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. 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.
    2. Brooks,Chris, 2008. "RATS Handbook to Accompany Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9780521896955.
    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. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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. Eric Rosengren, 2009. "Making monetary policy during a financial crisis," Speech 22, Federal Reserve Bank of Boston.
    12. 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)

    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. Thomas Walther & Lanouar Charfeddine & Tony Klein, 2018. "Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?," Working Papers on Finance 1816, University of St. Gallen, School of Finance.
    2. 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.
    3. 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.
    4. 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.
    5. Dierk HERZER & Felicitas NOWAK‐LEHMANN D. & Boriss SILIVERSTOVS, 2006. "Export‐Led Growth In Chile: Assessing The Role Of Export Composition In Productivity Growth," The Developing Economies, Institute of Developing Economies, vol. 44(3), pages 306-328, September.
    6. 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).
    7. 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).
    8. Alexeev, Vitali & Maynard, Alex, 2012. "Localized level crossing random walk test robust to the presence of structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3322-3344.
    9. 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.
    10. Herzer Dierk, 2005. "Exportdiversifizierung und Wirtschaftswachstum in Chile / Export Diversification and Economic Growth in Chile: Eine ökonometrische Analyse / An Econometric Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(2), pages 163-180, April.
    11. Dierk Herzer, 2005. "Does Trade Increase Total Factor Productivity: Cointegration Evidence for Chile," Ibero America Institute for Econ. Research (IAI) Discussion Papers 115, Ibero-America Institute for Economic Research.
    12. 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).
    13. Shen, Zhiwei & Ritter, Matthias, 2016. "Forecasting volatility of wind power production," Applied Energy, Elsevier, vol. 176(C), pages 295-308.
    14. Gillman, Max & Nakov, Anton, 2009. "Monetary effects on nominal oil prices," The North American Journal of Economics and Finance, Elsevier, vol. 20(3), pages 239-254, December.
    15. Dierk Herzer, 2007. "How does trade composition affect productivity? Evidence for Chile," Applied Economics Letters, Taylor & Francis Journals, vol. 14(12), pages 909-912.
    16. 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.
    17. 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.
    18. 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.
    19. Ketenci, Natalya, 2015. "Capital mobility in Russia," Russian Journal of Economics, Elsevier, vol. 1(4), pages 386-403.
    20. 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).

    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.