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Pairwise-Difference Rank Estimation of the Transformation Model

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  • Abrevaya, Jason

Abstract

This article considers pairwise-difference rank estimators of the coefficient vector in a transformation model. These estimators, like other existing rank estimators, require no subjective bandwidth choice. Monte Carlo simulations, numerical asymptotic efficiency comparisons, and two empirical applications suggest that the proposed estimators perform well in comparison with existing semiparametric estimators.

Suggested Citation

  • Abrevaya, Jason, 2003. "Pairwise-Difference Rank Estimation of the Transformation Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 437-447, July.
    • Handle: RePEc:bes:jnlbes:v:21:y:2003:i:3:p:437-47
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    Cited by:

    1. Esmeralda A. Ramalho & Joaquim J. S. Ramalho, 2017. "Moment-based estimation of nonlinear regression models with boundary outcomes and endogeneity, with applications to nonnegative and fractional responses," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 397-420, April.
    2. Kharratzadeh, Milad & Coates, Mark, 2017. "Semi-parametric order-based generalized multivariate regression," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 89-102.
    3. Caiyun Fan & Wenbin Lu & Rui Song & Yong Zhou, 2017. "Concordance-assisted learning for estimating optimal individualized treatment regimes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1565-1582, November.
    4. Subbotin, Viktor, 2007. "Asymptotic and bootstrap properties of rank regressions," MPRA Paper 9030, University Library of Munich, Germany, revised 20 Mar 2008.
    5. Kortelainen, Mika, 2008. "Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies," MPRA Paper 9257, University Library of Munich, Germany.
    6. Youngki Shin & Zvezdomir Todorov, 2021. "Exact computation of maximum rank correlation estimator," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 589-607.
    7. Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany.
    8. Yu, Tao & Li, Pengfei & Chen, Baojiang & Yuan, Ao & Qin, Jing, 2023. "Maximum pairwise-rank-likelihood-based inference for the semiparametric transformation model," Journal of Econometrics, Elsevier, vol. 235(2), pages 454-469.
    9. Xu, Wenchao & Zhang, Xinyu & Liang, Hua, 2024. "Linearized maximum rank correlation estimation when covariates are functional," Journal of Multivariate Analysis, Elsevier, vol. 202(C).

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