wage1 {np} | R Documentation |
Cross-Sectional Data on Wages
Description
Cross-section wage data consisting of a random sample
taken from the U.S. Current Population Survey for the year 1976. There
are 526 observations in total. data("wage1")
makes available the
dataset "wage"
plus additional objects "bw.all"
and
"bw.subset"
.
Usage
data("wage1")
Format
A data frame with 24 columns, and 526 rows.
Two local-linear rbandwidth
objects (bw.all
and
bw.subset
) have been computed for the user's convenience
which can be used to visualize this dataset using
plot(bw.all)
- wage
column 1, of type
numeric
, average hourly earnings- educ
column 2, of type
numeric
, years of education- exper
column 3, of type
numeric
, years potential experience- tenure
column 4, of type
numeric
, years with current employer- nonwhite
column 5, of type
factor
, =“Nonwhite” if nonwhite, “White” otherwise- female
column 6, of type
factor
, =“Female” if female, “Male” otherwise- married
column 7, of type
factor
, =“Married” if Married, “Nonmarried” otherwise- numdep
column 8, of type
numeric
, number of dependants- smsa
column 9, of type
numeric
, =1 if live in SMSA- northcen
column 10, of type
numeric
, =1 if live in north central U.S- south
column 11, of type
numeric
, =1 if live in southern region- west
column 12, of type
numeric
, =1 if live in western region- construc
column 13, of type
numeric
, =1 if work in construction industry- ndurman
column 14, of type
numeric
, =1 if in non-durable manufacturing industry- trcommpu
column 15, of type
numeric
, =1 if in transportation, communications, public utility- trade
column 16, of type
numeric
, =1 if in wholesale or retail- services
column 17, of type
numeric
, =1 if in services industry- profserv
column 18, of type
numeric
, =1 if in professional services industry- profocc
column 19, of type
numeric
, =1 if in professional occupation- clerocc
column 20, of type
numeric
, =1 if in clerical occupation- servocc
column 21, of type
numeric
, =1 if in service occupation- lwage
column 22, of type
numeric
, log(wage)- expersq
column 23, of type
numeric
, exper^2
- tenursq
column 24, of type
numeric
, tenure^2
Source
Jeffrey M. Wooldridge
References
Wooldridge, J.M. (2000), Introductory Econometrics: A Modern Approach, South-Western College Publishing.
Examples
data("wage1")
attach(wage1)
summary(wage1)
detach(wage1)