IDEAS home Printed from https://ideas.repec.org/p/cnb/wpaper/2016-07.html
   My bibliography  Save this paper

Confidence Cycles and Liquidity Hoarding

Author

Listed:
  • Volha Audzei

Abstract

Market confidence has proved to be an important factor during past crises. However, many existing general equilibrium models do not account for agents' expectations, market volatility, or overly pessimistic investor forecasts. In this paper, we incorporate a model of the interbank market into a DSGE model, with the interbank market rate and the volume of lending depending on market confidence and the perception of counterparty risk. In our model, a credit crunch occurs if the perception of counterparty risk increases. Our results suggest that changes in market confidence can generate credit crunches and contribute to the depth of recessions. We then conduct an exercise to mimic some central bank policies: targeted and untargeted liquidity provision, and reduction of the policy rate. Our results indicate that policy actions have a limited effect on the supply of credit if they fail to influence agents' expectations. Interestingly, a policy of a low policy rate worsens recessions due to its negative impact on banks' revenues. Liquidity provision stimulates credit slightly, but its efficiency is undermined by liquidity hoarding.

Suggested Citation

  • Volha Audzei, 2016. "Confidence Cycles and Liquidity Hoarding," Working Papers 2016/07, Czech National Bank.
  • Handle: RePEc:cnb:wpaper:2016/07
    as

    Download full text from publisher

    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2016_07.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clark, Todd E. & Davig, Troy, 2011. "Decomposing the declining volatility of long-term inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 981-999, July.
    2. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    3. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    4. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    5. Allen, Franklin & Carletti, Elena & Gale, Douglas, 2009. "Interbank market liquidity and central bank intervention," Journal of Monetary Economics, Elsevier, vol. 56(5), pages 639-652, July.
    6. Siklos, Pierre L., 2013. "Sources of disagreement in inflation forecasts: An international empirical investigation," Journal of International Economics, Elsevier, vol. 90(1), pages 218-231.
    7. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    8. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    9. Pfajfar, Damjan, 2013. "Formation of rationally heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1434-1452.
    10. Cúrdia, Vasco & Woodford, Michael, 2011. "The central-bank balance sheet as an instrument of monetarypolicy," Journal of Monetary Economics, Elsevier, vol. 58(1), pages 54-79, January.
    11. 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.
    12. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    13. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    14. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    15. Volha Audzei, 2012. "Efficiency of Central Bank Policy During the Crisis : Role of Expectations in Reinforcing Hoarding Behavior," CERGE-EI Working Papers wp477, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Confidence Cycles and Liquidity Hoarding
      by Christian Zimmermann in NEP-DGE blog on 2016-11-16 21:00:22

    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. James M. Nason & Gregor W. Smith, 2021. "Measuring the slowly evolving trend in US inflation with professional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
    2. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
    3. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.
    4. Ambrocio, Gene, 2017. "The real effects of overconfidence and fundamental uncertainty shocks," Research Discussion Papers 37/2017, Bank of Finland.
    5. Michael P. Clements, 2018. "Do Macroforecasters Herd?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(2-3), pages 265-292, March.
    6. CHEN Cheng & SENGA Tatsuro & SUN Chang & ZHANG Hongyong, 2018. "Uncertainty, Imperfect Information, and Expectation Formation over the Firm's Life Cycle," Discussion papers 18010, Research Institute of Economy, Trade and Industry (RIETI).
    7. Robert Rich & Joseph Tracy, 2021. "A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 233-253, February.
    8. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
    9. Cornand, Camille & Hubert, Paul, 2020. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    10. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Inflation fan charts, monetary policy and skew normal distribution," Discussion Papers in Economics 13/06, Division of Economics, School of Business, University of Leicester.
    11. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    12. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    13. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
    14. Yara de Almeida Campos Cordeiro & Wagner Piazza Gaglianone & João Victor Issler, 2017. "Inattention in individual expectations," Economia, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics], vol. 17(1), pages 40-59.
    15. Yoshiyuki Nakazono, 2016. "Inflation expectations and monetary policy under disagreements," Bank of Japan Working Paper Series 16-E-1, Bank of Japan.
    16. Clements, Michael P., 2019. "Do forecasters target first or later releases of national accounts data?," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1240-1249.
    17. Hur, Joonyoung & Kim, Insu, 2017. "Inattentive agents and disagreement about economic activity," Economic Modelling, Elsevier, vol. 63(C), pages 175-190.
    18. Snezana Eminidou & Marios Zachariadis, 2019. "Firms’ Expectations and Monetary Policy Shocks in the Eurozone," University of Cyprus Working Papers in Economics 02-2019, University of Cyprus Department of Economics.
    19. Michael Clements, 2016. "Are Macro-Forecasters Essentially The Same? An Analysis of Disagreement, Accuracy and Efficiency," ICMA Centre Discussion Papers in Finance icma-dp2016-08, Henley Business School, Reading University.
    20. Juan Camilo Galvis Ciro & Juan Camilo Anzoátegui Zapata, 2019. "Disagreement in inflation expectations: empirical evidence for Colombia," Applied Economics, Taylor & Francis Journals, vol. 51(40), pages 4411-4424, August.

    More about this item

    Keywords

    DSGE; expectations; financial intermediation; liquidity provision;
    All these keywords.

    JEL classification:

    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G01 - Financial Economics - - General - - - Financial Crises
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

    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:cnb:wpaper:2016/07. 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: (Jan Babecky). General contact details of provider: https://edirc.repec.org/data/cnbgvcz.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.