 111:507–548Google Scholar
  84. 84.
    Glaeser J, Dixit J, Green DP (2002) Studying hate crime with the internet: What makes racists advocate racial violence? J Soc Issues 58(122):177–194Google Scholar
  85. 85.
    Gourieroux C, Monfort A (1997) Simulation‐based econometric methods. Oxford University Press, OxfordGoogle Scholar
  86. 86.
    Greenwald B, Stiglitz JE (1986) Externalities in economies with imperfect information and incomplete markets. Q J Econ 101(2):229–264Google Scholar
  87. 87.
    Grossman SJ, Stiglitz JE (1976) Information and competitive price systems. Am Econ Rev 66:246–253Google Scholar
  88. 88.
    Grossman SJ, Stiglitz JE (1980) On the impossibility of informationally efficient markets. Am Econ Rev 70(3):393–408Google Scholar
  89. 89.
    Guesnerie R (1993) Successes and failures in coordinating expectations. Eur Econ Rev 37:243–268Google Scholar
  90. 90.
    Hahn F (1982) Money and inflation. Blackwell, OxfordGoogle Scholar
  91. 91.
    Haken H (1983) Synergetics. Nonequilibrium phase transitions and social measurement, 3rd edn. Springer, BerlinGoogle Scholar
  92. 92.
    Hansen L, Heckman J (1996) The empirical foundations of calibration. J Econ Perspect 10:87–104Google Scholar
  93. 93.
    Hempel CV (1965) Aspects of scientific explanation. Free Press, LondonGoogle Scholar
  94. 94.
    Hempel CV, Oppenheim P (1948) Studies in the logic of explanation. Philos Sci 15:135–175Google Scholar
  95. 95.
    Hildenbrand W, Kirman AP (1988) Equilibrium analysis: Variations on the themes by edgeworth and walras. North‐Holland, AmsterdamGoogle Scholar
  96. 96.
    Horgan J (1995) From complexity to perplexity. Sci Am 272:104Google Scholar
  97. 97.
    Horgan J (1997) The end of science: Facing the limits of knowledge in the twilight of the scientific age. Broadway Books, New YorkGoogle Scholar
  98. 98.
    Jerison M (1984) Aggregation and pairwise aggregation of demand when the distribution of income is fixed. J Econ Theory 33(1):1–31Google Scholar
  99. 99.
    Kirman AP (1992) Whom or what does the representative individual represent. J Econ Perspect 6:117–136Google Scholar
  100. 100.
    Kirman AP (1996) Microfoundations – built on sand? A review of Maarten Janssen's microfoundations: A Critical Inquiry. J Econ Methodol 3(2):322–333Google Scholar
  101. 101.
    Kirman AP (2000) Interaction and markets. In: Gallegati M, Kirman AP (eds) Beyond the representative agent. Edward Elgar, CheltenhamGoogle Scholar
  102. 102.
    Kleijnen JPC (1998) Experimental design for sensitivity analysis, optimization, and validation of simulation models. In: Banks J (ed) Handbook of simulation. Wiley, New York, pp 173–223Google Scholar
  103. 103.
    Kleijnen JPC, Sargent RG (2000) A methodology for the fitting and validation of metamodels in simulation. Eur J Oper Res 120(1):14–29Google Scholar
  104. 104.
    Krugman P (1998) Bubble, boom, crash: theoretical notes on Asia's crisis. mimeoGoogle Scholar
  105. 105.
    Kydland FE, Prescott EC (1996) The computational experiment: An econometric tool. J Econ Perspect 10:69–85Google Scholar
  106. 106.
    Lavoie D (1989) Economic chaos or spontaneous order? Implications for political economy of the new view of science. Cato J 8:613–635Google Scholar
  107. 107.
    Leibenstein H (1950) Bandwagon, snob, and veblen effects in the theory of consumers' demand. Q J Econ 64:183–207Google Scholar
  108. 108.
    Leijonhufvud A (1973) Life among the econ. Econ Inq 11:327–337Google Scholar
  109. 109.
    Leombruni R (2002) The methodological status of agent-based simulations, LABORatorio Revelli. Working Paper No. 19Google Scholar
  110. 110.
    Leombruni R, Richiardi MG (2005) Why are economists sceptical about agent-based simulations? Phys A 355:103–109Google Scholar
  111. 111.
    Leombruni R, Richiardi MG, Saam NJ, Sonnessa M (2005) A common protocol for agent-based social simulation. J Artif Soc Simul 9:1Google Scholar
  112. 112.
    Levy M, Levy H, Solomon S (2000) Microscopic simulation of financial markets. In: From Investor Behavior to Market Phenomena. Academica Press, New YorkGoogle Scholar
  113. 113.
    Lewontin C, Levins R (2008) Biology under the influence: Dialectical essays on the coevolution of nature and society. Monthly Review Press, USGoogle Scholar
  114. 114.
    Lucas RE (1976) Econometric policy evaluation: A critique. Carnegie-Rochester Conference Series, vol 1, pp 19–46Google Scholar
  115. 115.
    Lucas RE (1987) Models of business cycles. Blackwell, New YorkGoogle Scholar
  116. 116.
    Lucas RE, Sargent T (1979) After keynesian macroeconomics. Fed Reserv Bank Minneap Q Rev 3(2):270–294Google Scholar
  117. 117.
    Magnani L, Belli E (2006) Agent-based abduction: Being rational through fallacies. In: Magnani L (ed) Model-based reasoning in science and engineering, Cognitive Science, Epistemology, Logic. College Publications, London, pp 415–439Google Scholar
  118. 118.
    Manski CF (2000) Economic analysis of social interactions. J Econ Perspect 14:115–136Google Scholar
  119. 119.
    Mantel R (1974) On the characterization of aggregate excess demand. J Econ Theory 7:348–353Google Scholar
  120. 120.
    Mantegna RN, Stanley HE (2000) An introduction to econophysics. Cambridge University Press, CambridgeGoogle Scholar
  121. 121.
    Marks RE (2007) Validating Simulation Models: A general framework and four applied examples. Comput Econ 30:265–290Google Scholar
  122. 122.
    May RM (1976) Simple mathematical models with very complicated dynamics. Nature 261:459–467Google Scholar
  123. 123.
    Mas‐Colell A, Whinston MD, Green J (1995) Microeconomic theory. Oxford University Press, OxfordGoogle Scholar
  124. 124.
    Miller JH, Page SE (2006) Complex adaptive systems: An introduction to computational models of social life. Princeton University Press, New YorkGoogle Scholar
  125. 125.
    Mirowski P (1989) More heat than light. Cambridge University Press, CambridgeGoogle Scholar
  126. 126.
    Muth RF (1986) The causes of housing segregation. US Commission on Civil Rights, Issues in Housing Discrimination. US Commission on Civil RightsGoogle Scholar
  127. 127.
    Nagel E (1961) The structure of science. Routledge and Paul Kegan, LondonGoogle Scholar
  128. 128.
    Nicolis G, Prigogine I (1989) Exploring complexity: An introduction. WH Freeman, New YorkGoogle Scholar
  129. 129.
    North MJ, Howe TR, Collier NT, Vos JR (2005) Repast simphony runtime system. In: Macal CM, North MJ, Sallach D (eds) Proceedings of the agent 2005 Conference on Generative Social Processes, Models, and Mechanisms, 13–15 Oct 2005Google Scholar
  130. 130.
    Ostrom T (1988) Computer simulation: the third symbol system. J Exp Soc Psycholog 24:381–392Google Scholar
  131. 131.
    Page S (1999) Computational models from A to Z. Complexity 5:35–41Google Scholar
  132. 132.
    Peirce CS (1955) Abduction and induction. In: J Buchler (ed) Philosophical writings of peirce. Dover, New YorkGoogle Scholar
  133. 133.
    Phelan S (2001) What is complexity science, really? Emergence 3:120–136Google Scholar
  134. 134.
    Pollack R (1975) Interdependent preferences. Am Econ Rev 66:309–320Google Scholar
  135. 135.
    Railsback SF, Lytinen SL, Jackson SK (2006) Agent-based simulation platforms: Review and development recommendations. Simulation 82:609–623Google Scholar
  136. 136.
    Rappaport S (1996) Abstraction and unrealistic assumptions in economics. J Econ Methodol 3(2):215–36Google Scholar
  137. 137.
    Resnick M (1994) Turtles, termites and traffic jams: Explorations in massively parallel microworlds. MIT, CambidgeGoogle Scholar
  138. 138.
    Richter MK, Wong K (1999) Non‐computability of competitive equilibrium. Econ Theory 14:1–28Google Scholar
  139. 139.
    Rioss Rull V (1995) Models with heterogeneous agents. In: Cooley TF (ed) Frontiers of business cycle research. Princeton University Press, New YorkGoogle Scholar
  140. 140.
    Rosser JB (1999) On the complexities of complex economic dynamics. J Econ Perspect 13:169–192Google Scholar
  141. 141.
    Rosser JB (2000) Integrating the complexity vision into the teaching of mathematical economics. In: Colander D (ed) The complexity vision and the teaching of economics. Edward Elgar, Cheltenham, pp 209–230Google Scholar
  142. 142.
    Rosser JB (2003) Complexity in economics. Edward Elgar, CheltenhamGoogle Scholar
  143. 143.
    Rust J (1997) Using randomization to break the curse of dimensionality. Econometrica 65:487–516Google Scholar
  144. 144.
    Saari DG (1995) Mathematical complexity of simple economics. Notices Am Math Soc 42:222–230Google Scholar
  145. 145.
    Schelling TC (1969) Models of segregation. Am Econ Rev 59:488–493Google Scholar
  146. 146.
    Schelling TC (1971) Dynamic models of segregration. J Math Sociol 1:143–186Google Scholar
  147. 147.
    Schelling TC (1978) Micromotives and macrobehaviour. W.W. Norton, New YorkGoogle Scholar
  148. 148.
    Schelling TC (2006) Some fun, thirty‐five years ago. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics. Agent-based computational economics, vol 2, ch 37. North‐Holland, Amsterdam, pp 1639–1644Google Scholar
  149. 149.
    Schumpeter JA (1960) History of economic analysis. Oxford University Press, OxfordGoogle Scholar
  150. 150.
    Segre‐Tossani L, Smith LM (2003) Advanced modeling, visualization, and data mining techniques for a new risk landscape. Casualty Actuarial Society, Arlington, pp 83–97Google Scholar
  151. 151.
    Semmler W (2005) Introduction (multiple equilibria). J Econ Behav Organ 57:381–389Google Scholar
  152. 152.
    Shy O (2001) The economics of network industries. Cambridge University Press, CambridgeGoogle Scholar
  153. 153.
    Smith A (1776/1937) The wealth of nations. Random House, New YorkGoogle Scholar
  154. 154.
    Solomon S (2007) Complexity roadmap. Institute for Scientific Interchange, TorinoGoogle Scholar
  155. 155.
    Sonnenschein H (1972) Market excess demand functions. Econometrica 40:549–563Google Scholar
  156. 156.
    Stiglitz JE (1992) Methodological issues and the new keynesian economics. In: Vercelli A, Dimitri N (eds) Macroeconomics: A survey of research strategies. Oxford University Press, Oxford, pp 38–86Google Scholar
  157. 157.
    Stiglitz JE (2002) Globalization and its discontents. Northon, New YorkGoogle Scholar
  158. 158.
    Stoker T (1995) Empirical approaches to the problem of aggregation over individuals. J Econ Lit 31:1827–1874Google Scholar
  159. 159.
    Tesfatsion L (ed) (2001) Special issue on agent-based computational economics. J Econ Dyn Control 25Google Scholar
  160. 160.
    Tesfatsion L (ed) (2001) Special issue on agent-based computational economics. Comput Econ 18Google Scholar
  161. 161.
    Tesfatsion L (2001) Agent-based computational economics: A brief guide to the literature. In: Michie J (ed) Reader's guide to the social sciences. Fitzroy‐Dearborn, LondonGoogle Scholar
  162. 162.
    Tesfatsion L (2002) Agent-based computational economics: Growing economies from the bottom up. Artif Life 8:55–82Google Scholar
  163. 163.
    Tesfatsion L (2006) Agent-based computational economics: A constructive approach to economic theory. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics. Agent-based computational economics, vol 2, ch 16. North‐Holland, Amsterdam, pp 831–880Google Scholar
  164. 164.
    Troitzsch KG (2004) Validating simulation models. In: Horton G (ed) Proceedings of the 18th european simulation multiconference. Networked simulations and simulation networks. SCS Publishing House, Erlangen, pp 265–270Google Scholar
  165. 165.
    Vriend NJ (1994) A new perspective on decentralized trade. Econ Appl 46(4):5–22Google Scholar
  166. 166.
    Vriend NJ (2002) Was Hayek an ace? South Econ J 68:811–840Google Scholar
  167. 167.
    Velupillai KV (2000) Computable economics. Oxford University Press, OxfordGoogle Scholar
  168. 168.
    Velupillai KV (2002) Effectivity and constructivity in economic theory. J Econ Behav Organ 49:307–325Google Scholar
  169. 169.
    Velupillai KV (2005) The foundations of computable general equilibrium theory. In: Department of Economics Working Papers No 13. University of TrentoGoogle Scholar
  170. 170.
    Velupillai KV (2007) The impossibility of an effective theory of policy in a complex economy. In: Salzano M, Colander D (eds) Complexity hints for economic policy. Springer, MilanGoogle Scholar
  171. 171.
    von Hayek FA (1948) Individualism and economic order. University of Chicago Press, ChicagoGoogle Scholar
  172. 172.
    von Mises L (1949) Human action: A treatise on economics. Yale University Press, YaleGoogle Scholar
  173. 173.
    Wilensky U (1998) NetLogo segregation model. Center for connected learning and computer‐based modeling. Northwestern University, Evanston.
  174. 174.
    Winker P, Gilli M, Jeleskovic V (2007) An objective function for simulation based inference on exchange rate data. J Econ Interact Coord 2:125–145Google Scholar
  175. 175.
    Wooldridge M (2001) An introduction to multiagent systems. Wiley, New YorkGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Mauro Gallegati
    • 1
  • Matteo G. Richiardi
    • 1
    • 2
  1. 1.Università Politecnica delle MarcheAnconaItaly
  2. 2.Collegio Carlo Alberto – LABORatorio R. RevelliMoncalieriItaly