Skip to contents

National Longitudinal Survey of Young Men (NLSYM)

Source: R/data.R
card.Rd

Data used in Card (1995). Consists of a sample of 3,010 individuals from the National Longitudinal Survey of Young Men (NLSYM).

The treatment is educ, the outcome is lwage and the instrument is nearc4.

Usage

data('card')

Format

A data.frame with 3010 observations and 34 variables:

  • id: person identifier

  • nearc2: =1 if near 2 yr college, 1966

  • nearc4: =1 if near 4 yr college, 1966

  • educ: years of schooling, 1976

  • age: in years

  • fatheduc: father's schooling

  • motheduc: mother's schooling

  • weight: NLS sampling weight, 1976

  • momdad14: =1 if live with mom, dad at 14

  • sinmom14: =1 if with single mom at 14

  • step14: =1 if with step parent at 14

  • reg661: =1 for region 1, 1966

  • reg662: =1 for region 2, 1966

  • reg663: =1 for region 3, 1966

  • reg664: =1 for region 4, 1966

  • reg665: =1 for region 5, 1966

  • reg666: =1 for region 6, 1966

  • reg667: =1 for region 7, 1966

  • reg668: =1 for region 8, 1966

  • reg669: =1 for region 9, 1966

  • south66: =1 if in south in 1966

  • black: =1 if black

  • smsa: =1 in in SMSA, 1976

  • south: =1 if in south, 1976

  • smsa66: =1 if in SMSA, 1966

  • wage: hourly wage in cents, 1976

  • enroll: =1 if enrolled in school, 1976

  • KWW: knowledge world of work score

  • IQ: IQ score

  • married: =1 if married, 1976

  • libcrd14: =1 if lib. card in home at 14

  • exper: age - educ - 6

  • lwage: log(wage)

  • expersq: exper^2

References

Card, D. "Using Geographic Variation in College Proximity to Estimate the Return to Schooling". In L.N. Christofides, E.K. Grant, and R. Swidinsky, editors, Aspects of Labor Market Behaviour: Essays in Honour of John Vanderkamp. Toronto: University of Toronto Press, 1995.

Examples

data('card')
head(card)
#>   id nearc2 nearc4 educ age fatheduc motheduc weight momdad14 sinmom14 step14
#> 1  2      0      0    7  29       NA       NA 158413        1        0      0
#> 2  3      0      0   12  27        8        8 380166        1        0      0
#> 3  4      0      0   12  34       14       12 367470        1        0      0
#> 4  5      1      1   11  27       11       12 380166        1        0      0
#> 5  6      1      1   12  34        8        7 367470        1        0      0
#> 6  7      1      1   12  26        9       12 380166        1        0      0
#>   reg661 reg662 reg663 reg664 reg665 reg666 reg667 reg668 reg669 south66 black
#> 1      1      0      0      0      0      0      0      0      0       0     1
#> 2      1      0      0      0      0      0      0      0      0       0     0
#> 3      1      0      0      0      0      0      0      0      0       0     0
#> 4      0      1      0      0      0      0      0      0      0       0     0
#> 5      0      1      0      0      0      0      0      0      0       0     0
#> 6      0      1      0      0      0      0      0      0      0       0     0
#>   smsa south smsa66 wage enroll KWW  IQ married libcrd14 exper    lwage expersq
#> 1    1     0      1  548      0  15  NA       1        0    16 6.306275     256
#> 2    1     0      1  481      0  35  93       1        1     9 6.175867      81
#> 3    1     0      1  721      0  42 103       1        1    16 6.580639     256
#> 4    1     0      1  250      0  25  88       1        1    10 5.521461     100
#> 5    1     0      1  729      0  34 108       1        0    16 6.591674     256
#> 6    1     0      1  500      0  38  85       1        1     8 6.214608      64