IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/01-23.html
   My bibliography  Save this paper

Modelling Mortgage Rate Changes with a Smooth Transition Error-Correction Model

Author

Listed:
  • Ying Liu

Abstract

This paper uses a smooth transition error-correction model (STECM) to model the one-year and five-year mortgage rate changes. The model allows for a non-linear adjustment process of mortgage rates towards their long-run equilibrium. We also introduce time-varying thresholds into the standard STECM specification, to capture the gradual structural changes in the error-correction term. We find that the STECM, whether with fixed or time-varying thresholds, yields better in-sample fit and lower forecast errors than the linear benchmark and univariate models. Our estimation results indicate non-linearities in the adjustment process of mortgage rates towards their long-run equilibria. In particular, we find that mortgage rates respond more significantly to a large than to a small disequilibrium. The improvement of the STECMs in forecasting is statistically significant over the univariate models, but insignificant over the linear model.

Suggested Citation

  • Ying Liu, 2001. "Modelling Mortgage Rate Changes with a Smooth Transition Error-Correction Model," Staff Working Papers 01-23, Bank of Canada.
    • Handle: RePEc:bca:bocawp:01-23
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp01-23.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael A. Goldberg, 1984. "The Sensitivity Of The Prime Rate To Money Market Conditions," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 7(4), pages 269-280, December.
    2. K. S. Chan & H. Tong, 1986. "On Estimating Thresholds In Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 7(3), pages 179-190, May.
    3. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    4. Lundbergh, Stefan & Terasvirta, Timo & van Dijk, Dick, 2003. "Time-Varying Smooth Transition Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 104-121, January.
    5. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-745, September.
    6. Anderson, Heather M, 1997. "Transaction Costs and Non-linear Adjustment towards Equilibrium in the US Treasury Bill Market," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(4), pages 465-484, November.
    7. Dueker, Michael, 1999. "Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 466-472, October.
    8. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    10. Dwyer, Gerald P, Jr & Locke, Peter R & Yu, Wei, 1996. "Index Arbitrage and Nonlinear Dynamics between the S&P 500 Futures and Cash," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 301-332.
    11. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
    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. Jack R. Rogers, 2013. "Monetary Transmission to UK Retail Mortgage Rates before and after August 2007," Discussion Papers 1307, University of Exeter, Department of Economics.
    2. Fredj Jawadi & Georges Prat, 2012. "Arbitrage costs and nonlinear adjustment in the G7 stock markets," Applied Economics, Taylor & Francis Journals, vol. 44(12), pages 1561-1582, April.
    3. Tripe, David & Xia, Bingru & Roberts, Leigh, 2011. "Can implied forward mortgage rates predict future mortgage rates - recent New Zealand experience," Working Paper Series 18604, Victoria University of Wellington, School of Economics and Finance.
    4. Jan Willem van den End, 2011. "Statistical evidence on the mean reversion of interest rates," DNB Working Papers 284, Netherlands Central Bank, Research Department.
    5. Arouri, Mohamed & Jawadi, Fredj & Nguyen, Duc Khuong, 2013. "What can we tell about monetary policy synchronization and interdependence over the 2007–2009 global financial crisis?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 175-187.
    6. Tripe, David & Xia, Bingru & Roberts, Leigh, 2011. "Can implied forward mortgage rates predict future mortgage rates - recent New Zealand experience," Working Paper Series 1986, Victoria University of Wellington, School of Economics and Finance.
    7. Jawadi Fredj & Koubaa Yousra, 2004. "Threshold Cointegration between Stock Returns : An application of STECM Models," Econometrics 0412001, University Library of Munich, Germany.
    8. Chlibi Souhir & Jawadi Fredj & Sellami Mohamed, 2017. "Modeling threshold effects in stock price co-movements: a vector nonlinear cointegration approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 47-63, February.
    9. Michael Sager, 2006. "Explaining the persistence of deviations from PPP: a non-linear Harrod-Balassa-Samuelson effect?," Applied Financial Economics, Taylor & Francis Journals, vol. 16(1-2), pages 41-61.
    10. Kieran Farrelly & Ben Sanderson, 2005. "Modelling Regime Shifts in the City of London Office Rental Cycle," Journal of Property Research, Taylor & Francis Journals, vol. 22(4), pages 325-344, December.

    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. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    3. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    4. Clements, Michael P. & Galvao, Ana Beatriz, 2004. "A comparison of tests of nonlinear cointegration with application to the predictability of US interest rates using the term structure," International Journal of Forecasting, Elsevier, vol. 20(2), pages 219-236.
    5. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    6. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CREATES Research Papers 2013-32, Department of Economics and Business Economics, Aarhus University.
    7. Zanetti Chini, Emilio, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," International Journal of Forecasting, Elsevier, vol. 34(4), pages 711-732.
    8. Kim, Bong-Han & Chun, Sun-Eae & Min, Hong-Ghi, 2010. "Nonlinear dynamics in arbitrage of the S&P 500 index and futures: A threshold error-correction model," Economic Modelling, Elsevier, vol. 27(2), pages 566-573, March.
    9. Mainardi, Stefano, 2001. "Limited arbitrage in international wheat markets: threshold and smooth transition cointegration," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(3), pages 1-26.
    10. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
    11. Nicholas Taylor, 2007. "A New Econometric Model of Index Arbitrage," European Financial Management, European Financial Management Association, vol. 13(1), pages 159-183, January.
    12. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    13. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    14. Franses, Philip Hans & van Dijk, Dick, 2005. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," International Journal of Forecasting, Elsevier, vol. 21(1), pages 87-102.
    15. Michael J. Dueker & Katrin Wesche, 2001. "European business cycles: new indices and analysis of their synchronicity," Working Papers 1999-019, Federal Reserve Bank of St. Louis.
    16. Bekiros, Stelios & Avdoulas, Christos & Hassapis, Christis, 2018. "Nonlinear equilibrium adjustment dynamics and predictability of the term structure of interest rates," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 140-155.
    17. Byeongseon Seo, 2004. "Testing for Nonlinear Adjustment in Smooth Transition Vector Error Correction Models," Econometric Society 2004 Far Eastern Meetings 749, Econometric Society.
    18. Ayşen ARAÇ, 2015. "Nonlinear Dynamics in Term Structure of Interest Rates: Evidence from the Euro Area," Sosyoekonomi Journal, Sosyoekonomi Society, issue 23(26).
    19. Eliana González & Luis F. Melo & Viviana Monroy & Brayan Rojas, 2009. "A Dynamic Factor Model For The Colombian Inflation," Borradores de Economia 5273, Banco de la Republica.
    20. Dimitrakopoulos, Stefanos & Tsionas, Mike, 2019. "Ordinal-response GARCH models for transaction data: A forecasting exercise," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1273-1287.

    More about this item

    Keywords

    Econometric and statistical methods; Interest rates;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

    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:bca:bocawp:01-23. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.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.