IDEAS home Printed from https://ideas.repec.org/p/fip/fedgif/1236.html
   My bibliography  Save this paper

Asset Price Learning and Optimal Monetary Policy

Author

Abstract

We characterize optimal monetary policy when agents are learning about endogenous asset prices. Boundedly rational expectations induce inefficient equilibrium asset price fluctuations which translate into inefficient aggregate demand fluctuations. We find that the optimal policy raises interest rates when expected capital gains, and the level of current asset prices, is high. The optimal policy does not eliminate deviations of asset prices from their fundamental value. When monetary policymakers are information-constrained, optimal policy can be reasonably approximated by simple interest rate rules that respond to capital gains. Our results are robust to a wide range of belief specifications as well as to the inclusion of an investment channel.

Suggested Citation

  • Colin C. Caines & Fabian Winkler, 2018. "Asset Price Learning and Optimal Monetary Policy," International Finance Discussion Papers 1236, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgif:1236
    DOI: 10.17016/IFDP.2018.1236
    as

    Download full text from publisher

    File URL: https://www.federalreserve.gov/econres/ifdp/files/ifdp1236.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.17016/IFDP.2018.1236?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Klaus Adam & Pei Kuang & Albert Marcet, 2012. "House Price Booms and the Current Account," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 77-122.
    2. Molnár, Krisztina & Santoro, Sergio, 2014. "Optimal monetary policy when agents are learning," European Economic Review, Elsevier, vol. 66(C), pages 39-62.
    3. Andreas Fuster & Benjamin Hebert & David Laibson, 2012. "Natural Expectations, Macroeconomic Dynamics, and Asset Pricing," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 1-48.
    4. Acemoglu, Daron & Woodford, Michael (ed.), 2012. "NBER Macroeconomics Annual 2011," National Bureau of Economic Research Books, University of Chicago Press, number 9780226002149, July.
    5. Albert Saiz, 2010. "The Geographic Determinants of Housing Supply," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1253-1296.
    6. Holston, Kathryn & Laubach, Thomas & Williams, John C., 2017. "Measuring the natural rate of interest: International trends and determinants," Journal of International Economics, Elsevier, vol. 108(S1), pages 59-75.
    7. Barberis, Nicholas & Greenwood, Robin & Jin, Lawrence & Shleifer, Andrei, 2015. "X-CAPM: An extrapolative capital asset pricing model," Journal of Financial Economics, Elsevier, vol. 115(1), pages 1-24.
    8. Preston, Bruce, 2006. "Adaptive learning, forecast-based instrument rules and monetary policy," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 507-535, April.
    9. Klaus Adam & Michael Woodford, 2018. "Leaning Against Housing Prices as Robustly Optimal Monetary Policy," CESifo Working Paper Series 7071, CESifo.
    10. Lawrence J. Christiano & Cosmin Ilut & Roberto Motto & Massimo Rostagno, 2010. "Monetary policy and stock market booms," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 85-145.
    11. Neiss, Katharine S. & Nelson, Edward, 2003. "The Real-Interest-Rate Gap As An Inflation Indicator," Macroeconomic Dynamics, Cambridge University Press, vol. 7(2), pages 239-262, April.
    12. Caines, Colin, 2020. "Can learning explain boom-bust cycles in asset prices? An application to the US housing boom," Journal of Macroeconomics, Elsevier, vol. 66(C).
    13. Klaus Adam & Albert Marcet & Johannes Beutel, 2017. "Stock Price Booms and Expected Capital Gains," American Economic Review, American Economic Association, vol. 107(8), pages 2352-2408, August.
    14. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    15. Feng Dong & Jianjun Miao & Pengfei Wang, 2020. "Asset Bubbles and Monetary Policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 37, pages 68-98, August.
    16. Jordi Gal?, 2014. "Monetary Policy and Rational Asset Price Bubbles," American Economic Review, American Economic Association, vol. 104(3), pages 721-752, March.
    17. Robin Greenwood & Andrei Shleifer, 2014. "Expectations of Returns and Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 714-746.
    18. Glaeser, Edward L. & Nathanson, Charles G., 2017. "An extrapolative model of house price dynamics," Journal of Financial Economics, Elsevier, vol. 126(1), pages 147-170.
    19. Charles R. Bean, 2004. "Asset Prices, Financial Instability, and Monetary Policy," American Economic Review, American Economic Association, vol. 94(2), pages 14-18, May.
    20. Stefano Eusepi & Bruce Preston, 2018. "The Science of Monetary Policy: An Imperfect Knowledge Perspective," Journal of Economic Literature, American Economic Association, vol. 56(1), pages 3-59, March.
    21. Dupor, Bill, 2005. "Stabilizing non-fundamental asset price movements under discretion and limited information," Journal of Monetary Economics, Elsevier, vol. 52(4), pages 727-747, May.
    22. Pierre Collin-Dufresne & Michael Johannes & Lars A. Lochstoer, 2013. "Parameter Learning in General Equilibrium: The Asset Pricing Implications," NBER Working Papers 19705, National Bureau of Economic Research, Inc.
    23. Winkler, Fabian, 2020. "The role of learning for asset prices and business cycles," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 42-58.
    24. Thomas Laubach & John C. Williams, 2015. "Measuring the natural rate of interest redux," Working Paper Series 2015-16, Federal Reserve Bank of San Francisco.
    25. Xavier Gabaix, 2020. "A Behavioral New Keynesian Model," American Economic Review, American Economic Association, vol. 110(8), pages 2271-2327, August.
    26. Faia, Ester & Monacelli, Tommaso, 2007. "Optimal interest rate rules, asset prices, and credit frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3228-3254, October.
    27. Billi, Roberto M., 2018. "Price level targeting and risk management," Economic Modelling, Elsevier, vol. 73(C), pages 163-173.
    28. Harding, John P. & Rosenthal, Stuart S. & Sirmans, C.F., 2007. "Depreciation of housing capital, maintenance, and house price inflation: Estimates from a repeat sales model," Journal of Urban Economics, Elsevier, vol. 61(2), pages 193-217, March.
    29. Adam, Klaus & Woodford, Michael, 2018. "Leaning against housing prices as robustly optimal monetary policy," CFS Working Paper Series 601, Center for Financial Studies (CFS).
    30. Christoph E. Boehm & Christopher L. House, 2014. "Optimal Taylor Rules in New Keynesian Models," NBER Working Papers 20237, National Bureau of Economic Research, Inc.
    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. Winkler, Fabian, 2020. "The role of learning for asset prices and business cycles," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 42-58.
    2. Caines, Colin, 2020. "Can learning explain boom-bust cycles in asset prices? An application to the US housing boom," Journal of Macroeconomics, Elsevier, vol. 66(C).
    3. Klaus Adam & Oliver Pfäuti & Timo Reinelt, 2020. "Falling Natural Rates, Rising Housing Volatility and the Optimal Inflation Target," CRC TR 224 Discussion Paper Series crctr224_2020_235, University of Bonn and University of Mannheim, Germany.
    4. Katsuhiro Oshima, 2021. "Heterogeneous beliefs, monetary policy, and stock price volatility," Annals of Finance, Springer, vol. 17(1), pages 79-125, March.
    5. Katsuhiro Oshima, 2019. "Subjective Beliefs, Monetary Policy, and Stock Price Volatility," KIER Working Papers 1012, Kyoto University, Institute of Economic Research.
    6. Katsuhiro Oshima, 2019. "Heterogeneous Beliefs, Monetary Policy, and Stock Price Volatility," KIER Working Papers 1013, Kyoto University, Institute of Economic Research.

    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. Caines, Colin & Winkler, Fabian, 2021. "Asset price beliefs and optimal monetary policy," Journal of Monetary Economics, Elsevier, vol. 123(C), pages 53-67.
    2. Klaus Adam & Oliver Pfäuti & Timo Reinelt, 2020. "Falling Natural Rates, Rising Housing Volatility and the Optimal Inflation Target," CRC TR 224 Discussion Paper Series crctr224_2020_235, University of Bonn and University of Mannheim, Germany.
    3. Adam, Klaus & Merkel, Sebastian, 2019. "Stock price cycles and business cycles," Working Paper Series 2316, European Central Bank.
    4. Adam, Klaus & Woodford, Michael, 2021. "Robustly optimal monetary policy in a new Keynesian model with housing," Journal of Economic Theory, Elsevier, vol. 198(C).
    5. Winkler, Fabian, 2020. "The role of learning for asset prices and business cycles," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 42-58.
    6. Boehl, Gregor, 2022. "Monetary policy and speculative asset markets," European Economic Review, Elsevier, vol. 148(C).
    7. Tortorice, Daniel L., 2018. "Equity return predictability, time varying volatility and learning about the permanence of shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 315-343.
    8. Oesinghaus, Andreas, 2024. "Analysts’ extrapolative expectations in the cross-section," Journal of Economics and Business, Elsevier, vol. 130(C).
    9. Zhang, Tongbin, 2021. "Stock prices and the risk-free rate: An internal rationality approach," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    10. 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.
    11. Paolo Gelain & Kevin J. Lansing & Caterina Mendicino, 2013. "House Prices, Credit Growth, and Excess Volatility: Implications for Monetary and Macroprudential Policy," International Journal of Central Banking, International Journal of Central Banking, vol. 9(2), pages 219-276, June.
    12. Gelain, Paolo & Lansing, Kevin J., 2014. "House prices, expectations, and time-varying fundamentals," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 3-25.
    13. Adam, Klaus & Woodford, Michael, 2018. "Leaning against housing prices as robustly optimal monetary policy," CFS Working Paper Series 601, Center for Financial Studies (CFS).
    14. Daniel L. Tortorice, 2019. "Long-Run Expectations, Learning and the US Housing Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(4), pages 497-531, October.
    15. Kuang, Pei & Mitra, Kaushik, 2016. "Long-run growth uncertainty," Journal of Monetary Economics, Elsevier, vol. 79(C), pages 67-80.
    16. Malmendier, Ulrike & Pouzo, Demian & Vanasco, Victoria, 2020. "Investor experiences and financial market dynamics," Journal of Financial Economics, Elsevier, vol. 136(3), pages 597-622.
    17. Pauline Gandré, 2020. "Learning, house prices and macro-financial linkages," EconomiX Working Papers 2020-10, University of Paris Nanterre, EconomiX.
    18. Caines, Colin, 2020. "Can learning explain boom-bust cycles in asset prices? An application to the US housing boom," Journal of Macroeconomics, Elsevier, vol. 66(C).
    19. Li, Kai & Liu, Jun, 2023. "Extrapolative asset pricing," Journal of Economic Theory, Elsevier, vol. 210(C).
    20. 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.

    More about this item

    Keywords

    Optimal monetary policy; Natural real Interest rate; Learning; Asset price volatility; Leaning against the wind;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    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:fip:fedgif:1236. 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: Ryan Wolfslayer ; Keisha Fournillier (email available below). General contact details of provider: https://edirc.repec.org/data/frbgvus.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.