"Willingness to Pay" for fracregmlogit models

Evaluate the "Willingness to Pay" given a set of arbitrary values for outcome variables. Usually used for policy evaluations where the total magnitude of marginal change matters.

Usage

wtp(object, wtp.vec, varlist = NULL, indv.obs = FALSE)

Arguments

object: A fracregmlogit.pe object.
wtp.vec: A numeric vector containing the arbitrary outcome values to be evaluated for each choice j.
varlist: A string vector which provides the names of variables to calculate the wtp for. If missing, all variables in the object will be calculated.
indv.obs: A logical value indicating whether to return individual observations.

Value

A "fracregmlogit.wtp" object containing the estimates, standard error, z-stats, and p-value.

Details

This function calculates the aggregate effect of a variable on the "willingness to pay" by linearly multiplying the average partial effect with ex-ante (arbitrary) willingness to pay numbers associated with each choice.

Suppose there are three choices A, B, C, each with a willingness to pay (or cost, profit, budget), of 100, 200, and 300. The discrete effects of variable X on A, B and C are 0.5, 0.5, and -1, with standard errors 0.2, 0.3 and 0.5. The aggregated discrete effect of X on the total willingness to pay (or cost), is thus 100*0.5 + 200*0.5 + 300*(-1) = -150. The standard error can also be calculated to be 162.8, assuming that the standard error is independent. A simple z-test is provided to test whether the aggregate effect is different from zero.

Note that if the input fracregmlogit.pe object has no standard error computation, then no standard error will be computed for the willingness to pay.

Examples

# \donttest{
data("fracreg_spending")
X = fracreg_spending[,2:5]
y = fracreg_spending[,6:11]
results1 = fracregmlogit(y, X)
pe = fracregmlogit.pe(results1)
# Assuming arbitrary WTP values for the 6 choices
wtp_est = wtp(pe, wtp.vec = c(1, 2, 3, 4, 5, 6), varlist = "houseval")
summary(wtp_est)
#> 
#> -------------------------------------------------------------------------------- 
#>                                Willingness to Pay 
#> -------------------------------------------------------------------------------- 
#>                     Fractional multinomial logit regression 
#> -------------------------------------------------------------------------------- 
#> 
#> Note: Krinsky-Robb standard error calculated
#>          Coefficient Std. Error z value Pr(>|z|)
#> houseval   -0.078693   0.120347 -0.6539   0.5132
#> 
#> -------------------------------------------------------------------------------- 
#>                          Run Date: 2026-08-08 15:50:34 
#> -------------------------------------------------------------------------------- 
#> 
# }