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Applying the copula approach to sample selection modelling

Author

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  • Margarita Genius
  • Elisabetta Strazzera

Abstract

The limited availability of tractable multivariate distributions undermines the validity of the standard parametric approach to sample selection modelling. Copula distributions can be very useful in situations where the applied researcher has a prior on the distributional form of the margins, since the modelling of the latter is separated from that of the dependence structure. The present article first presents an application to female work data. Afterwards, the approach is analysed in an application to contingent valuation data on recreational values of forests. It is shown that the copula approach is especially beneficial in case of strong departures from the hypothesis of normality.

Suggested Citation

  • Margarita Genius & Elisabetta Strazzera, 2008. "Applying the copula approach to sample selection modelling," Applied Economics, Taylor & Francis Journals, vol. 40(11), pages 1443-1455.
  • Handle: RePEc:taf:applec:v:40:y:2008:i:11:p:1443-1455
    DOI: 10.1080/00036840600794348
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    Citations

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    Cited by:

    1. Naveen Eluru & Chandra Bhat & Ram Pendyala & Karthik Konduri, 2010. "A joint flexible econometric model system of household residential location and vehicle fleet composition/usage choices," Transportation, Springer, vol. 37(4), pages 603-626, July.
    2. Jörg Schwiebert, 2016. "Evidence on copula-based double-hurdle models with flexible margins," Empirical Economics, Springer, vol. 51(1), pages 245-289, August.
    3. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    4. Marra, Giampiero & Wyszynski, Karol, 2016. "Semi-parametric copula sample selection models for count responses," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 110-129.
    5. Pigini Claudia, 2015. "Bivariate Non-Normality in the Sample Selection Model," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-22, January.
    6. Chhorn, Theara & Chhorn, Dina, 2017. "Modelling Linkage of Globalization and Financial Development to Human Development in CLMV Region," MPRA Paper 84878, University Library of Munich, Germany, revised 01 Nov 2017.
    7. Jörg Schwiebert, 2016. "Multinomial choice models based on Archimedean copulas," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(3), pages 333-354, July.
    8. Claudia PIGINI, 2012. "Of Butterflies and Caterpillars: Bivariate Normality in the Sample Selection Model," Working Papers 377, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute for the Study of Labor (IZA).
    10. Sener, Ipek N. & Reeder, Phillip R., 2014. "An integrated analysis of workers’ physically active activity and active travel choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 381-393.
    11. repec:jss:jstsof:v:071:i06 is not listed on IDEAS
    12. Schwiebert, Jörg, 2012. "Analyzing the Composition of the Female Workforce - A Semiparametric Copula Approach," Hannover Economic Papers (HEP) dp-503, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

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