IDEAS home Printed from https://ideas.repec.org/p/wil/wileco/2013-12.html
   My bibliography  Save this paper

How Inflation Affects Macroeconomic Performance: An Agent-Based Computational Investigation

Author

Abstract

We use an agent-based computational approach to show how inflation can worsen macroeconomic performance by disrupting the mechanism of exchange in a decentralized market economy. We find that, in our model economy, increasing the trend rate of inflation above 3 percent has a substantial deleterious effect, but lowering it below 3 percent has no significant macroeconomic consequences. Our finding remains qualitatively robust to changes in parameter values and to modifications to our model that partly address the Lucas critique. Finally, we contribute a novel explanation for why cross-country regressions may fail to detect a significant negative effect of trend inflation on output even when such an effect exists in reality.

Suggested Citation

  • Quamrul Ashraf & Boris Gershman & Peter Howitt, 2011. "How Inflation Affects Macroeconomic Performance: An Agent-Based Computational Investigation," Department of Economics Working Papers 2013-12, Department of Economics, Williams College, revised Mar 2014.
    • Handle: RePEc:wil:wileco:2013-12
    as

    Download full text from publisher

    File URL: https://web.williams.edu/Economics/wp/AshrafGershmanHowitt_Inflation.pdf
    File Function: Full text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Peter Howitt, 2006. "The Microfoundations of the Keynesian Multiplier Process," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(1), pages 33-44, May.
    2. Guido Ascari, 2004. "Staggered Prices and Trend Inflation: Some Nuisances," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 7(3), pages 642-667, July.
    3. David Laidler, 1997. "Money and Macroeconomics," Books, Edward Elgar Publishing, number 1252.
    4. Lach, Saul & Tsiddon, Daniel, 1992. "The Behavior of Prices and Inflation: An Empirical Analysis of Disaggregated Price Data," Journal of Political Economy, University of Chicago Press, vol. 100(2), pages 349-389, April.
    5. Bullard, James & Keating, John W., 1995. "The long-run relationship between inflation and output in postwar economies," Journal of Monetary Economics, Elsevier, vol. 36(3), pages 477-496, December.
    6. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
    7. Dosi, Giovanni & Fagiolo, Giorgio & Roventini, Andrea, 2010. "Schumpeter meeting Keynes: A policy-friendly model of endogenous growth and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1748-1767, September.
    8. Guillaume Rocheteau & Randall Wright, 2005. "Money in Search Equilibrium, in Competitive Equilibrium, and in Competitive Search Equilibrium," Econometrica, Econometric Society, vol. 73(1), pages 175-202, January.
    9. Mikhail Golosov & Robert E. Lucas Jr., 2007. "Menu Costs and Phillips Curves," Journal of Political Economy, University of Chicago Press, vol. 115, pages 171-199.
    10. Christophe Deissenberg & Sander van der Hoog & Herbert Dawid, 2008. "EURACE: A Massively Parallel Agent-Based Model of the European Economy," Working Papers halshs-00339756, HAL.
    11. Debelle, Guy & Lamont, Owen, 1997. "Relative Price Variability and Inflation: Evidence from U.S. Cities," Journal of Political Economy, University of Chicago Press, vol. 105(1), pages 132-152, February.
    12. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    13. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    14. Gomme, Paul, 1993. "Money and growth revisited : Measuring the costs of inflation in an endogenous growth model," Journal of Monetary Economics, Elsevier, vol. 32(1), pages 51-77, August.
    15. Stockman, Alan C., 1981. "Anticipated inflation and the capital stock in a cash in-advance economy," Journal of Monetary Economics, Elsevier, vol. 8(3), pages 387-393.
    16. Christopher Ragan, 1998. "On the Believable Benefits of Low Inflation," Staff Working Papers 98-15, Bank of Canada.
    17. Parsley, David C, 1996. "Inflation and Relative Price Variability in the Short and Long Run: New Evidence from the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(3), pages 323-341, August.
    18. Pierre Fortin, 1996. "The Great Canadian Slump," Canadian Journal of Economics, Canadian Economics Association, vol. 29(4), pages 761-787, November.
    19. Joseph H. Haslag, 1997. "Output, growth, welfare, and inflation: a survey," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Q II, pages 11-21.
    20. Parks, Richard W, 1978. "Inflation and Relative Price Variability," Journal of Political Economy, University of Chicago Press, vol. 86(1), pages 79-95, February.
    21. Allen Head & Alok Kumar, 2005. "Price Dispersion, Inflation, And Welfare," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(2), pages 533-572, May.
    22. Tack Yun, 2005. "Optimal Monetary Policy with Relative Price Distortions," American Economic Review, American Economic Association, vol. 95(1), pages 89-109, March.
    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. Jean-Luc Gaffard & Mauro Napoletano, 2018. "Hétérogénéité des agents, interconnexions financières et politique monétaire : une approche non conventionnelle," Revue française d'économie, Presses de Sciences-Po, vol. 0(3), pages 201-231.
    2. Ricetti, Luca & Russo, Alberto & Gallegati, Mauro, 2013. "Unemployment benefits and financial leverage in an agent based macroeconomic model," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 7, pages 1-44.
    3. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2017. "Taming macroeconomic instability: Monetary and macro-prudential policy interactions in an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 117-140.
    4. Richard Bookstaber, 2012. "Using Agent-Based Models for Analyzing Threats to Financial Stability," Working Papers 12-03, Office of Financial Research, US Department of the Treasury.
    5. Isabelle SALLE & Marc-Alexandre SENEGAS & Murat YILDIZOGLU, 2013. "How Transparent About Its Inflation Target Should a Central Bank be? An Agent-Based Model Assessment," Cahiers du GREThA (2007-2019) 2013-24, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    6. Giri, Federico & Riccetti, Luca & Russo, Alberto & Gallegati, Mauro, 2019. "Monetary policy and large crises in a financial accelerator agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 42-58.
    7. Dawid, H. & Harting, P. & Neugart, M., 2014. "Economic convergence: Policy implications from a heterogeneous agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 54-80.
    8. Edoardo Gaffeo & Mauro Gallegati & Umberto Gostoli, 2012. "An agent-based "proof of principle" for Walrasian macroeconomic theory," CEEL Working Papers 1202, Cognitive and Experimental Economics Laboratory, Department of Economics, University of Trento, Italia.
    9. Howitt, Peter & Özak, Ömer, 2014. "Adaptive consumption behavior," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 37-61.
    10. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    11. Caiani, Alessandro & Catullo, Ermanno & Gallegati, Mauro, 2019. "The effects of alternative wage regimes in a monetary union: A multi-country agent based-stock flow consistent model," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 389-416.
    12. Herbert Dawid & Philipp Harting & Sander Hoog & Michael Neugart, 2019. "Macroeconomics with heterogeneous agent models: fostering transparency, reproducibility and replication," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 467-538, March.
    13. Ooft, Gavin, 2016. "Inflation and Economic Activity in Suriname," EconStor Preprints 215533, ZBW - Leibniz Information Centre for Economics.
    14. Kinda Hachem & Jing Cynthia Wu, 2017. "Inflation Announcements and Social Dynamics," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(8), pages 1673-1713, December.
    15. Isabelle Salle & Marc-Alexandre Sénégas & Murat Yıldızoğlu, 2019. "How transparent about its inflation target should a central bank be?," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 391-427, March.
    16. Teglio, Andrea & Mazzocchetti, Andrea & Ponta, Linda & Raberto, Marco & Cincotti, Silvano, 2019. "Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 59-83.
    17. Tweneboah Senzu, Emmanuel, 2020. "Theoretically proposed policy instrument to resolve the negative effect of inflation flow into a positive macroeconomic growth: the case of Sierra Leone economy," MPRA Paper 99402, University Library of Munich, Germany.
    18. Lai, Van Son & Ye, Xiaoxia & Zhao, Lu, 2019. "Are market views on banking industry useful for forecasting economic growth?," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    19. Miguel A. Fuentes & Claudio J. Tessone & Bernardo A. Furtado, 2019. "Policy Modeling and Applications: State-of-the-Art and Perspectives," Complexity, Hindawi, vol. 2019, pages 1-11, February.

    More about this item

    Keywords

    Agent-based computational model; trend inflation; price dispersion; firm turnover;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E00 - Macroeconomics and Monetary Economics - - General - - - General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

    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:wil:wileco:2013-12. 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: (Stephen Sheppard). General contact details of provider: http://edirc.repec.org/data/edwilus.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 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.

    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.