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Estimating features of a distribution from binomial data

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Author Info

  • Arthur Lewbel

    (Institute for Fiscal Studies and Boston College)

  • Oliver Linton

    ()
    (Institute for Fiscal Studies and London School of Economics)

  • Daniel McFadden

    ()
    (Institute for Fiscal Studies and University of California, Berkeley)

Abstract

A statistical problem that arises in several fields is that of estimating the features of an unknown distribution, which may be conditioned on covariates, using a sample of binomial observations on whether draws from this distribution exceed threshold levels set by experimental design. One application is destructive duration analysis, where the process is censored at an observation test time. Another is referendum contingent valuation in resource economics, where one is interested in features of the distribution of values placed by consumers on a public good such as endangered species. Sample consumers are asked whether they would vote for a referendum that would provide the good at a cost speci…ed by experimental design. This paper provides estimators for moments and quantiles of the unknown distribution in this problem.

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File URL: http://cemmap.ifs.org.uk/wps/cwp0107.pdf
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Bibliographic Info

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP07/01.

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Length: 32 pp.
Date of creation: Dec 2001
Date of revision:
Handle: RePEc:ifs:cemmap:07/01

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  1. Arthur Lewbel, 1999. "Semiparametric Qualitative Response Model Estimation with Unknown Heteroskedasticity or Instrumental Variables," Boston College Working Papers in Economics 454, Boston College Department of Economics.
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  3. Chen, Heng Z. & Randall, Alan, 1997. "Semi-nonparametric estimation of binary response models with an application to natural resource valuation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 323-340.
  4. Donald Green & Karen Jacowitz & Daniel Kahneman & Daniel McFadden, 1995. "Referendum Contingent Valuation, Anchoring, and Willingness to Pay for Public Goods," Working Papers _010, University of California at Berkeley, Econometrics Laboratory Software Archive.
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