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Distribution-free estimation with interval-censored contingent valuation data: troubles with Turnbull?
by
Day, Brett
in
Algorithms
/ Censorship
/ Contingencies
/ Contingent valuation
/ Convergence
/ Data
/ Elicitation
/ Environmental economics
/ Estimates
/ Estimating techniques
/ Estimation
/ Interval-censored data
/ Mathematical models
/ Maximum likelihood method
/ Monte Carlo method
/ Monte Carlo simulation
/ Nonparametric maximum likelihood
/ Polls & surveys
/ Population
/ Random variables
/ Research methods
/ Respondents
/ Statistical analysis
/ Studies
/ surveys
/ Turnbull’s self-consistent algorithm
/ Valuation
/ Willingness to pay
2007
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Distribution-free estimation with interval-censored contingent valuation data: troubles with Turnbull?
by
Day, Brett
in
Algorithms
/ Censorship
/ Contingencies
/ Contingent valuation
/ Convergence
/ Data
/ Elicitation
/ Environmental economics
/ Estimates
/ Estimating techniques
/ Estimation
/ Interval-censored data
/ Mathematical models
/ Maximum likelihood method
/ Monte Carlo method
/ Monte Carlo simulation
/ Nonparametric maximum likelihood
/ Polls & surveys
/ Population
/ Random variables
/ Research methods
/ Respondents
/ Statistical analysis
/ Studies
/ surveys
/ Turnbull’s self-consistent algorithm
/ Valuation
/ Willingness to pay
2007
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Do you wish to request the book?
Distribution-free estimation with interval-censored contingent valuation data: troubles with Turnbull?
by
Day, Brett
in
Algorithms
/ Censorship
/ Contingencies
/ Contingent valuation
/ Convergence
/ Data
/ Elicitation
/ Environmental economics
/ Estimates
/ Estimating techniques
/ Estimation
/ Interval-censored data
/ Mathematical models
/ Maximum likelihood method
/ Monte Carlo method
/ Monte Carlo simulation
/ Nonparametric maximum likelihood
/ Polls & surveys
/ Population
/ Random variables
/ Research methods
/ Respondents
/ Statistical analysis
/ Studies
/ surveys
/ Turnbull’s self-consistent algorithm
/ Valuation
/ Willingness to pay
2007
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Distribution-free estimation with interval-censored contingent valuation data: troubles with Turnbull?
Journal Article
Distribution-free estimation with interval-censored contingent valuation data: troubles with Turnbull?
2007
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Overview
Contingent valuation (CV) surveys frequently employ elicitation procedures that return interval-censored data on respondents’ willingness to pay (WTP). Almost without exception, CV practitioners have applied Turnbull’s self-consistent algorithm to such data in order to obtain nonparametric maximum likelihood (NPML) estimates of the WTP distribution. This paper documents two failings of Turnbull’s algorithm; (1) that it may not converge to NPML estimates and (2) that it may be very slow to converge. With regards to (1) we propose starting and stopping criteria for the algorithm that guarantee convergence to the NPML estimates. With regards to (2) we present a variety of alternative estimators and demonstrate, through Monte Carlo simulations, their performance advantages over Turnbull’s algorithm. Copyright Springer Science+Business Media, Inc. 2007
Publisher
European Association of Environmental and Resource Economists,Springer Nature B.V
Subject
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