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Nonparametric vs parametric binary choice models: An empirical investigation

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  • Bontemps, Christophe
  • Racine, Jeffrey S.
  • Simioni, Michel

Abstract

The estimation of conditional probability distribution functions (PDFs) in a kernel nonparametric framework has recently received attention. As emphasized by Hall, Racine and Li (2004), these conditional PDFs are extremely useful for a range of tasks including modelling and predicting consumer choice. The aim of this paper is threefold. First, we implement nonparametric kernel estimation of PDF with a binary choice variable and both continuous and discrete explanatory variables. Second, we address the issue of the performances of this nonparametric estimator when compared to a classic on-the-shelf parametric estimator, namely a probit. We propose to evaluate these estimators in terms of their predictive performances, in the line of the recent "revealed performance" test proposed by Racine and Parmeter (2009). Third, we provide a detailed discussion of the results focusing on environmental insights provided by the two estimators, revealing some patterns that can only be detected using the nonparametric estimator.

Suggested Citation

  • Bontemps, Christophe & Racine, Jeffrey S. & Simioni, Michel, 2009. "Nonparametric vs parametric binary choice models: An empirical investigation," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49286, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea09:49286
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    File URL: http://purl.umn.edu/49286
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    References listed on IDEAS

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    1. BONTEMPS Christophe & NAUGES Céline, 2006. "Carafe ou bouteille ? Le rôle de la qualité de l'environnement dans la décision du consommateur," LERNA Working Papers 06.07.200, LERNA, University of Toulouse.
    2. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355.
    3. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    4. Christophe Bontemps & Céline Nauges, 2010. "Carafe ou bouteille ? Le rôle de la qualité de l’environnement dans la décision du consommateur," INRA Sciences Sociales, INRA Department of Economics.
    5. Li, Qi & Racine, Jeff, 2003. "Nonparametric estimation of distributions with categorical and continuous data," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 266-292, August.
    6. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643.
    7. Briesch R.A. & Chintagunta P.K. & Matzkin R.L., 2002. "Semiparametric Estimation of Brand Choice Behavior," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 973-982, December.
    8. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    9. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
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    Cited by:

    1. Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da & Cerqueira, Pedro A., 2015. "Evaluating the market splitting determinants: evidence from the Iberian spot electricity prices," Energy Policy, Elsevier, vol. 85(C), pages 218-234.
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, Elsevier.

    More about this item

    Keywords

    Binary choice models; Nonparametric estimation; specification test; tap water demand; Research Methods/ Statistical Methods;

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