COMPLEX SYSTEMS AND MULTI-AGENT BASED MODELS: TOOLS FOR STUDYING THE DYNAMICS OF URBAN ECONOMIC

Authors

  • Diego Silva Ardila Economista e Historiador de la Universidad de los Andes con maestría en Economía de la Universidad de los Andes y Maestría en Análisis de Problemas Políticos, Económicos e Internacionales Contemporáneos de la Universidad Externado de Colombia. Candidato a Doctor en Urban Planning and Policy de la Universidad de Illinois en Chicago. Profesor e investigador de la escuela de Economía de la Universidad Industrial de Santander, Bucaramanga, Colombia.

DOI:

https://doi.org/10.15332/rl.v0i3.48

Keywords:

Complex systems, multi-agent based models, networks, informality, urban land markets

Abstract

In recent years, there has been an interesting academic debate about possibilities that complex systems and multi-agent based models provide to study social processes and economic dynamics. The article presents this new theoretical framework and some of its methodological tools through the discussion of two preliminary research: the first explores the existence of networks in the Latin American urban system and the other one refers to a market research of the land at urban peripheries, which emphasizes on the incidence of informality in land use and spatial distribution of prices. The possibility of extending to models and future applications by using this new approach is discussed at the end of the document and it also invites contemporary economic analysts to use such kind of tools.

Downloads

Download data is not yet available.

References

Amaral y Ottino (2004). Complex networks: Augmenting the framework for the study of complex systems. The European Physical Journal B. 38, 147–162

Axelrod, R., & Cohen, M. D. (2001). Harnessing Complexity: Organizational Implications of a Scientific Frontier [Paperback] (p. 208). Basic Books.

Axtell, R. L., Epstein, J. M., Dean, J. S., Gumerman, G. J., Swedlund, A. C., Harburger, J., Chakravarty, S., et al. (2002). Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences of the United States of America, 99 Suppl 3(1), 7275-9. doi:10.1073/pnas.092080799

Batty, M. (1997). Cellular automata and urban form: a primer. Journal of the American Planning Association.

Batty, Michael. (2008). The size, scale, and shape of cities. Science (New York, N.Y.), 319(5864), 769-71. doi:10.1126/science.1151419

Beaverstock, J. , Smith, R. , Taylor, P. , Walker, D. R. , & Lorimer, H. (2000). Globalization and world cities: some measurement methodologies. Applied Geography, 20(1), 43-63. doi:10.1016/S0143-6228(99)00016-8

Beckmann, M. (1958). City hierarchies and the distribution of city size. Economic Development and Cultural Change, 6(3), 243-248. Retrieved from http://www.jstor.org/stable/10.2307/1151689

Clifton, K., Ewing, R., Knaap, G., & Song, Y. (2008). Quantitative analysis of urban form: a multidisciplinary review. Journal of Urbanism: International Research on Placemaking and Urban Sustainability, 1(1), 17-45.

Coelho, D., & Ruth, M. (2006). Seeking a unified urban systems theory. The Sustainable City IV: Urban Regeneration and Sustainability, 1, 179-188. Southampton, UK: WIT Press.

Ewing, R. (1997). Is Los Angeles-style sprawl desirable? Journal of the American Planning Association.

Ewing, Reid, & Pendall, R. (n.d.). Measuring sprawl and its impact. 2002. Smart Growth America.

Gastner, M. T., & Newman, M. E. J. (2006). Shape and efficiency in spatial distribution networks. Journal of Statistical Mechanics: Theory and Experiment, 2006(January),

Kogut, B. (2001). The small world of Germany and the durability of national networks. American Sociological Review, 66(3), 317-335.

Marshall, J. D. (2007). Urban Land Area and Population Growth: A New Scaling Relationship for Metropolitan Expansion. Urban Studies, 44(10), 1889-1904.

Mcdonald, J. F. (1989). Econometric studies of urban population density: a survey. Journal of urban economics, 26, 361-85.

Miller, J. H., & Page, S. E. (2007). Complex Adaptive Systems: An Introduction to Computational Models of Social Life (p. 284). Princeton University Press.

Resnick, M. (1997). Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds (p. 183). A Bradford Book.

Sassen, S. (2002). Locating cities on global circuits. Environment and urbanization, (2002), 1-18. Retrieved from http://eau.sagepub.com/content/14/1/13.short

Taylor, P J, Catalano, G., & Walker, D. R. F. (2002). Measurement of the World City Network. Urban Studies, 39(13), 2367-2376.

Taylor, Peter J. (1997). Hierarchical tendencies amongst world cities: a global research proposal. Cities, 14(6), 323-332.

Tesfatsion, L. (Editor), & Judd, K. L. (Editor). (2006). Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics (p. 904). North Holland; 1 edition.

Wu, F. (2007). Book Review: Cities and complexity: understanding cities with celular automata, agent-based models, and fractals. Progress in Human Geography, 31(1), 113-115.

Zellner, M. (2012) Planificación urbana y complejidad. El potencial de los modelos multiagentes. Borrador en proceso de publicación.

Published

2011-01-01

How to Cite

Silva Ardila, D. (2011). COMPLEX SYSTEMS AND MULTI-AGENT BASED MODELS: TOOLS FOR STUDYING THE DYNAMICS OF URBAN ECONOMIC. Lebret, (3), 117–136. https://doi.org/10.15332/rl.v0i3.48

Issue

Section

Articles