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Mortgage rate predictability and consumer home-buying assessments

Author

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  • Hamid Baghestani

    (American University of Sharjah)

Abstract

This study aims to examine whether US consumer home-buying assessments can potentially help reduce the random walk prediction errors of mortgage rates. Forecast evaluations under flexible loss reveal that the random walk predictions for 1992–2020 imply asymmetric loss, meaning that they are of value to a user who assigns more (less) cost to over-predictions (under-predictions). Further results indicate that such survey measures as consumer home-buying attitudes and consumer opinion about interest rates can help improve the accuracy of the random walk predictions of mortgage rates. As such, we recommend that forecasters consider using such survey measures in predicting mortgage rates.

Suggested Citation

  • Hamid Baghestani, 2022. "Mortgage rate predictability and consumer home-buying assessments," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 593-603, July.
    • Handle: RePEc:spr:jecfin:v:46:y:2022:i:3:d:10.1007_s12197-022-09578-8
    DOI: 10.1007/s12197-022-09578-8
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    References listed on IDEAS

    as
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    2. Hamid Baghestani, 2016. "Interest rate movements and US consumers’ inflation forecast errors: is there a link?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(3), pages 623-630, July.
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    8. Soren T. Anderson & Ryan Kellogg & James M. Sallee & Richard T. Curtin, 2011. "Forecasting Gasoline Prices Using Consumer Surveys," American Economic Review, American Economic Association, vol. 101(3), pages 110-114, May.
    9. Baghestani, Hamid, 2009. "Forecasting in efficient bond markets: Do experts know better?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 624-630, October.
    10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    11. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    12. Mitchell, Karlyn & Pearce, Douglas K., 2007. "Professional forecasts of interest rates and exchange rates: Evidence from the Wall Street Journal's panel of economists," Journal of Macroeconomics, Elsevier, vol. 29(4), pages 840-854, December.
    13. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    14. Hamid Baghestani & Mohammad Arzaghi & Ilker Kaya, 2015. "On the accuracy of Blue Chip forecasts of interest rates and country risk premiums," Applied Economics, Taylor & Francis Journals, vol. 47(2), pages 113-122, January.
    15. Pesando, James E., 1981. "On forecasting interest rates : An efficient markets perspective," Journal of Monetary Economics, Elsevier, vol. 8(3), pages 305-318.
    16. Hamid Baghestani & Liliana Danila, 2014. "Interest Rate and Exchange Rate Forecasting in the Czech Republic: Do Analysts Know Better than a Random Walk?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 282-295, September.
    17. Hamid Baghestani, 2005. "Improving the Accuracy of Recent Survey Forecasts of the T-bill Rate," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 40(2), pages 36-40, April.
    18. Hamid Baghestani & Ilker Kaya, 2016. "Do financial indicators have directional predictability for US home sales?," Applied Economics, Taylor & Francis Journals, vol. 48(15), pages 1349-1360, March.
    19. Hamid Baghestani & Sehar Fatima, 2021. "Growth in US Durables Spending: Assessing the Impact of Consumer Ability and Willingness to Buy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 55-69, April.
    20. Hamid Baghestani, 2010. "Forecasting the 10‐year US treasury rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(8), pages 673-688, December.
    21. Baghestani, Hamid, 2015. "Predicting gasoline prices using Michigan survey data," Energy Economics, Elsevier, vol. 50(C), pages 27-32.
    22. Hamid Baghestani, 2017. "Do US consumer survey data help beat the random walk in forecasting mortgage rates?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1343017-134, January.
    23. Hamid Baghestani, 2019. "Long-term interest rate predictability: Exploring the usefulness of survey forecasts of growth and inflation," Cogent Economics & Finance, Taylor & Francis Journals, vol. 7(1), pages 1582317-158, January.
    24. Ibrahim Filiz & Thomas Nahmer & Markus Spiwoks & Kilian Bizer, 2019. "The accuracy of interest rate forecasts in the Asia-Pacific region: opportunities for portfolio management," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6309-6332, December.
    25. Hamid Baghestani & Woo Jung & Daniel Zuchegno, 2000. "On the information content of futures market and professional forecasts of interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 10(6), pages 679-684.
    26. Baghestani, Hamid & Marchon, Cassia, 2012. "An evaluation of private forecasts of interest rate targets in Brazil," Economics Letters, Elsevier, vol. 115(3), pages 352-355.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Mortgage rate; Random walk; Consumer survey data; Asymmetric loss; Orthogonality;
    All these keywords.

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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