Wooldridge Source: I collected these data from the old Michigan Department of Education web site. See MATHPNL.RAW for the current web site. I used data on most high schools in the state of Michigan for 1993. I dropped some high schools that had suspicious-looking data. Data loads lazily.

data('meap93')

Format

A data.frame with 408 observations on 17 variables:

  • lnchprg: perc of studs in sch lnch prog

  • enroll: school enrollment

  • staff: staff per 1000 students

  • expend: expend. per stud, $

  • salary: avg. teacher salary, $

  • benefits: avg. teacher benefits, $

  • droprate: school dropout rate, perc

  • gradrate: school graduation rate, perc

  • math10: perc studs passing MEAP math

  • sci11: perc studs passing MEAP science

  • totcomp: salary + benefits

  • ltotcomp: log(totcomp)

  • lexpend: log of expend

  • lenroll: log(enroll)

  • lstaff: log(staff)

  • bensal: benefits/salary

  • lsalary: log(salary)

Source

https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041

Notes

Many states have data, at either the district or building level, on student performance and spending. A good exercise in data collection and cleaning is to have students find such data for a particular state, and to put it into a form that can be used for econometric analysis.

Used in Text: pages 50, 65, 111-112, 127-128, 155-156, 219, 336, 339, 696-697

Examples

str(meap93)
#> 'data.frame': 408 obs. of 17 variables: #> $ lnchprg : num 1.4 2.3 2.7 3.4 3.4 ... #> $ enroll : int 1862 11355 7685 1148 1572 2496 3358 11983 3499 5095 ... #> $ staff : num 112.6 101.2 114 85.4 96.1 ... #> $ expend : int 5765 6601 6834 3586 3847 5070 4474 5159 5012 6501 ... #> $ salary : num 37498 48722 44541 31566 29781 ... #> $ benefits: int 7420 10370 7313 5989 5545 5895 6934 8085 7253 7386 ... #> $ droprate: num 2.9 1.3 3.5 3.6 0 ... #> $ gradrate: num 89.2 91.4 91.4 86.6 100 ... #> $ math10 : num 56.4 42.7 43.8 25.3 15.3 ... #> $ sci11 : num 67.9 65.3 54.3 60 65.8 ... #> $ totcomp : num 44918 59092 51854 37555 35326 ... #> $ ltotcomp: num 10.7 11 10.9 10.5 10.5 ... #> $ lexpend : num 8.66 8.79 8.83 8.18 8.26 ... #> $ lenroll : num 7.53 9.34 8.95 7.05 7.36 ... #> $ lstaff : num 4.72 4.62 4.74 4.45 4.57 ... #> $ bensal : num 0.198 0.213 0.164 0.19 0.186 ... #> $ lsalary : num 10.5 10.8 10.7 10.4 10.3 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"