Discrete choice models with response transformation : An application to beverage choice

  • Authors

    • Sunil K Sapra Department of Economics and StatisticsCalifornia State University5151 State University DrLos Angeles, CA 90032, USA
    2015-09-25
    https://doi.org/10.14419/ijaes.v3i2.5317
  • Box-Cox Transformation, Categorical Response Data, Logit Model, Generalized Linear Models, Link Functions.

  • The paper studies various response transformation models for discrete choice and categorical data. These response transformation models are fitted to binary response data on beverage choice. Several models are compared, and the best model is selected using AICs and deviances. The transformations include extensions of the widely used Box-Cox transformation to Normality for continuous data to categorical data. The econometric techniques employed in the paper are widely applicable to the analysis of count, binary response, and duration types of data encountered in business and economics.

    Author Biography

    • Sunil K Sapra, Department of Economics and StatisticsCalifornia State University5151 State University DrLos Angeles, CA 90032, USA

      Profesor, Department of Economics and Statistics, California State University, Los Angeles, USA

      Sunil Sapra, earned both his M.Phil. and Ph.D. in Econometrics at Columbia University, New York. He is currently a Professor of Economics and Statistics at CaliforniaStateUniversity, Los Angeles. Prior to joining Cal. State, LA, he taught at State University of New York, Buffalo and held the prestigious ASA/NSF/Census Research Fellowship (1989-90) at the Bureau of the Census, Washington, D. C. He is an expert in Business Statistics at the Westlaw Roundtable Group. He has published more than 70 articles in some of the most prestigious statistics and econometrics journals. His research on semi-parametric econometrics, missing data problems, nonlinear statistical and econometric models, robust statistical procedures, limited dependent variables and duration data analysis has been published in Econometric Theory, The American Statistician, International Journal of Advanced Statistics and Probability, Statistica Neerlandica, Statistical Papers, Sankhya, Economics e-journal, Bulletin of Economic Research, Economics Letters, Applied Economics Letters, and Empirical Economics Letters. He serves on the editorial boards of several statistics and economics journals. His research has been cited in statistics and econometrics textbooks and journals as well as a widely-used volume on statistical distributions. He received the Outstanding Professor Award from California State University, Los Angeles in 2003 for excellence in teaching and research. He has been listed in Who’s Who among American Teachers and Educators (11th Edition, 2007).

  • References

    1. [1] Aranda-Ordaz F (1981) On Two Families of Transformations to Additivity for Binary Response Data. Biometrika. 68, 357–363. http://dx.doi.org/10.1093/biomet/68.2.357.

      [2] Box, GEP. & Cox DR (1964) an Analysis of Transformations. Journal of the Royal Statistical Society, Series B, 26, 211-252

      [3] Carrol, RJ & Ruppert D (1988) Transformations and Weighting in Regression, Chapman and Hall: New York http://dx.doi.org/10.1007/978-1-4899-2873-3.

      [4] Doebler P, Holling H, Boehning D (2012) A Mixed Model Approach to Meta-Analysis of Diagnostic Studies with Binary Test Outcome. Psychological Methods, 17(3), 418–436. http://dx.doi.org/10.1037/a0028091.

      [5] Guerrero V, Johnson R (1982) Use of the Box-Cox Transformation with Binary Response Models. Biometrika, 69, 309–314. http://dx.doi.org/10.1093/biomet/69.2.309.

      [6] Hill, RC, WE Griffiths, and GG Lim (2011) Principles of Econometrics, New York: Wiley.

      [7] Koenker R (2006) Parametric Links for Binary Response. R News, 6, 32–34.

      [8] Koenker R & Yoon J (2009) Parametric Links for Binary Choice Models: A Fisherian-Bayesian Colloquy. Journal of Econometrics, 152, 120–130. http://dx.doi.org/10.1016/j.jeconom.2009.01.009.

      [9] McCullagh, P & Nelder RA (1989) Generalized Linear Models, Chapman and Hall: New York. http://dx.doi.org/10.1007/978-1-4899-3242-6.

      [10] Piepho H (2003) the Folded Exponential Transformation for Proportions. Journal of the Royal Statistical Society D, 52, 575–589. http://dx.doi.org/10.1046/j.0039-0526.2003.00509.x.

      [11] Pregibon D (1980) Goodness of Link Tests for Generalized Linear Models. Journal of the Royal Statistical Society C, 29, 15–23. http://dx.doi.org/10.2307/2346405.

      [12] Rocke DM (1993) On the Beta Transformation Family. Technometrics, 35, 73–81. http://dx.doi.org/10.1080/00401706.1993.10484995.

      [13] Shin, Y (2008) Semiparametric estimation of the Box-Cox transformation model, The Econometrics Journal, 11, 517-537. http://dx.doi.org/10.1111/j.1368-423X.2008.00255.x.

      [14] Zeileis, A, Koenker R & Doebler P (2014) R-package glmx.

  • Downloads

  • How to Cite

    Sapra, S. K. (2015). Discrete choice models with response transformation : An application to beverage choice. International Journal of Accounting and Economics Studies, 3(2), 135-140. https://doi.org/10.14419/ijaes.v3i2.5317