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Regression Model for Proportions with Probability Masses at Zero and One

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  • Raffaella Calabrese

    (Geary Dynamics Lab, Geary Institute, University College Dublin)

Abstract

In many settings, the variable of interest is a proportion with high concentration of data at the boundaries. This paper proposes a regression model for a fractional variable with nontrivial probability masses at the extremes. In particular, the dependent variable is assumed to be a mixed random variable, obtained as the mixture of a Bernoulli and a beta random variables. The extreme values of zero and one are modelled by a logistic regression model. The values belonging to the interval (0,1) are assumed beta distributed and their mean and dispersion are jointly modelled by using two link functions. The regression model here proposed accommodates skewness and heteroscedastic errors. Finally, an application to loan recovery process of Italian banks is also provided.

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File URL: http://www.ucd.ie/geary/static/publications/workingpapers/gearywp201209.pdf
File Function: First version, 2012
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Bibliographic Info

Paper provided by Geary Institute, University College Dublin in its series Working Papers with number 201209.

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Length: 14 pages
Date of creation: 14 Mar 2012
Date of revision:
Handle: RePEc:ucd:wpaper:201209

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Keywords: proportions; mixed random variable; beta regression; skewness; heteroscedasticity;

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References

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  1. Joao A. Bastos, 2009. "Forecasting bank loans loss-given-default," CEMAPRE Working Papers 0901, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  2. Esmeralda A. Ramalho & Joaquim J.S. Ramalho & José M.R. Murteira, 2011. "Alternative Estimating And Testing Empirical Strategies For Fractional Regression Models," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 19-68, 02.
  3. Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
  4. Papke, Leslie E & Wooldridge, Jeffrey M, 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 619-32, Nov.-Dec..
  5. Grunert, Jens & Weber, Martin, 2009. "Recovery rates of commercial lending: Empirical evidence for German companies," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 505-513, March.
  6. Julie Agnew & Pierluigi Balduzzi & Annika Sundén, 2003. "Portfolio Choice and Trading in a Large 401(k) Plan," American Economic Review, American Economic Association, vol. 93(1), pages 193-215, March.
  7. Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
  8. Cook, Douglas O. & Kieschnick, Robert & McCullough, B.D., 2008. "Regression analysis of proportions in finance with self selection," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 860-867, December.
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