Wooldridge Source: Altonji, J.G., T.E. Elder, and C.R. Taber (2005), “An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling,” Journal of Human Resources 40, 791-821. Professor Elder kindly provided a subset of the data, with some variables stripped away for confidentiality reasons. Data loads lazily.

data('catholic')

Format

A data.frame with 7430 observations on 13 variables:

  • id: person identifier

  • read12: reading standardized score

  • math12: mathematics standardized score

  • female: =1 if female

  • asian: =1 if Asian

  • hispan: =1 if Hispanic

  • black: =1 if black

  • motheduc: mother's years of education

  • fatheduc: father's years of education

  • lfaminc: log of family income

  • hsgrad: =1 if graduated from high school by 1994

  • cathhs: =1 if attended Catholic HS

  • parcath: =1 if a parent reports being Catholic

Source

http://www.cengage.com/c/introductory-econometrics-a-modern-approach-6e-wooldridge

Used in Text

pages 267, 551

Examples

str(catholic)
#> 'data.frame': 7430 obs. of 13 variables: #> $ id : int 124902 124915 124916 124932 124944 124947 124966 124968 124972 124974 ... #> $ read12 : num 61.4 58.3 59.3 49.6 57.6 ... #> $ math12 : num 49.8 59.8 50.4 45 54.3 ... #> $ female : int 0 0 1 1 1 1 1 0 0 0 ... #> $ asian : int 0 0 0 0 0 0 0 0 0 0 ... #> $ hispan : int 0 0 0 0 0 0 0 0 0 0 ... #> $ black : int 0 0 0 0 0 0 0 0 0 0 ... #> $ motheduc: num 14 14 14 12 12 12 14 14 14 14 ... #> $ fatheduc: num 12 14 11 14 12 11 14 14 14 12 ... #> $ lfaminc : num 10.3 10.3 10.3 10.3 10.7 ... #> $ hsgrad : int 1 1 1 1 1 1 1 1 1 1 ... #> $ cathhs : int 0 0 0 0 0 0 0 0 0 0 ... #> $ parcath : int 1 1 1 1 1 1 1 1 1 1 ...