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Optimal Monetary Policy when Information is Market-Generated

Author

Listed:
  • Isabella Blengini

    (Ecole hôtelière de Lausanne)

  • Kenza Benhima

    (University of Lausanne (HEC))

Abstract
In this paper we study how the endogenous nature of the signals ob- served by the private sector affects optimal monetary policy. Agents learn from sources of information that are not market-determined, such as news, but also from variables that are endogenously determined on the markets, such as prices or production. In that case, how can the central optimally condition its monetary instrument on its information? When signals re- ceived by private agents are purely exogenous, it is optimal for the central bank to directly steer the economy towards the efficient allocation. This can be achieved through a price stabilization objective. In this case the public does not need to infer the state of the economy and the central bank is in charge of all the action. When information is endogenous, the policy of the central bank is aimed at maximizing the information content of the market-determined variables that agents use as sources of information. This is achieved by exacerbating the natural response of prices to shocks. This result holds independently of the possibility of the central bank to directly communicate its information through public announcements.

Suggested Citation

  • Isabella Blengini & Kenza Benhima, 2016. "Optimal Monetary Policy when Information is Market-Generated," 2016 Meeting Papers 1223, Society for Economic Dynamics.
    • Handle: RePEc:red:sed016:1223
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    References listed on IDEAS

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    2. Markus Heckel & Kiyohiko G. Nishimura, 2020. "Unconventional Monetary Policy through Open Market Operations: A Principal Component Analysis," CARF F-Series CARF-F-501, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Jonathan J Adams, 2020. "Moderating Macroeconomic Bubbles Under Dispersed Information," Working Papers 001005, University of Florida, Department of Economics.
    4. Adams, Jonathan J., 2023. "Moderating noise-driven macroeconomic fluctuations under dispersed information," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).
    5. Ryan Chahrour & Gaetano Gaballo, 2021. "Learning from House Prices: Amplification and Business Fluctuations [House Price Booms and the Current Account]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(4), pages 1720-1759.

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    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • 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
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements

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