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Likelihood Estimation for Censored Random Vectors

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  • Wendelin Schnedler

    (University of Heidelberg, Department of Economics)

Abstract

This article shows how to construct a likelihood for a general class of censoring problems. This likelihood is proven to be valid, i.e. its maximiser is consistent and the respective root-n estimator is asymptotically efficient and normally distributed under regularity conditions. The method generalises ordinary maximum likelihood estimation as well as several standard estimators for censoring problems (e.g. tobit type I - tobit type V).

Suggested Citation

  • Wendelin Schnedler, 2005. "Likelihood Estimation for Censored Random Vectors," Working Papers 0417, University of Heidelberg, Department of Economics, revised Feb 2005.
    • Handle: RePEc:awi:wpaper:0417
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    File URL: http://www.uni-heidelberg.de/md/awi/forschung/dp417.pdf
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    References listed on IDEAS

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    Cited by:

    1. Wendelin Schnedler & Nina Lucia Stephan, 2020. "Revisiting a Remedy Against Chains of Unkindness," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(3), pages 347-364, July.
    2. Mauricio Villamizar-Villegas, 2016. "Identifying The Effects Of Simultaneous Monetary Policy Shocks," Contemporary Economic Policy, Western Economic Association International, vol. 34(2), pages 268-296, April.
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    4. Suiyao Chen & Nan Kong & Xuxue Sun & Hongdao Meng & Mingyang Li, 2019. "Claims data-driven modeling of hospital time-to-readmission risk with latent heterogeneity," Health Care Management Science, Springer, vol. 22(1), pages 156-179, March.
    5. Antonio F. Galvao & Carlos Lamarche & Luiz Renato Lima, 2013. "Estimation of Censored Quantile Regression for Panel Data With Fixed Effects," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1075-1089, September.
    6. Ramzi Suleiman & Yuval Samid, 2021. "Punishment Strategies across Societies: Conventional Wisdoms Reconsidered," Games, MDPI, vol. 12(3), pages 1-23, August.
    7. Tingting Yu & Lang Wu & Peter Gilbert, 2019. "New approaches for censored longitudinal data in joint modelling of longitudinal and survival data, with application to HIV vaccine studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 229-258, April.
    8. Xue, Hong & Mainville, Denise Y. & You, Wen & Nayga, Rodolfo M., Jr., 2009. "Nutrition Knowledge, Sensory Characteristics and Consumers’ Willingness to Pay for Pasture-Fed Beef," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49277, Agricultural and Applied Economics Association.
    9. Getachew A. Dagne, 2016. "A growth mixture Tobit model: application to AIDS studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1174-1185, July.
    10. Mònica González & Germà Coenders & Marc Saez & Ferran Casas, 2010. "Non-linearity, Complexity and Limited Measurement in the Relationship Between Satisfaction with Specific Life Domains and Satisfaction with Life as a Whole," Journal of Happiness Studies, Springer, vol. 11(3), pages 335-352, June.
    11. Servtka, Maros, 2009. "Separating reputation, social influence, and identification effects in a dictator game," European Economic Review, Elsevier, vol. 53(2), pages 197-209, February.
    12. Sabourin, Anne, 2015. "Semi-parametric modeling of excesses above high multivariate thresholds with censored data," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 126-146.
    13. Biørn, Erik & Wangen, Knut R., 2012. "New Taxonomies for Limited Dependent Variables Models," MPRA Paper 41461, University Library of Munich, Germany.
    14. Qian, Hang, 2009. "Estimating SUR Tobit Model while errors are gaussian scale mixtures: with an application to high frequency financial data," MPRA Paper 31509, University Library of Munich, Germany.

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    More about this item

    Keywords

    Censored variables; Limited dependent variables; Multivariate methods; Random censoring; Likelihood;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models

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