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A Neural Network Analysis of Mortgage Choice

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  • G. Grudnitski
  • A. Quang Do
  • J. D. Shilling

Abstract

There exists today an unanswered question as to whether, and the degree to which, borrower characteristics impact the choice between fixed and adjustable rate mortgages. In this paper, we apply a neural network analysis to supply evidence that answers this question. We find evidence that the characteristics of a borrower's net worth, marital status and education level and whether a co‐borrower is involved contribute in a significant way to the neural network's ability to determine mortgage choice. Further, we show how, because of the facility of neural networks in modeling intrasample differences, they achieve material and statistically significant accuracy gains over qualitative choice models in predicting whether a borrower will choose a fixed or adjustable rate mortgage.

Suggested Citation

  • G. Grudnitski & A. Quang Do & J. D. Shilling, 1995. "A Neural Network Analysis of Mortgage Choice," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(2), pages 127-135, June.
    • Handle: RePEc:wly:isacfm:v:4:y:1995:i:2:p:127-135
    DOI: 10.1002/j.1099-1174.1995.tb00085.x
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    References listed on IDEAS

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    1. Brueckner, Jan K & Follain, James R, 1988. "The Rise and Fall of the ARM: An Econometric Analysis of Mortgage Choice," The Review of Economics and Statistics, MIT Press, vol. 70(1), pages 93-102, February.
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    Cited by:

    1. Dungey, Mardi & Doko Tchatoka, Firmin & Yanotti, María B., 2018. "Endogeneity in household mortgage choice," Economic Modelling, Elsevier, vol. 73(C), pages 30-44.

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