Estimating features of a distribution from binomial data
Arthur Lewbel,
Daniel McFadden and
Oliver Linton
Journal of Econometrics, 2011, vol. 162, issue 2, 170-188
Abstract:
We propose estimators of features of the distribution of an unobserved random variable W. What is observed is a sample of Y,V,X where a binary Y equals one when W exceeds a threshold V determined by experimental design, and X are covariates. Potential applications include bioassay and destructive duration analysis. Our empirical application is referendum contingent valuation in resource economics, where one is interested in features of the distribution of values W (willingness to pay) placed by consumers on a public good such as endangered species. Sample consumers with characteristics X are asked whether they favor (with Y=1 if yes and zero otherwise) a referendum that would provide the good at a cost V specified by experimental design. This paper provides estimators for quantiles and conditional on X moments of W under both nonparametric and semiparametric specifications.
Keywords: Willingness; to; pay; Contingent; valuation; Discrete; choice; Binomial; response; Bioassay; Destructive; duration; testing; Semiparametric; Nonparametric; Latent; variable; models (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(10)00210-1
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Estimating Features of a Distribution from Binomial Data (2010) 
Working Paper: Estimating features of a distribution from binomial data (2006) 
Working Paper: Estimating features of a distribution from binomial data (2001) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:162:y:2011:i:2:p:170-188
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().