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Estimation With Censored Regressors: Basic Issues

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  • Roberto Rigobon
  • Thomas M. Stoker

Abstract

We study issues that arise for estimation of a linear model when a regressor is censored. We discuss the efficiency losses from dropping censored observations, and illustrate the losses for bound censoring. We show that the common practice of introducing a dummy variable to "correct for" censoring does not correct bias or improve estimation. We show how censored observations generally have zero semiparametric information, and we discuss implications for estimation. We derive the likelihood function for a parametric model of mixed bound-independent censoring, and apply that model to the estimation of wealth effects on consumption. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 48 (2007)
Issue (Month): 4 (November)
Pages: 1441-1467

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Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1441-1467

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Cited by:
  1. Kilian, Lutz & Vigfusson, Robert J., 2009. "Pitfalls in Estimating Asymmetric Effects of Energy Price Shocks," CEPR Discussion Papers 7284, C.E.P.R. Discussion Papers.
  2. John Gilbert & Reza Oladi, 2011. "Net Campaign Contributions, Agricultural Interests, and Votes on Liberalizing Trade with China," Working Papers 2011-02, Utah State University, Department of Economics.
  3. Gumpert, Anna & Hines Jr., James R. & Schnitzer, Monika, 2012. "The use of tax havens in exemption regimes," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 381, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
  4. Murasko, Jason E., 2009. "Socioeconomic status, height, and obesity in children," Economics & Human Biology, Elsevier, vol. 7(3), pages 376-386, December.
  5. Tsimikas, John V. & Bantis, Leonidas E. & Georgiou, Stelios D., 2012. "Inference in generalized linear regression models with a censored covariate," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1854-1868.
  6. Jeon, Jin Q. & Ligon, James A., 2011. "How much is reasonable? The size of termination fees in mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 17(4), pages 959-981, September.
  7. Bernhardt, Paul W. & Wang, Huixia Judy & Zhang, Daowen, 2014. "Flexible modeling of survival data with covariates subject to detection limits via multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 81-91.

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