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Constrained Discretion and Central Bank Transparency

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  • Francesco Bianchi
  • Leonardo Melosi

Abstract

We develop and estimate a general equilibrium model in which monetary policy can deviate from active inflation stabilization and agents face uncertainty about the nature of these deviations. When observing a deviation, agents conduct Bayesian learning to infer its likely duration. Under constrained discretion, only short deviations occur: Agents are confident about a prompt return to the active regime, macroeconomic uncertainty is low, welfare is high. However, if a deviation persists, agents' beliefs start drifting, uncertainty accelerates, and welfare declines. If the duration of the deviations is announced, uncertainty follows a reverse path. When estimated to match past U.S. experience, our model suggests that transparency lowers uncertainty and increases welfare.

Suggested Citation

  • Francesco Bianchi & Leonardo Melosi, 2014. "Constrained Discretion and Central Bank Transparency," NBER Working Papers 20566, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20566
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    Cited by:

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    2. Philippe Andrade & Gaetano Gaballo & Eric Mengus & Benoît Mojon, 2019. "Forward Guidance and Heterogeneous Beliefs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(3), pages 1-29, July.
    3. Istrefi, Klodiana & Mouabbi, Sarah, 2018. "Subjective interest rate uncertainty and the macroeconomy: A cross-country analysis," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 296-313.
    4. Leonardo Melosi, 2014. "Signaling Effects of Monteray Policy," 2014 Meeting Papers 830, Society for Economic Dynamics.
    5. Michael Ehrmann, 2015. "Targeting Inflation from Below: How Do Inflation Expectations Behave?," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 213-249, September.
    6. Stephen Hansen & Michael McMahon, 2016. "First Impressions Matter: Signalling as a Source of Policy Dynamics," Review of Economic Studies, Oxford University Press, vol. 83(4), pages 1645-1672.
    7. Leonardo Melosi, 2017. "Signalling Effects of Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 84(2), pages 853-884.
    8. Pablo Garcia, 2021. "Learning, expectations and monetary policy," BCL working papers 153, Central Bank of Luxembourg.
    9. Ehrmann, Michael & Gaballo, Gaetano & Hoffmann, Peter & Strasser, Georg, 2019. "Can more public information raise uncertainty? The international evidence on forward guidance," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 93-112.
    10. Timothy Cogley & Boyan Jovanovic, 2020. "Structural Breaks in an Endogenous Growth Model," NBER Working Papers 28026, National Bureau of Economic Research, Inc.
    11. Ippei Fujiwara & Yuichiro Waki, 2015. "Private news and monetary policy forward guidance or (the expected virtue of ignorance)," Globalization Institute Working Papers 238, Federal Reserve Bank of Dallas.
    12. Francesco Bianchi & Leonardo Melosi, 2014. "Dormant Shocks and Fiscal Virtue," NBER Macroeconomics Annual, University of Chicago Press, vol. 28(1), pages 1-46.
    13. Xin Wei, 2020. "Dynamic Expectations Formation and U.S. Monetary Policy Regime Change," CAEPR Working Papers 2020-007, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    14. Francesco Bianchi & Leonardo Melosi, 2012. "Modeling the Evolution of Expectations and Uncertainty in General Equilibrium," PIER Working Paper Archive 13-030, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    15. Levieuge, Grégory & Lucotte, Yannick & Pradines-Jobet, Florian, 2021. "The cost of banking crises: Does the policy framework matter?," Journal of International Money and Finance, Elsevier, vol. 110(C).
    16. Francesco Bianchi & Leonardo Melosi, 2016. "Modeling The Evolution Of Expectations And Uncertainty In General Equilibrium," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 717-756, May.
    17. Christian Matthes, 2015. "Figuring Out the Fed—Beliefs about Policymakers and Gains from Transparency," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(1), pages 1-29, February.
    18. McClung, Nigel, 2020. "E-stability vis-à-vis determinacy in regime-switching models," Journal of Economic Dynamics and Control, Elsevier, vol. 121(C).
    19. K. Istrefi & A. Piloiu, 2016. "Economic policy uncertainty and inflation expectations," Rue de la Banque, Banque de France, issue 33, november..
    20. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2021. "Monetary policy, Twitter and financial markets: evidence from social media traffic," BAFFI CAREFIN Working Papers 21160, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    21. Bianchi, Francesco, 2016. "Methods for measuring expectations and uncertainty in Markov-switching models," Journal of Econometrics, Elsevier, vol. 190(1), pages 79-99.
    22. Donato Masciandaro & Davide Romelli & Gaia Rubera, 2020. "Tweeting on Monetary Policy and Market Sentiments: The Central Bank Surprise Index," BAFFI CAREFIN Working Papers 20134, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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