Endogenous matching functions: An agent-based computational approach
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DOI: 10.1142/S0219525904000147
Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/146279/
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Other versions of this item:
- Michael Neugart, 2004. "Endogenous Matching Functions: An Agent-Based Computational Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 187-201.
- M. Neugart, 2004. "Endogenous Matching Functions: An Agent-Based Computational Approach," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 6, pages 90-106, World Scientific Publishing Co. Pte. Ltd..
- Neugart, Michael, 2004. "Endogenous matching functions: an agent-based computational approach," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57291, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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JEL classification:
- B21 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Microeconomics
- B22 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Macroeconomics
- G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
- D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights
- O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CMP-2024-08-19 (Computational Economics)
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