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

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  • Ying Liu
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    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.

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    Bibliographic Info

    Paper provided by Bank of Canada in its series Working Papers with number 01-23.

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    Length: 32 pages
    Date of creation: 2001
    Date of revision:
    Handle: RePEc:bca:bocawp:01-23

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    Related research

    Keywords: Econometric and statistical methods; Interest rates;

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    1. 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 465-84, November.
    2. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
    4. 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 725-45, September.
    5. 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 466-72, October.
    6. 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 301-32.
    7. 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.
    8. Lundbergh, Stefan & Teräsvirta, Timo & van Dijk, Dick, 2000. "Time-Varying Smooth Transition Autoregressive Models," Working Paper Series in Economics and Finance 376, Stockholm School of Economics.
    9. 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.
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    Cited by:
    1. 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.
    2. Jack R. Rogers, 2013. "Monetary Transmission to UK Retail Mortgage Rates before and after August 2007," Discussion Papers 1307, Exeter University, Department of Economics.
    3. 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.

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