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

Author

Listed:
  • 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.

Suggested Citation

  • Theodore Tsekeris & Klimis Vogiatzoglou & Stelios Bekiros, 2011. "Multi-Regional Agent-Based Modeling of Household and Firm Location Choices with Endogenous Transport Costs," ERSA conference papers ersa10p479, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa10p479
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    References listed on IDEAS

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    Cited by:

    1. Mahyar Amirgholy & Hojjat Rezaeestakhruie & Hossain Poorzahedy, 2015. "Multi-objective cordon price design to control long run adverse traffic effects in large urban areas," Netnomics, Springer, vol. 16(1), pages 1-52, August.
    2. J. Raimbault & J. Broere & M. Somveille & J. M. Serna & E. Strombom & C. Moore & B. Zhu & L. Sugar, 2020. "A spatial agent based model for simulating and optimizing networked eco-industrial systems," Papers 2003.14133, arXiv.org.
    3. Andreas Deckert & Robert Klein, 2014. "Simulation-based optimization of an agent-based simulation," Netnomics, Springer, vol. 15(1), pages 33-56, July.
    4. repec:acf:journl:y::id:470 is not listed on IDEAS
    5. Victor Suslov & Tatyana Novikova & Alexander Tsyplakov, 2016. "Simulation of the Role of Government in Spatial Agent-Based Model," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 951-965.

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