In the single-bounded dichotomous choice CV that was first proposed by Bishop and Heberlein (1979) respondents are requested to answer a question like the following:
If the environmental policy burdens you with USD $X$ annually, would you agree or disagree to it? This format, respondents only states "yes (I agree)" or "no (I disagree)," meaning whether their willingness to pay (WTP) is greater or lower than the bid (USD $X$) they are offered.
The double-bounded dichotomous choice CV was proposed by Hanemann (1985) and Carson (1985) to improve the efficiency of single-bounded dichotomous choice CV. In the CV format, respondents are requested to answer the second (follow-up) question just after they answer the single-bounded dichotomous choice CV style question (the first/initial question). An example of double-bounded dichotomous choice CV questions is as follows ($Xl < X < Xh$):
First question If the environmental policy burdens you with USD $X$ annually, would you agree or disagree to it?
Second question for the respondents who agree to the policy in the first question If the amount of tax is USD $Xh$, would you agree or disagree to it?
Second question for the respondents who disagree to the policy in the first question If the amount of tax is USD $Xl$, would you agree or disagree to it?
In the double-bounded dichotomous choice CV question, there are four possible response
outcomes: (yes, yes); (yes, no); (no, yes); and (no, no). If the respondent $i$'s answer
is (yes, yes), the analyst can tell $WTPi > Xh$ ($WTPi$ is the WTP of the
respondent $i$). Similarly, (yes, no) means $X < WTPi < Xh$, (no, yes) means
$Xl < WTPi < X$, and (no, no) means $WTPi There are two ways of estimating WTP from the single- and double-bounded dichotomous choice CV:
parametric and nonparametric approaches. In this package, the functions Confidence intervals for the estimates of WTPs are constructed by two methods.
These are the Krinsky and Robb (1986, 1990)'s method and the bootstrap one.
The former is implemented by Both of the methods rely on simulation techniques with different settings. Usually,
a bootstrap method takes much longer time than the Krinsky and Robb's method does.
It has been pointed out that each method has both advantages and disadvantages, see,
for instance, the discussions in Hole (2007) and the references therein. Functions for nonparametric approaches are also included in the package. sbchoice
and dbchoice, which are based on the utility difference approach (Hanemann, 1984),
are developed for the parametric approach to single- and double-bounded dichotomous choice data,
respectively. krCI while the latter by bootCI. kristrom
(Kristrom, 1990) and turnbull.sb (Carson and Steinberg, 1990) are designed for
analyses for single-bounded dichotomous choice data whereas turnbull.db
(Carson and Hanemann, 2005) for double-bounded ones.
Carson RT (1985).
Carson RT, Hanemann WM (2005).
Carson RT, Steinberg D (1990).
Croissant Y (2011).
Fay MP, Shaw PA (2010).
Gentleman R, Vandal A (2011).
Icens: NPMLE for Censored and Truncated Data.
Rpackage version 1.24.0,
Hanemann, WM (1984).
Hanemann WM (1985).
Hole AR (2007).
Krinsky I, Robb AL (1986).
Krinsky I, Robb AL (1990).
Kristr"{o}m B (1990).
## Installation of DCchoice along with dependent packages is carried out
## by the following lines of code:
install.packages("DCchoice",
repos = c("http://R-Forge.R-project.org",
"http://www.bioconductor.org/packages/release/bioc",
"http://cran.rstudio.com/"),
dep = TRUE)
## For Mac and Unix/Linux users, add the option argument 'type="source"'.Run the code above in your browser using DataLab