IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/20-2.html
   My bibliography  Save this paper

Social Learning and Monetary Policy at the Effective Lower Bound

Author

Listed:
  • Jasmina Arifovic
  • Alex Grimaud
  • Isabelle Salle
  • Gauthier Vermandel

Abstract

The first contribution of this paper is to develop a model that jointly accounts for the missing disinflation in the wake of the Great Recession and the subsequently observed inflation-less recovery. The key mechanism works through heterogeneous expectations that may durably lose their anchorage to the central bank (CB)’s target and coordinate on particularly persistent below-target paths. We jointly estimate the structural and the learning parameters of the model by matching moments from both macroeconomic and Survey of Professional Forecasters data. The welfare cost associated with those dynamics may be reduced if the CB communicates to the agents its target or its own inflation forecasts, as communication helps anchor expectations at the target. However, the CB may lose its credibility whenever its announcements become decoupled from actual inflation, for instance in the face of large and unexpected shocks.

Suggested Citation

  • Jasmina Arifovic & Alex Grimaud & Isabelle Salle & Gauthier Vermandel, 2020. "Social Learning and Monetary Policy at the Effective Lower Bound," Staff Working Papers 20-2, Bank of Canada.
  • Handle: RePEc:bca:bocawp:20-2
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2020/01/swp2020-2.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Thomas M. Mertens & John C. Williams, 2019. "Monetary Policy Frameworks and the Effective Lower Bound on Interest Rates," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 427-432, May.
    2. Anton Nakov, 2008. "Optimal and Simple Monetary Policy Rules with Zero Floor on the Nominal Interest Rate," International Journal of Central Banking, International Journal of Central Banking, vol. 4(2), pages 73-127, June.
    3. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    4. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    5. Guerrieri, Luca & Iacoviello, Matteo, 2015. "OccBin: A toolkit for solving dynamic models with occasionally binding constraints easily," Journal of Monetary Economics, Elsevier, vol. 70(C), pages 22-38.
    6. William A. Branch, 2004. "The Theory of Rationally Heterogeneous Expectations: Evidence from Survey Data on Inflation Expectations," Economic Journal, Royal Economic Society, vol. 114(497), pages 592-621, July.
    7. Barbara Rossi & Tatevik Sekhposyan, 2015. "Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions," American Economic Review, American Economic Association, vol. 105(5), pages 650-655, May.
    8. Adam, Klaus & Marcet, Albert, 2011. "Internal rationality, imperfect market knowledge and asset prices," Journal of Economic Theory, Elsevier, vol. 146(3), pages 1224-1252, May.
    9. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    10. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2017. "Inflation Expectations, Learning, and Supermarket Prices: Evidence from Survey Experiments," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(3), pages 1-35, July.
    11. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Optimal fiscal and monetary policy under sticky prices," Journal of Economic Theory, Elsevier, vol. 114(2), pages 198-230, February.
    12. Jasmina Arifovic & John Ledyard, 2012. "Individual Evolutionary Learning, Other-regarding Preferences, and the Voluntary Contributions Mechanism," Discussion Papers wp12-01, Department of Economics, Simon Fraser University.
    13. Mikhail Anufriev & Cars Hommes, 2012. "Evolutionary Selection of Individual Expectations and Aggregate Outcomes in Asset Pricing Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(4), pages 35-64, November.
    14. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    15. Olivier Coibion & Yuriy Gorodnichenko & Michael Weber, 2022. "Monetary Policy Communications and Their Effects on Household Inflation Expectations," Journal of Political Economy, University of Chicago Press, vol. 130(6), pages 1537-1584.
    16. Cars Hommes & Domenico Massaro & Isabelle Salle, 2019. "Monetary And Fiscal Policy Design At The Zero Lower Bound: Evidence From The Lab," Economic Inquiry, Western Economic Association International, vol. 57(2), pages 1120-1140, April.
    17. Evans, George W. & Guse, Eran & Honkapohja, Seppo, 2008. "Liquidity traps, learning and stagnation," European Economic Review, Elsevier, vol. 52(8), pages 1438-1463, November.
    18. Arifovic, Jasmina & Ledyard, John, 2012. "Individual evolutionary learning, other-regarding preferences, and the voluntary contributions mechanism," Journal of Public Economics, Elsevier, vol. 96(9-10), pages 808-823.
    19. Jasmina Arifovic & James Bullard & Olena Kostyshyna, 2013. "Social Learning and Monetary Policy Rules," Economic Journal, Royal Economic Society, vol. 123(567), pages 38-76, March.
    20. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    21. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    22. Stefano Eusepi & Bruce Preston, 2010. "Central Bank Communication and Expectations Stabilization," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 235-271, July.
    23. Thomas M. Mertens & John C. Williams, 2019. "Tying Down the Anchor: Monetary Policy Rules and the Lower Bound on Interest Rates," Working Paper Series 2019-14, Federal Reserve Bank of San Francisco.
    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. Petersen, Luba & Rholes, Ryan, 2022. "Macroeconomic expectations, central bank communication, and background uncertainty: A COVID-19 laboratory experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    2. Tolga Özden, 2021. "Heterogeneous Expectations and the Business Cycle at the Effective Lower Bound," Working Papers 714, DNB.

    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. Hommes, Cars, 2018. "Behavioral & experimental macroeconomics and policy analysis: a complex systems approach," Working Paper Series 2201, European Central Bank.
    2. Arifovic, Jasmina & Petersen, Luba, 2017. "Stabilizing expectations at the zero lower bound: Experimental evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 21-43.
    3. Goy, Gavin & Hommes, Cars & Mavromatis, Kostas, 2022. "Forward guidance and the role of central bank credibility under heterogeneous beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 1240-1274.
    4. Bao, Te & Hommes, Cars & Pei, Jiaoying, 2021. "Expectation formation in finance and macroeconomics: A review of new experimental evidence," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    5. Ahrens, Steffen & Lustenhouwer, Joep & Tettamanzi, Michele, 2017. "The Stabilizing Role of Forward Guidance: A Macro Experiment," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168063, Verein für Socialpolitik / German Economic Association.
    6. Gavin Goy & Cars Homme & Kostas Mavromatis, 2018. "Forward Guidance and the Role of Central Bank Credibility," DNB Working Papers 614, Netherlands Central Bank, Research Department.
    7. Gasteiger, Emanuel, 2018. "Do Heterogeneous Expectations Constitute A Challenge For Policy Interaction?," Macroeconomic Dynamics, Cambridge University Press, vol. 22(8), pages 2107-2140, December.
    8. Tiziana Assenza & William A. Brock & Cars H. Hommes, 2013. "Animal Spirits, Heterogeneous Expectations and the Emergence of Booms and Busts," Tinbergen Institute Discussion Papers 13-205/II, Tinbergen Institute.
    9. Cole, Stephen J. & Milani, Fabio, 2021. "Heterogeneity in individual expectations, sentiment, and constant-gain learning," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 627-650.
    10. Elton Beqiraj & Giovanni Di Bartolomeo & Marco Di Pietro & Carolina Serpieri, 2020. "Bounded rationality and heterogeneous expectations: Euler versus anticipated-utility approach," Journal of Economics, Springer, vol. 130(3), pages 249-273, August.
    11. Gauti Eggertsson & Sergey Egiev & Alessandro Lin & Josef Platzer & Luca Riva, 2021. "A Toolkit for Solving Models with a Lower Bound on Interest Rates of Stochastic Duration," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 41, pages 121-173, July.
    12. Mele, Antonio & Molnár, Krisztina & Santoro, Sergio, 2020. "On the perils of stabilizing prices when agents are learning," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 339-353.
    13. Lena Dräger & Klaus Gründler & Niklas Potrafke, 2022. "Political Shocks and Inflation Expectations: Evidence from the 2022 Russian Invasion of Ukraine," ifo Working Paper Series 371, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    14. Kryvtsov, Oleksiy & Petersen, Luba, 2021. "Central bank communication that works: Lessons from lab experiments," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 760-780.
    15. Anna Agliari & Domenico Massaro & Nicolò Pecora & Alessandro Spelta, 2017. "Inflation Targeting, Recursive Inattentiveness, and Heterogeneous Beliefs," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(7), pages 1587-1619, October.
    16. Hommes, Cars & Massaro, Domenico & Weber, Matthias, 2019. "Monetary policy under behavioral expectations: Theory and experiment," European Economic Review, Elsevier, vol. 118(C), pages 193-212.
    17. Tiziana Assenza & William A. Brock & Cars H. Hommes, 2017. "Animal Spirits, Heterogeneous Expectations, And The Amplification And Duration Of Crises," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 542-564, January.
    18. Beqiraj Elton & Di Bartolomeo Giovanni & Serpieri Carolina, 2017. "Bounded-rationality and heterogeneous agents: Long or short forecasters?," wp.comunite 00132, Department of Communication, University of Teramo.
    19. repec:ctc:serie1:def7 is not listed on IDEAS
    20. Rostagno, Massimo & Altavilla, Carlo & Carboni, Giacomo & Lemke, Wolfgang & Motto, Roberto & Saint Guilhem, Arthur & Yiangou, Jonathan, 2019. "A tale of two decades: the ECB’s monetary policy at 20," Working Paper Series 2346, European Central Bank.
    21. Bianchi, Francesco & Melosi, Leonardo & Rottner, Matthias, 2021. "Hitting the elusive inflation target," Journal of Monetary Economics, Elsevier, vol. 124(C), pages 107-122.

    More about this item

    Keywords

    Business fluctuations and cycles; Central bank research; Credibility; Economic models; Monetary Policy; Monetary policy communications;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E70 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bca:bocawp:20-2. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.html .

    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.