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Comparative Analysis of Australian Residential Mortgage (Home Loan) Interest Rates

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  • Harry M. Karamujic

    (University of Melbourne, Victoria 3010 Australia, Tel: +61 3 8344 3030; fax: +61 3 8344 5532, email: harryk@unimelb.edu.au)

Abstract

The contention of this article is to ascertain whether or not the selected Australian home loan interest rates exhibit the expected cyclical and seasonal variations, and whether seasonality, if present, is stochastic or deterministic. The article uses a structural time series modelling approach and product-level home loan interest rates data from two major banks in Australia, National Australia Bank (NAB) and Commonwealth Bank of Australia (CBA).1 The modelling results overall confirm cyclicality of the selected home loan interest rates. Although most of the variables analysed also show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

Suggested Citation

  • Harry M. Karamujic, 2011. "Comparative Analysis of Australian Residential Mortgage (Home Loan) Interest Rates," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 5(3), pages 311-341, August.
    • Handle: RePEc:sae:mareco:v:5:y:2011:i:3:p:311-341
    DOI: 10.1177/097380101100500302
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    References listed on IDEAS

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    1. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, January.
    2. Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
    3. Luci Ellis & Laura Berger-Thomson, 2004. "Housing Construction Cycles and Interest Rates," Econometric Society 2004 Australasian Meetings 335, Econometric Society.
    4. Harvey, Andrew & Scott, Andrew, 1994. "Seasonality in Dynamic Regression Models," Economic Journal, Royal Economic Society, vol. 104(427), pages 1324-1345, November.
    5. Frank Campbell & Eleanor Lewis, 1998. "What Moves Yields in Australia?," RBA Research Discussion Papers rdp9808, Reserve Bank of Australia.
    6. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    7. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.
    8. Khalid Al-Saad & Imad Moosa, 2005. "Seasonality in stock returns: evidence from an emerging market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(1), pages 63-71.
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