Bank Wages
Wages of employees of a US bank.
data("BankWages")A data frame containing 474 observations on 4 variables.
Ordered factor indicating job category, with levels "custodial",
"admin" and "manage".
Education in years.
Factor indicating gender.
Factor. Is the employee member of a minority?
Online complements to Heij, de Boer, Franses, Kloek, and van Dijk (2004).
Heij, C., de Boer, P.M.C., Franses, P.H., Kloek, T. and van Dijk, H.K. (2004). Econometric Methods with Applications in Business and Economics. Oxford: Oxford University Press.
data("BankWages")
## exploratory analysis of job ~ education
## (tables and spine plots, some education levels merged)
xtabs(~ education + job, data = BankWages)
edcat <- factor(BankWages$education)
levels(edcat)[3:10] <- rep(c("14-15", "16-18", "19-21"), c(2, 3, 3))
tab <- xtabs(~ edcat + job, data = BankWages)
prop.table(tab, 1)
spineplot(tab, off = 0)
plot(job ~ edcat, data = BankWages, off = 0)
## fit multinomial model for male employees
library("nnet")
fm_mnl <- multinom(job ~ education + minority, data = BankWages,
subset = gender == "male", trace = FALSE)
summary(fm_mnl)
confint(fm_mnl)
## same with mlogit package
library("mlogit")
fm_mlogit <- mlogit(job ~ 1 | education + minority, data = BankWages,
subset = gender == "male", shape = "wide", reflevel = "custodial")
summary(fm_mlogit)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.