IDEAS home Printed from https://ideas.repec.org/a/spr/dyngam/v8y2018i4d10.1007_s13235-017-0234-6.html
   My bibliography  Save this article

An Evolutionary Analysis of Growth and Fluctuations with Negative Externalities

Author

Listed:
  • Anindya S. Chakrabarti

    (Indian Institute of Management Ahmedabad)

  • Ratul Lahkar

    (Indian Institute of Management Udaipur)

Abstract

We present an evolutionary game theoretic model of growth and fluctuations with negative externalities. Agents in a population choose the level of input. Total output is a function of aggregate input and a productivity parameter. The model, which is equivalent to a tragedy of the commons, constitutes an aggregative potential game with negative externalities. Aggregate input at the Nash equilibrium is inefficiently high causing aggregate payoff to be suboptimally low. Simulations with the logit dynamic reveal that while the aggregate input increases monotonically from an initial low level, aggregate payoff may decline from the corresponding high level. Hence, a positive technology shock causes a rapid initial increase in aggregate payoff, which is unsustainable as agents increase aggregate input to the inefficient equilibrium level. Aggregate payoff, therefore, declines subsequently. A sequence of exogenous shocks, therefore, generates a sustained pattern of growth and fluctuations in aggregate payoff.

Suggested Citation

  • Anindya S. Chakrabarti & Ratul Lahkar, 2018. "An Evolutionary Analysis of Growth and Fluctuations with Negative Externalities," Dynamic Games and Applications, Springer, vol. 8(4), pages 733-760, December.
  • Handle: RePEc:spr:dyngam:v:8:y:2018:i:4:d:10.1007_s13235-017-0234-6
    DOI: 10.1007/s13235-017-0234-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13235-017-0234-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13235-017-0234-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    3. William H. Sandholm, 2002. "Evolutionary Implementation and Congestion Pricing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(3), pages 667-689.
    4. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    5. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    6. Gerard Hoberg & Gordon Phillips, 2010. "Real and Financial Industry Booms and Busts," Journal of Finance, American Finance Association, vol. 65(1), pages 45-86, February.
    7. Hofbauer, Josef & Sandholm, William H., 2007. "Evolution in games with randomly disturbed payoffs," Journal of Economic Theory, Elsevier, vol. 132(1), pages 47-69, January.
    8. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5.
    9. Josef Hofbauer & William H. Sandholm, 2002. "On the Global Convergence of Stochastic Fictitious Play," Econometrica, Econometric Society, vol. 70(6), pages 2265-2294, November.
    10. Sandholm, William H., 2001. "Potential Games with Continuous Player Sets," Journal of Economic Theory, Elsevier, vol. 97(1), pages 81-108, March.
    11. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
    12. Friedman, James W, 1973. "Concavity of Production Functions and Non-Increasing Returns to Scale," Econometrica, Econometric Society, vol. 41(5), pages 981-984, September.
    13. Chakrabarti, Anindya S. & Lahkar, Ratul, 2017. "Productivity dispersion and output fluctuations: An evolutionary model," Journal of Economic Behavior & Organization, Elsevier, vol. 137(C), pages 339-360.
    14. Lahkar, Ratul & Sandholm, William H., 2008. "The projection dynamic and the geometry of population games," Games and Economic Behavior, Elsevier, vol. 64(2), pages 565-590, November.
    15. Ratul Lahkar, 2017. "Large Population Aggregative Potential Games," Dynamic Games and Applications, Springer, vol. 7(3), pages 443-467, September.
    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. Sarvesh Bandhu & Ratul Lahkar, 2022. "A Large Population Approach to Implementing Efficiency with Minimum Inequality," Working Papers 76, Ashoka University, Department of Economics.
    2. Jonathan Newton, 2018. "Evolutionary Game Theory: A Renaissance," Games, MDPI, vol. 9(2), pages 1-67, May.
    3. Luis C. Corchón, 2021. "Aggregative games," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(1), pages 49-71, 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. Sandholm,W.H., 2003. "Excess payoff dynamics, potential dynamics, and stable games," Working papers 5, Wisconsin Madison - Social Systems.
    2. Mertikopoulos, Panayotis & Sandholm, William H., 2018. "Riemannian game dynamics," Journal of Economic Theory, Elsevier, vol. 177(C), pages 315-364.
    3. Sandholm, William H., 2015. "Population Games and Deterministic Evolutionary Dynamics," Handbook of Game Theory with Economic Applications,, Elsevier.
    4. Sandholm,W.H., 2002. "Potential dynamics and stable games," Working papers 21, Wisconsin Madison - Social Systems.
    5. Cominetti, Roberto & Melo, Emerson & Sorin, Sylvain, 2010. "A payoff-based learning procedure and its application to traffic games," Games and Economic Behavior, Elsevier, vol. 70(1), pages 71-83, September.
    6. Lahkar, Ratul & Mukherjee, Sayan & Roy, Souvik, 2022. "Generalized perturbed best response dynamics with a continuum of strategies," Journal of Economic Theory, Elsevier, vol. 200(C).
    7. Ratul Lahkar, 2017. "Large Population Aggregative Potential Games," Dynamic Games and Applications, Springer, vol. 7(3), pages 443-467, September.
    8. Jakub Bielawski & Thiparat Chotibut & Fryderyk Falniowski & Michal Misiurewicz & Georgios Piliouras, 2022. "Unpredictable dynamics in congestion games: memory loss can prevent chaos," Papers 2201.10992, arXiv.org, revised Jan 2022.
    9. RatulLahkar & Sayan Mukherjee & Souvik Roy, 2021. "Generalized Perturbed Best Response Dynamics with a Continuum of Strategies," Working Papers 51, Ashoka University, Department of Economics.
    10. Kets, W., 2007. "The Minority Game : An Economics Perspective," Other publications TiSEM 65d52a6a-b27d-45a9-93a7-e, Tilburg University, School of Economics and Management.
    11. Kets, W., 2008. "Networks and learning in game theory," Other publications TiSEM 7713fce1-3131-498c-8c6f-3, Tilburg University, School of Economics and Management.
    12. Panayotis Mertikopoulos & William H. Sandholm, 2016. "Learning in Games via Reinforcement and Regularization," Mathematics of Operations Research, INFORMS, vol. 41(4), pages 1297-1324, November.
    13. Hofbauer, Josef & Sandholm, William H., 2009. "Stable games and their dynamics," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1665-1693.4, July.
    14. Dai Zusai, 2018. "Evolutionary dynamics in heterogeneous populations: a general framework for an arbitrary type distribution," Papers 1805.04897, arXiv.org, revised May 2019.
    15. Saeed Hadikhanloo & Rida Laraki & Panayotis Mertikopoulos & Sylvain Sorin, 2022. "Learning in nonatomic games, part Ⅰ: Finite action spaces and population games," Post-Print hal-03767995, HAL.
    16. Ratul Lahkar & Sayan Mukherjee & Souvik Roy, 2022. "A Deterministic Approximation Approach to the Continuum Logit Dynamic with an Application to Supermodular Games," Working Papers 79, Ashoka University, Department of Economics.
    17. Dai Zusai, 2017. "Nonaggregable evolutionary dynamics under payoff heterogeneity," DETU Working Papers 1702, Department of Economics, Temple University.
    18. Cheung, Man-Wah & Lahkar, Ratul, 2018. "Nonatomic potential games: the continuous strategy case," Games and Economic Behavior, Elsevier, vol. 108(C), pages 341-362.
    19. Russell, Golman, 2011. "Quantal response equilibria with heterogeneous agents," Journal of Economic Theory, Elsevier, vol. 146(5), pages 2013-2028, September.
    20. Sandholm, William H., 2005. "Excess payoff dynamics and other well-behaved evolutionary dynamics," Journal of Economic Theory, Elsevier, vol. 124(2), pages 149-170, October.

    More about this item

    Keywords

    Business cycles; Potential games; Logit dynamic; Negative externality;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:spr:dyngam:v:8:y:2018:i:4:d:10.1007_s13235-017-0234-6. See general information about how to correct material in RePEc.

    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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.