| BankWages | R Documentation |
Bank Wages
Description
Wages of employees of a US bank.
Usage
data("BankWages")Format
A data frame containing 474 observations on 4 variables.
- job
Ordered factor indicating job category, with levels
"custodial","admin"and"manage".- education
Education in years.
- gender
Factor indicating gender.
- minority
Factor. Is the employee member of a minority?
Source
Online complements to Heij, de Boer, Franses, Kloek, and van Dijk (2004).
References
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.
Examples
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)