IDEAS home Printed from https://ideas.repec.org/p/lev/wrkpap/wp_929.html
   My bibliography  Save this paper

When to Ease Off the Brakes--and Hopefully Prevent Recessions

Author

Listed:
  • Harold M. Hastings
  • Tai Young-Taft
  • Thomas Wang

Abstract

Increases in the federal funds rate aimed at stabilizing the economy have inevitably been followed by recessions. Recently, peaks in the federal funds rate have occurred 6-16 months before the start of recessions; reductions in interest rates apparently occurred too late to prevent those recessions. Potential leading indicators include measures of labor productivity, labor utilization, and demand, all of which influence stock market conditions, the return to capital, and changes in the federal funds rate, among many others. We investigate the dynamics of the spread between the 10-year Treasury rate and the federal funds rate in order to better understand "when to ease off the (federal funds) brakes.""

Suggested Citation

  • Harold M. Hastings & Tai Young-Taft & Thomas Wang, 2019. "When to Ease Off the Brakes--and Hopefully Prevent Recessions," Economics Working Paper Archive wp_929, Levy Economics Institute.
  • Handle: RePEc:lev:wrkpap:wp_929
    as

    Download full text from publisher

    File URL: http://www.levyinstitute.org/pubs/wp_929.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arturo Estrella & Frederic S. Mishkin, 1996. "The yield curve as a predictor of U.S. recessions," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 2(Jun).
    2. Arturo Estrella & Mary R. Trubin, 2006. "The yield curve as a leading indicator: some practical issues," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 12(Jul).
    3. Boldrin, Michele & Woodford, Michael, 1990. "Equilibrium models displaying endogenous fluctuations and chaos : A survey," Journal of Monetary Economics, Elsevier, vol. 25(2), pages 189-222, March.
    4. E. Stockhammere & J. Michell, 2017. "Pseudo-Goodwin cycles in a Minsky model," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 41(1), pages 105-125.
    5. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    6. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    7. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    8. Harvie, David, 2000. "Testing Goodwin: Growth Cycles in Ten OECD Countries," Cambridge Journal of Economics, Oxford University Press, vol. 24(3), pages 349-376, May.
    9. Michael D. Bauer & Thomas M. Mertens, 2018. "Information in the Yield Curve about Future Recessions," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    Full references (including those not matched with items on IDEAS)

    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. Massimo Ferrari Minesso & Laura Lebastard & Helena Mezo, 2023. "Text-Based Recession Probabilities," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(2), pages 415-438, June.
    2. Dongfeng Chang & Ryan S. Mattson & Biyan Tang, 2019. "The Predictive Power of the User Cost Spread for Economic Recession in China and the US," IJFS, MDPI, vol. 7(2), pages 1-12, June.
    3. Pawel Dlotko & Simon Rudkin, 2019. "The Topology of Time Series: Improving Recession Forecasting from Yield Spreads," Working Papers 2019-02, Swansea University, School of Management.
    4. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
    5. Fernandez-Perez, Adrian & Fernández-Rodríguez, Fernando & Sosvilla-Rivero, Simón, 2014. "The term structure of interest rates as predictor of stock returns: Evidence for the IBEX 35 during a bear market," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 21-33.
    6. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    7. Candelon, B. & Dumitrescu, E-I. & Hurlin, C., 2010. "How to evaluate an early warning system? Towards a united statistical framework for assessing financial crises forecasting methods," Research Memorandum 046, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    8. B. De Backer & M. Deroose & Ch. Van Nieuwenhuyze, 2019. "Is a recession imminent? The signal of the yield curve," Economic Review, National Bank of Belgium, issue i, pages 69-93, June.
    9. Ferdi Botha & Gavin Keeton, 2014. "A Note on the (Continued) Ability of the Yield Curve to Forecast Economic Downturns in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 82(3), pages 468-473, September.
    10. Maas, Benedikt, 2019. "Nowcasting and forecasting US recessions: Evidence from the Super Learner," MPRA Paper 96408, University Library of Munich, Germany.
    11. Johannes A. Skjeltorp & Bernt Arne Ødegaard, 2009. "The information content of market liquidity: An empirical analysis of liquidity at the Oslo Stock Exchange?," Working Paper 2009/26, Norges Bank.
    12. Todd J. BARRY, 2020. "Causes of the curve: Assessing risk in public and private financial economics," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(623), S), pages 109-130, Summer.
    13. Yutaka Kurihara, 2016. "Term Structure of Interest Rates under Zero or Low Bound: The Recent Japanese Case," Economy, Asian Online Journal Publishing Group, vol. 3(1), pages 19-23.
    14. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    15. Kuang-Liang Chang & Nan-Kuang Chen & Charles Ka Yui Leung, 2013. "In the Shadow of the U nited S tates: The International Transmission Effect of Asset Returns," Pacific Economic Review, Wiley Blackwell, vol. 18(1), pages 1-40, February.
    16. Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I., 2019. "Residential investment and recession predictability," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1790-1799.
    17. Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2021. "Applications of machine learning for corporate bond yield spread forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    18. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(1), pages 320-346, February.
    19. Jos'e-Manuel Pe~na & Fernando Su'arez & Omar Larr'e & Domingo Ram'irez & Arturo Cifuentes, 2023. "A Modified CTGAN-Plus-Features Based Method for Optimal Asset Allocation," Papers 2302.02269, arXiv.org, revised Feb 2023.
    20. Ohnsorge,Franziska Lieselotte & Stocker,Marc & Some,Modeste Y., 2016. "Quantifying uncertainties in global growth forecasts," Policy Research Working Paper Series 7770, The World Bank.

    More about this item

    Keywords

    Federal Funds Rate; Yield Curve; Monetary Policy; Nonlinear Dynamics; Takens' Embedding;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • 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:lev:wrkpap:wp_929. 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: Elizabeth Dunn (email available below). General contact details of provider: http://www.levyinstitute.org .

    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.