Wooldridge Source: Professor Daniel Hamermesh, at the University of Texas, compiled these data from the May 1991 Current Population Survey. Professor Hamermesh kindly provided these data. Data loads lazily.
data('cps91')A data.frame with 5634 observations on 24 variables:
husage: husband's age
husunion: =1 if hus. in union
husearns: hus. weekly earns
huseduc: husband's yrs schooling
husblck: =1 if hus. black
hushisp: =1 if hus. hispanic
hushrs: hus. weekly hours
kidge6: =1 if have child >= 6
earns: wife's weekly earnings
age: wife's age
black: =1 if wife black
educ: wife's yrs schooling
hispanic: =1 if wife hispanic
union: =1 if wife in union
faminc: annual family income
husexp: huseduc - husage - 6
exper: age - educ - 6
kidlt6: =1 if have child < 6
hours: wife's weekly hours
expersq: exper^2
nwifeinc: non-wife inc, $1000s
inlf: =1 if wife in labor force
hrwage: earns/hours
lwage: log(hrwage)
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This is much bigger than the other CPS data sets even though the sample is restricted to married women. (CPS91.RAW contains many more observations than MROZ.RAW, too.) In addition to the usual human capital variables for the women in the sample, we have information on the husband. Therefore, we can estimate a labor supply function as in Chapter 16, although the validity of potential experience as an IV for log(wage) is questionable. (MROZ.RAW contains an actual experience variable.) Perhaps more convincing is to add hours to the wage offer equation, and instrument hours with indicators for young and old children. This data set also contains a union membership indicator. The web site for the National Bureau of Economic Research makes it very easy now to download CPS data files in a variety offormats. Go to http://www.nber.org/data/cps_basic.html.
Used in Text: page 627-628
str(cps91)
#> 'data.frame': 5634 obs. of 24 variables:
#> $ husage : int 42 26 56 35 42 55 68 48 38 48 ...
#> $ husunion: int 0 0 0 NA 0 0 NA 0 NA 1 ...
#> $ husearns: int 568 600 1500 0 450 465 0 492 0 1923 ...
#> $ huseduc : int 14 14 14 12 11 13 16 10 14 12 ...
#> $ husblck : int 0 0 0 0 0 0 0 0 0 0 ...
#> $ hushisp : int 0 0 0 0 0 0 0 1 0 0 ...
#> $ hushrs : int 40 0 40 40 45 50 0 48 65 21 ...
#> $ kidge6 : int 1 0 1 0 1 0 0 0 1 0 ...
#> $ earns : num 290 654 100 0 0 0 360 0 0 0 ...
#> $ age : int 43 26 49 35 43 58 56 48 37 39 ...
#> $ black : int 0 0 0 0 0 0 0 0 0 0 ...
#> $ educ : int 14 14 12 10 13 12 12 12 12 14 ...
#> $ hispanic: int 0 0 0 0 0 0 0 1 0 0 ...
#> $ union : int 0 0 0 NA NA NA 0 NA NA NA ...
#> $ faminc : num 45000 45000 55000 55000 27500 ...
#> $ husexp : int 22 6 36 17 25 36 46 32 18 30 ...
#> $ exper : int 23 6 31 19 24 40 38 30 19 19 ...
#> $ kidlt6 : int 0 0 0 1 0 0 0 0 0 1 ...
#> $ hours : int 0 0 15 0 0 0 45 0 0 0 ...
#> $ expersq : int 529 36 961 361 576 1600 1444 900 361 361 ...
#> $ nwifeinc: num 29.9 11 49.8 55 27.5 ...
#> $ inlf : int 0 0 1 0 0 0 1 0 0 0 ...
#> $ hrwage : num NA NA 6.67 NA NA ...
#> $ lwage : num NA NA 1.9 NA NA ...
#> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"