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Computation and Complexity in Economic Behavior and Organization

Author

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  • Mount,Kenneth R.
  • Reiter,Stanley

Abstract

This book presents a model of computing and a measure of computational complexity which are intended to facilitate analysis of computations performed by people, machines, or a mixed system of people and machines. The model is designed to apply directly to models of economic theory, which typically involve continuous variables and smooth functions, without requiring analysis of approximations. The model permits analysis of the feasibility and complexity of the calculations required of economic agents in order for them to arrive at their decisions. The treatment contains applications of the model to game theory and economics, including comparison of the complexities of different solution concepts in certain bargaining games, and the trade-off between communication and computation in an example of an Edgeworth Box economy.

Suggested Citation

  • Mount,Kenneth R. & Reiter,Stanley, 2002. "Computation and Complexity in Economic Behavior and Organization," Cambridge Books, Cambridge University Press, number 9780521800563.
    • Handle: RePEc:cup:cbooks:9780521800563
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    Cited by:

    1. Mirowski, Philip, 2007. "Markets come to bits: Evolution, computation and markomata in economic science," Journal of Economic Behavior & Organization, Elsevier, vol. 63(2), pages 209-242, June.
    2. K. Vela Velupillai, 2007. "Taming the Incomputable, Reconstructing the Nonconstructive and Deciding the Undecidable in Mathematical Economics," Department of Economics Working Papers 0722, Department of Economics, University of Trento, Italia.
    3. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    4. Dingyu Zhang & Nadia Bhuiyan & Linghua Kong, 2018. "An Analysis of Organizational Structure in Process Variation," Organization Science, INFORMS, vol. 29(4), pages 722-738, August.
    5. Scott E. Page, 2008. "Uncertainty, Difficulty, and Complexity," Journal of Theoretical Politics, , vol. 20(2), pages 115-149, April.
    6. K. Vela Velupillai, 2007. "A Computable Economist�s Perspective on Computational Complexity," Department of Economics Working Papers 0723, Department of Economics, University of Trento, Italia.
    7. Mateos-Garcia, Juan, 2017. "To Err is Algorithm: Algorithmic fallibility and economic organisation," SocArXiv xuvf9, Center for Open Science.
    8. Ioannides, Yannis M., 2012. "Complexity and organizational architecture," Mathematical Social Sciences, Elsevier, vol. 64(2), pages 193-202.
    9. Kieron Meagher & Andrew Wait, 2008. "Who Decides about Change and Restructuring in Organizations?," CEPR Discussion Papers 587, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    10. Thijssen, J.J.J., 2003. "Investment under uncertainty, market evolution and coalition spillovers in a game theoretic perspective," Other publications TiSEM 672073a6-492e-4621-8d4a-0, Tilburg University, School of Economics and Management.
    11. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    12. Marschak, Thomas, 2006. "Organization Structure," MPRA Paper 81518, University Library of Munich, Germany.
    13. Mehmet Barlo & Nuh Aygün Dalkıran, 2022. "Computational implementation," Review of Economic Design, Springer;Society for Economic Design, vol. 26(4), pages 605-633, December.
    14. K. Vela Velupillai, 2012. "Taming The Incomputable, Reconstructing The Nonconstructive And Deciding The Undecidable In Mathematical Economics," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 5-51.
    15. K. Vela Velupillai, 2010. "The Algorithmic Revolution in the Social Sciences: Mathematical Economics, Game Theory and Statistical Inference," ASSRU Discussion Papers 1005, ASSRU - Algorithmic Social Science Research Unit.

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