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Multi-Regional Agent-Based Modeling of Household and Firm Location Choices with Endogenous Transport Costs

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  • Theodore Tsekeris

    ()

  • Klimis Vogiatzoglou
  • Stelios Bekiros

Abstract

The paper describes a spatial economic agent-based model (ABM), consistent with the principles of new economic geography (NEG), which allows the discrete-time evolutionary simulation of complex interactions of household and firm location choices. In contrast with the current ABM approaches, it considers a multi-regional (multi-urban) setting to enable a more realistic representation of decisions related to commuting, migration and household and employment location. The model allows simulating spatially differentiated, multi-commodity markets for land and labor in a system of cities and the behavior of profit-maximizing firms with multi-regional asset investment decisions, incorporating endogenous intra- and inter-urban transport costs with congestion effects. It also accounts for the impact of industrial and urban agglomeration forces on location choices and the formation of urban development patterns. Other features include the representation of the actions of central and local government agents to address issues of territorial development, efficiency and equity. The simulation set-up and evolutionary analysis of the spatial ABM are presented and several implications are discussed with regard to the possible outcomes of a set of policy interventions.

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Bibliographic Info

Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa10p479.

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Date of creation: Sep 2011
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Handle: RePEc:wiw:wiwrsa:ersa10p479

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  1. Luis E Fernandez & Daniel G Brown & Robert W Marans & Joan I Nassauer, 2005. "Characterizing location preferences in an exurban population: implications for agent-based modeling," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 32(6), pages 799-820, November.
  2. Markose, Sheri & Alentorn, Amadeo & Koesrindartoto, Deddy & Allen, Peter & Blythe, Phil & Grosso, Sergio, 2007. "A smart market for passenger road transport (SMPRT) congestion: An application of computational mechanism design," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 2001-2032, June.
  3. Eric J Heikkila & Yiming Wang, 2009. "Fujita and Ogawa revisited: an agent-based modeling approach," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 36(4), pages 741-756, July.
  4. Wei Fan & Frederick Treyz & George Treyz, 2000. "An Evolutionary New Economic Geography Model," Journal of Regional Science, Wiley Blackwell, vol. 40(4), pages 671-695.
  5. Oswald T J Devisch & Harry J P Timmermans & Theo A Arentze & Aloys W J Borgers, 2009. "An agent-based model of residential choice dynamics in nonstationary housing markets," Environment and Planning A, Pion Ltd, London, vol. 41(8), pages 1997-2013, August.
  6. Abdel-Rahman, Hesham M. & Anas, Alex, 2003. "Theories of system of cities," Working Papers 2003-08, University of New Orleans, Department of Economics and Finance.
  7. Mun, Se-il, 1997. "Transport Network and System of Cities," Journal of Urban Economics, Elsevier, vol. 42(2), pages 205-221, September.
  8. Roorda, Matthew J. & Cavalcante, Rinaldo & McCabe, Stephanie & Kwan, Helen, 2010. "A conceptual framework for agent-based modelling of logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 18-31, January.
  9. Takama, Takeshi & Preston, John, 2008. "Forecasting the effects of road user charge by stochastic agent-based modelling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 738-749, May.
  10. Anas, Alex & Xu, Rong, 1999. "Congestion, Land Use, and Job Dispersion: A General Equilibrium Model," Journal of Urban Economics, Elsevier, vol. 45(3), pages 451-473, May.
  11. Tabuchi, Takatoshi & Thisse, Jacques-Fran├žois & Zeng, Dao-Zhi, 2002. "On the Number and Size of Cities," CEPR Discussion Papers 3386, C.E.P.R. Discussion Papers.
  12. Liedtke, Gernot, 2009. "Principles of micro-behavior commodity transport modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(5), pages 795-809, September.
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