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

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  • 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
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    Cited by:

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    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Jawadi Fredj & Koubaa Yousra, 2004. "Threshold Cointegration between Stock Returns : An application of STECM Models," Econometrics 0412001, University Library of Munich, Germany.
    7. 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.
    8. Jan Willem van den End, 2011. "Statistical evidence on the mean reversion of interest rates," DNB Working Papers 284, Netherlands Central Bank, Research Department.
    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.

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    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

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