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Weighted and Two Stage Least Squares Estimation of Semiparametric Truncated Regression Models

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Author Info
Shakeeb Khan (University of Rochester)
Arthur Lewbel () (Boston College)

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Abstract

This paper provides a root-n consistent, asymptotically normal weighted least squares estimator of the coefficients in a truncated regression model. The distribution of the errors is unknown and permits general forms of unknown heteroskedasticity. Also provided is an instrumental variables based two stage least squares estimator for this model, which can be used when some regressors are endogenous, mismeasured, or otherwise correlated with the errors. A simulation study indicates the new estimators perform well in finite samples. Our limiting distribution theory includes a new asymptotic trimming result addressing the boundary bias in first stage density estimation without knowledge of the support boundary.

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Publisher Info
Paper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 525.

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Length: 48 pages
Date of creation: 14 Feb 2002
Date of revision: 04 Sep 2006
Handle: RePEc:boc:bocoec:525

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Related research
Keywords: Semiparametric; Truncated Regression; Heteroscedasticity; Latent Variable Models; Endogenous Regressors.;

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Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Lee, Myoung-jae, 1989. "Mode regression," Journal of Econometrics, Elsevier, vol. 42(3), pages 337-349, November. [Downloadable!] (restricted)
  2. Lee, Myoung-jae, 1993. "Quadratic mode regression," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 1-19. [Downloadable!] (restricted)
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  3. Arthur Lewbel, 1998. "Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors," Econometrica, Econometric Society, vol. 66(1), pages 105-122, January.
  4. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September. [Downloadable!] (restricted)
  5. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July. [Downloadable!] (restricted)
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  6. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

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  2. David Jacho-Chávez, 2008. "k nearest-neighbor estimation of inverse density weighted expectations," Economics Bulletin, Economics Bulletin, vol. 3(48), pages 1-6. [Downloadable!]
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  4. Sophocles N. Brissimis & Manthos D. Delis & Nikolaos I. Papanikolaou, 2008. "Exploring the Nexus between Banking Sector Reform and Performance: Evidence from Newly Acceded EU Countries," Working Papers 73, Bank of Greece. [Downloadable!]
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  5. Arthur Lewbel, 2000. "Endogenous Selection Or Treatment Model Estimation," Boston College Working Papers in Economics 462, Boston College Department of Economics, revised 13 Jun 2007. [Downloadable!]
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  7. Delis, Manthos D & Molyneux, Philip & Pasiouras, Fotios, 2009. "Regulations and productivity growth in banking," MPRA Paper 13891, University Library of Munich, Germany. [Downloadable!]
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