IDEAS home Printed from https://ideas.repec.org/p/gro/rugsom/99b41.html
   My bibliography  Save this paper

Governance and matching

Author

Listed:
  • Klos, Tomas B.

    (Groningen University)

Abstract

We investigate the impact of advertising in a simple static differentiated duopoly model. First, we consider the Nash equilibrium of the situation in which the duopolistic firms compete simultaneously with two instruments, i.e. the prices and the advertising expenditures. Second, we examine the Nash equilibrium of the situa-tion in which the firms only compete in prices and do not advertise at all. Next, we compare the two different Nash equilibria in order to assess the impact of advertising. In particular, we characterize in terms of the model parameters the circumstances in which the profits, outputs and/or prices of each firm are greater (smaller) in the Nash equilibrium with advertising than in the Nash equilibrium without advertising. We show that the results depend on (a) the size of the (positive) effect of advertising of a firm on its own demand, (b) the size and nature (stimulating or adverse) of the cross-effect of the advertising of each firm on the demand of the other firm, and (c) the size of the autonomous demand of the firms.

Suggested Citation

  • Klos, Tomas B., 1999. "Governance and matching," Research Report 99B41, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  • Handle: RePEc:gro:rugsom:99b41
    as

    Download full text from publisher

    File URL: http://irs.ub.rug.nl/ppn/18820959X
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Tesfatsion, Leigh, 1995. "A Trade Network Game with Endogenous Partner Selection," ISU General Staff Papers 199505010700001034, Iowa State University, Department of Economics.
    2. Arthur, W Brian, 1993. "On Designing Economic Agents That Behave Like Human Agents," Journal of Evolutionary Economics, Springer, vol. 3(1), pages 1-22, February.
    3. Tomas Klos, "undated". "Decentralized Interaction and Co-adaptation in the Repeated Prisoner's Dilemma," Computing in Economics and Finance 1997 88, Society for Computational Economics.
    4. Williamson, Oliver E, 1979. "Transaction-Cost Economics: The Governance of Contractural Relations," Journal of Law and Economics, University of Chicago Press, vol. 22(2), pages 233-261, October.
    5. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
    6. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    7. Weisbuch, Gerard & Kirman, Alan & Herreiner, Dorothea, 2000. "Market Organisation and Trading Relationships," Economic Journal, Royal Economic Society, vol. 110(463), pages 411-436, April.
    8. Edmund Chattoe-Brown, 1998. "Just How (Un)realistic Are Evolutionary Algorithms As Representations of Social Processes?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(3), pages 1-2.
    9. Stanley, E. Ann & Ashlock, Dan & Tesfatsion, Leigh, 1993. "Iterated Prisoner's Dilemma with Choice and Refusal of Partners," ISU General Staff Papers 199302010800001028, Iowa State University, Department of Economics.
    10. Nicolaas J. Vriend, 1996. "A model of market-making," Economics Working Papers 184, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Arthur, W Brian, 1991. "Designing Economic Agents that Act Like Human Agents: A Behavioral Approach to Bounded Rationality," American Economic Review, American Economic Association, vol. 81(2), pages 353-359, May.
    12. Ronald H. Coase, 2000. "The new institutional economics," Chapters, in: Claude Ménard (ed.), Institutions, Contracts and Organizations, chapter 1, Edward Elgar Publishing.
    13. Lane, David A, 1993. "Artificial Worlds and Economics, Part I," Journal of Evolutionary Economics, Springer, vol. 3(2), pages 89-107, May.
    14. Roth, Alvin E. & Sotomayor, Marilda, 1992. "Two-sided matching," Handbook of Game Theory with Economic Applications, in: R.J. Aumann & S. Hart (ed.), Handbook of Game Theory with Economic Applications, edition 1, volume 1, chapter 16, pages 485-541, Elsevier.
    15. Thomas Riechmann, 1999. "Learning and behavioral stability An economic interpretation of genetic algorithms," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 225-242.
    16. Leigh Tesfatsion, 1999. "Market Power Effects on Worker-Employer Network Formation in Evolutionary Labor Markets with Adaptive Search," Computing in Economics and Finance 1999 543, Society for Computational Economics.
    17. Thomas Brenner, 1998. "Can evolutionary algorithms describe learning processes?," Journal of Evolutionary Economics, Springer, vol. 8(3), pages 271-283.
    18. Vriend, Nicolaas J, 1995. "Self-Organization of Markets: An Example of a Computational Approach," Computational Economics, Springer;Society for Computational Economics, vol. 8(3), pages 205-231, August.
    19. Albin, Peter & Foley, Duncan K., 1992. "Decentralized, dispersed exchange without an auctioneer : A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 18(1), pages 27-51, June.
    20. Williamson, Oliver E, 1981. "The Modern Corporation: Origins, Evolution, Attributes," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1537-1568, December.
    21. ANDERSON, Simon P. & de PALMA, André & THISSE, Jacques-François, 1992. "Interpretations of the logit discrete choice models and the theory of product differentiation," LIDAM Reprints CORE 1017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    23. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-371, May.
    24. Lane, David A, 1993. "Artificial Worlds and Economics, Part II," Journal of Evolutionary Economics, Springer, vol. 3(3), pages 177-197, August.
    25. Miller, John H., 1996. "The coevolution of automata in the repeated Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 87-112, January.
    26. Kollman, Ken & Miller, John H. & Page, Scott E., 1992. "Adaptive Parties in Spatial Elections," American Political Science Review, Cambridge University Press, vol. 86(4), pages 929-937, December.
    27. Miller, J. H. & Stadler, P. F., 1998. "The dynamics of locally adaptive parties under spatial voting," Journal of Economic Dynamics and Control, Elsevier, vol. 23(2), pages 171-189, September.
    28. Robert Axtell, 1999. "The Emergence of Firms in a Population of Agents," Working Papers 99-03-019, Santa Fe Institute.
    29. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Klos, Tomas B. & Nooteboom, Bart, 2001. "Agent-based computational transaction cost economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 503-526, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:dgr:rugsom:99b41 is not listed on IDEAS
    2. Tesfatsion, Leigh, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," ISU General Staff Papers 199807010700001043, Iowa State University, Department of Economics.
    3. Klos, Tomas B. & Nooteboom, Bart, 2001. "Agent-based computational transaction cost economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 503-526, March.
    4. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics.
    5. Tesfatsion, Leigh, 1998. "Gale-Shapley Matching in an Evolutionary Trade Network Game," ISU General Staff Papers 199804010800001041, Iowa State University, Department of Economics.
    6. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    7. Leigh S. Tesfatsion, "undated". "An Evolutionary Trade Network Game with Preferential Partner Selection," Computing in Economics and Finance 1996 _057, Society for Computational Economics.
    8. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    9. Tesfatsion, Leigh, 1995. "A Trade Network Game with Endogenous Partner Selection," ISU General Staff Papers 199505010700001034, Iowa State University, Department of Economics.
    10. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    11. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
    12. Tomas B. Klos, 1999. "Decentralized Interaction and Co-Adaptation in the Repeated Prisoner&2018;s Dilemma," Computational and Mathematical Organization Theory, Springer, vol. 5(2), pages 147-165, July.
    13. Sieg, Gernot, 2001. "A political business cycle with boundedly rational agents," European Journal of Political Economy, Elsevier, vol. 17(1), pages 39-52, March.
    14. Denis Phan & Stephane Pajot & Jean-Pierre Nadal, 2003. "The Monopolist's Market with Discrete Choices and Network Externality Revisited: Small-Worlds, Phase Transition and Avalanches in an ACE Framework," Computing in Economics and Finance 2003 150, Society for Computational Economics.
    15. Alexander Gorobets & Bart Nooteboom, 2006. "Adaptive Build-up and Breakdown of Trust: An Agent Based Computational Approach," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 10(3), pages 277-306, September.
    16. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    17. Tony Curson Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Levine's Working Paper Archive 588, David K. Levine.
    18. Paola Tubaro, 2011. "Computational Economics," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 10, Edward Elgar Publishing.
    19. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    20. Shu-Heng Chen & Bin-Tzong Chie & Ying-Fang Kao & Ragupathy Venkatachalam, 2019. "Agent-Based Modeling of a Non-tâtonnement Process for the Scarf Economy: The Role of Learning," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 305-341, June.
    21. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gro:rugsom:99b41. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/ferugnl.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Hanneke Tamling (email available below). General contact details of provider: https://edirc.repec.org/data/ferugnl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.