SBCV: Single Bounded Contingent Valuation

In umor/ContingentValuation: Analyse Data from Contingent Valuation Method Surveys

Description

The function SBCV estimates coefficients from a single-bounded contingent valuation survey. It basically is a probit regression.

Usage

SBCV(x, ...)
## Default S3 method:
SBCV(x,y,z, data, initpar, method, functionalForm, ...)
## S3 method for class 'formula'
SBCV(formula, data=list(), initpar=NULL, method=NULL, functionalForm="linear", ...)
## S3 method for class 'SBCV'
summary(object, ...)
## S3 method for class 'SBCV'
print(x, ...)
## S3 method for class 'summary.SBCV'
print(x, ...)

Arguments

y	a vector with the answer to the 'yes/no' question. It must be 1 if the answer was 'yes' and and 0 if the answer was 'no'.
x	a vector the the bids.
z	additional, subject specific, explaining variables
formula	a symbolic description of the model to estimate. See details below.
data	an optional data.frame containing the variables in the model.
initpar	a vector of initial parameters for logLik() function from the logLik-package. The vector consist of an initial parameter for the bid, the intercept and each of the explaining variables, in this order. If NULL, the initial values are estimated with the glm() function from the stats-package.
method	a character determining the optimization method in the function logLik(). If NULL, "Newton-Raphson" method is used. For alternatives and details see the documentation of logLik()
functionalForm	Either "linear", "loglinearWTP" or "loglinearRUM".
object	an object of class "SBCV", i.e., a fitted model
...	currently not used

Details

The formula must be given in the following forms: For linear models

yes ~ bid | z1 + z2 + ... + zn

where yes is the reply to the survey question. This numeric variable are 1 if the subject answered 'yes' and 0 if the subject answered 'no'. For loglinearWTP models

yes ~ bid | z1 + z2 + ... + zn

where a bid variable

log(bid)

is generated. For loglinearRUM models

yes ~ bid + income | z1 + z2 + ... + zn

where a bid variable of the form

log((income-bid)/income)

is generated.

bid is a numeric variables which is the bid offered to the subject. z1 tozn are additonal explaining, subject specific, variables.

For identification the variance is fixed to one.

Value

An object of class "SBCV", basically a list containing

coefficients	a named vector of coefficients
vcov	covariance matrix of coefficients
LogLik	log-likelihood value
df	Degrees of freedom
model	data used to estimate the function
functionalForm	The functional form used for the estimation

Author(s)

Ulrich B. Morawetz

References

Haab, T.C. and McConnell, K.E. (2003), Valuing Environmental and Natural Resources. The Econometrics of non-market Valuation. Cheltenham, UK: Edward Elgar

Examples

 data("maizeWTP")
 require(Formula)

data("maizeWTP")

# example
maizeSBCV<- SBCV(yuYes2~yuBid2|age+gender+experimenter , data=maizeWTP)
maizeSBCV

umor/ContingentValuation documentation built on Nov. 5, 2019, 2:16 p.m.