Rank estimation of a transformation model with observed truncation
AbstractThis paper introduces rank estimators for a general transformation model with observable truncation points. The estimators, which are modified versions of the rank estimators of Han (1987) and Cavanagh and Sherman (1998), are asymptotically normal and require no bandwidth choice. Log-concavity of the error disturbance?s survival function is a sufficient condition for the associated monotonicity conditions. Monte Carlo simulations investigate the estimators? behavior for various sample sizes.
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Bibliographic InfoArticle provided by Royal Economic Society in its journal The Econometrics Journal.
Volume (Year): 2 (1999)
Issue (Month): 2 ()
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- Chen, Songnian & Zhou, Xianbo, 2012. "Semiparametric estimation of a truncated regression model," Journal of Econometrics, Elsevier, vol. 167(2), pages 297-304.
- Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Discussion Paper 2013-062, Tilburg University, Center for Economic Research.
- Subbotin, Viktor, 2007. "Asymptotic and bootstrap properties of rank regressions," MPRA Paper 9030, University Library of Munich, Germany, revised 20 Mar 2008.
- Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, vol. 136(1), pages 251-280, January.
- Sule Alan & Bo E. Honoré & Luojia Hu & Søren Leth-Petersen, 2011. "Estimation of panel data regression models with two-sided censoring or truncation," Working Paper Series WP-2011-08, Federal Reserve Bank of Chicago.
- Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany.
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