IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v11y2018i1p9-d130475.html
   My bibliography  Save this article

Effectiveness of Interest Rate Policy of the Fed in Management of Subprime Mortgage Crisis

Author

Listed:
  • Samet Gunay

    (Finance Department, American University of the Middle East, 15453 Egaila, Kuwait)

  • Bojan Georgievski

    (Finance Department, American University of the Middle East, 15453 Egaila, Kuwait)

Abstract

The federal funds rate is one of the most important monetary policy instruments of Federal Reserve Bank of America. In this study, we analyze the effectiveness of Fed interest rate policy on different markets in the period between 1976 and 2016 through Markov regime-switching regression analysis. Results indicate that Federal funds’ rate affects labor and housing markets with a few months’ lag. However, the influence of Federal funds rate on inflation rate is quite limited. It is most probable that Fed employs alternative monetary instruments to regulate inflation. The most interesting results are obtained in the domain of personal savings. The interaction of personal savings and Federal funds rate is significant during both expansion and recession regimes.

Suggested Citation

  • Samet Gunay & Bojan Georgievski, 2018. "Effectiveness of Interest Rate Policy of the Fed in Management of Subprime Mortgage Crisis," JRFM, MDPI, vol. 11(1), pages 1-11, February.
    • Handle: RePEc:gam:jjrfmx:v:11:y:2018:i:1:p:9-:d:130475
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/11/1/9/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/11/1/9/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955, November.
    2. George Kapetanios, 2005. "Unit‐root testing against the alternative hypothesis of up to m structural breaks," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 123-133, January.
    3. Balcilar, Mehmet & Gupta, Rangan & Miller, Stephen M., 2015. "Regime switching model of US crude oil and stock market prices: 1859 to 2013," Energy Economics, Elsevier, vol. 49(C), pages 317-327.
    4. Shujie Yao & Dan Luo & Stephen Morgan, 2008. "Impact of the US Credit Crunch and Housing Market Crisis on China," Discussion Papers 08/32, University of Nottingham, GEP.
    5. Eric Rosengren, 2009. "Making monetary policy during a financial crisis," Speech 22, Federal Reserve Bank of Boston.
    6. Ayben Koy, 2017. "International Credit Default Swaps Market During European Crisis: A Markov Switching Approach," Contributions to Economics, in: Ümit Hacioğlu & Hasan Dinçer (ed.), Global Financial Crisis and Its Ramifications on Capital Markets, pages 431-443, Springer.
    7. Puri, Manju & Rocholl, Jörg & Steffen, Sascha, 2011. "Global retail lending in the aftermath of the US financial crisis: Distinguishing between supply and demand effects," Journal of Financial Economics, Elsevier, vol. 100(3), pages 556-578, June.
    8. Samet Günay, 2016. "Alteration of Risk in Asian Bond Markets during and after Mortgage Crisis: Evidence from Value at Risk (VaR) Analysis," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 12(Suppl. 1), pages 159–182-1.
    9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    10. Lee, Tae-Hwy & White, Halbert & Granger, Clive W. J., 1993. "Testing for neglected nonlinearity in time series models : A comparison of neural network methods and alternative tests," Journal of Econometrics, Elsevier, vol. 56(3), pages 269-290, April.
    11. Brock, William A. & Sayers, Chera L., 1988. "Is the business cycle characterized by deterministic chaos?," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 71-90, July.
    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. Abakah, Emmanuel Joel Aikins & Brahim, Mariem & Carlotti, Jean-Etienne & Tiwari, Aviral Kumar & Mensi, Walid, 2024. "Extreme downside risk connectedness and portfolio hedging among the G10 currencies," International Economics, Elsevier, vol. 178(C).

    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. Ilu, Ahmad Ibraheem, 2019. "Oil price Volatility and Exchange rate Dynamics in Nigeria: A Markov Switching Approach," MPRA Paper 97643, University Library of Munich, Germany.
    2. Giorgio Fagiolo & Mauro Napoletano & Andrea Roventini, 2008. "Are output growth-rate distributions fat-tailed? some evidence from OECD countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(5), pages 639-669.
    3. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    4. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    5. Lin, Ling & Zhou, Zhongbao & Jiang, Yong & Ou, Yangchen, 2021. "Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    6. Robinson Kruse & Michael Frömmel & Lukas Menkhoff & Philipp Sibbertsen, 2012. "What do we know about real exchange rate nonlinearities?," Empirical Economics, Springer, vol. 43(2), pages 457-474, October.
    7. Lopes, Artur Silva & Zsurkis, Gabriel Florin, 2017. "Are linear models really unuseful to describe business cycle data?," Economics Discussion Papers 2017-5, Kiel Institute for the World Economy (IfW Kiel).
    8. repec:hum:wpaper:sfb649dp2015-026 is not listed on IDEAS
    9. Psaradakis Zacharias & Spagnolo Nicola, 2002. "Power Properties of Nonlinearity Tests for Time Series with Markov Regimes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-16, November.
    10. Barnett, William A. & Serletis, Apostolos, 2000. "Martingales, nonlinearity, and chaos," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 703-724, June.
    11. Marianna Oliskevych & Iryna Lukianenko, 2020. "European unemployment nonlinear dynamics over the business cycles: Markov switching approach," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 22(4), pages 375-401.
    12. Kirikkaleli, Dervis, 2020. "The effect of domestic and foreign risks on an emerging stock market: A time series analysis," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    13. Manfred M. Fischer & Wolfgang Koller, 2001. "Testing for Non-Linear Dependence in Univariate Time Series: An Empirical Investigation of the Austrian Unemployment Rate," ERSA conference papers ersa01p233, European Regional Science Association.
    14. Ng, Serena, 1996. "Looking for evidence of speculative stockholding in commodity markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 123-143.
    15. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2016. "The impact of oil shocks on exchange rates: A Markov-switching approach," Energy Economics, Elsevier, vol. 54(C), pages 11-23.
    16. Robert J Bianchi & Adam E Clements & Michael E Drew, 2009. "HACking at Non-linearity: Evidence from Stocks and Bonds," School of Economics and Finance Discussion Papers and Working Papers Series 244, School of Economics and Finance, Queensland University of Technology.
    17. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun.
    18. Shintani, Mototsugu, 2005. "Nonlinear Forecasting Analysis Using Diffusion Indexes: An Application to Japan," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 517-538, June.
    19. Barnett, William A. & Serletis, Apostolos & Serletis, Demitre, 2015. "Nonlinear And Complex Dynamics In Economics," Macroeconomic Dynamics, Cambridge University Press, vol. 19(8), pages 1749-1779, December.
    20. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    21. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.

    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:gam:jjrfmx:v:11:y:2018:i:1:p:9-:d:130475. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.