Hi everyone. I had a question regarding WTP estimations using two different packages. To my understanding, using mlogit allows me to estimate WTP in preference-space, while logitr directly in space. I tried to do both but the coefficients are 1) very dissimilar and 2) way to high/low (for reference, the price range in my data goes from 0 - for the opt-out option- to 30). What could be causing this?
mxl_base <- mlogit(
RES ~ ASC_none + ASC_organic + ASC_plant + ASC_synthetic + price + CO2_A + CO2_B + Origin_Swiss|0,
data = mdata,
rpar = c(ASC_organic="n",ASC_synthetic= "n",ASC_plant="n"),
R=100,
halton = NA,
panel = TRUE,
reflevel = "conventional")
mwtp(output = mxl_base, monetary.variables = c("price"),nonmonetary.variables = c(
"CO2_A", "CO2_B", "Origin_Swiss","ASC_synthetic","ASC_plant","ASC_organic"),confidence.level = c(0.9),method = "kr")
Output (WTP preference-space)
MWTP 5% 95%
CO2_A 22.678 8.065 84.477
CO2_B 5.903 -8.796 30.135
Origin_Swiss 26.151 11.262 95.847
ASC_synthetic 1.232 -29.598 39.809
ASC_plant 76.317 37.390 269.062
ASC_organic 103.505 51.327 370.092
method = Krinsky and Robb
wtp<-logitr(
test1,
outcome = "RES",
obsID="obsID",
pars = c("ASC_meat","ASC_organic","ASC_plant","ASC_synthetic","CO2_A","CO2_B","Origin_Swiss"),
scalePar = "price",
randPars = c(ASC_organic="n",ASC_plant="n",ASC_synthetic="n"),
panelID ="ID",
drawType = "halton",
numDraws = 100
)
summary(wtp)
Output (WTP space)
logitr(data = test1, outcome = "RES", obsID = "obsID", pars = c("ASC_meat",
"ASC_organic", "ASC_plant", "ASC_synthetic", "CO2_A", "CO2_B",
"Origin_Swiss"), scalePar = "price", randPars = c(ASC_organic = "n",
ASC_plant = "n", ASC_synthetic = "n"), panelID = "ID", drawType = "halton",
numDraws = 100)
Frequencies of alternatives:
1 2 3 4 5
0.12021 0.34661 0.30678 0.12021 0.10619
Exit Status: 3, Optimization stopped because ftol_rel or ftol_abs was reached.
Model Type: Mixed Logit
Model Space: Willingness-to-Pay
Model Run: 1 of 1
Iterations: 82
Elapsed Time: 0h:0m:7s
Algorithm: NLOPT_LD_LBFGS
Weights Used?: FALSE
Panel ID: ID
Robust? FALSE
Model Coefficients:
Estimate Std. Error z-value Pr(>|z|)
scalePar 0.019051 0.008642 2.2044 0.027495 *
ASC_meat 7.710661 10.009879 0.7703 0.441119
ASC_organic 60.393515 19.568390 3.0863 0.002027 **
ASC_plant 33.159772 11.695771 2.8352 0.004580 **
ASC_synthetic -66.441506 45.168455 -1.4710 0.141299
CO2_A 21.678263 11.303000 1.9179 0.055121 .
CO2_B 9.005566 7.155115 1.2586 0.208168
Origin_Swiss 17.949375 9.290319 1.9321 0.053353 .
sd_ASC_organic -97.861240 44.981905 -2.1756 0.029587 *
sd_ASC_plant -112.356144 51.874685 -2.1659 0.030318 *
sd_ASC_synthetic 173.618829 81.436078 2.1320 0.033010 *