Wooldridge Source: Thada Chaisawangwong, a former graduate student at MSU, obtained these data for a term project in applied econometrics. They come from the Material Requirement Planning Survey carried out in Thailand during 1998. Data loads lazily.
data('engin')A data.frame with 403 observations on 17 variables:
male: =1 if male
educ: highest grade completed
wage: monthly salary, Thai baht
swage: starting wage
exper: years on current job
pexper: previous experience
lwage: log(wage)
expersq: exper^2
highgrad: =1 if high school graduate
college: =1 if college graduate
grad: =1 if some graduate school
polytech: =1 if a polytech
highdrop: =1 if no high school degree
lswage: log(swage)
pexpersq: pexper^2
mleeduc: male*educ
mleeduc0: male*(educ - 14)
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This is a nice change of pace from wage data sets for the United States. These data are for engineers in Thailand, and represents a more homogeneous group than data sets that consist of people across a variety of occupations. Plus, the starting salary is also provided in the data set, so factors affecting wage growth – and not just wage levels at a given point in time – can be studied. This is a good data set for a common term project that tests basic understanding of multiple regression and the interpretation of models with a logarithm for a dependent variable.
Used in Text: not used
str(engin)
#> 'data.frame': 403 obs. of 17 variables:
#> $ male : int 0 0 0 0 0 0 0 1 1 1 ...
#> $ educ : int 12 12 12 12 12 12 12 17 15 19 ...
#> $ wage : int 20400 23850 22800 20700 21300 24300 19650 60000 30300 61250 ...
#> $ swage : int 11250 12750 11250 11250 11250 15000 13950 32490 15750 33000 ...
#> $ exper : int 6 12 12 12 12 12 12 12 12 12 ...
#> $ pexper : int 0 3 0 0 1 21 23 3 10 2 ...
#> $ lwage : num 9.92 10.08 10.03 9.94 9.97 ...
#> $ expersq : int 36 144 144 144 144 144 144 144 144 144 ...
#> $ highgrad: int 1 1 1 1 1 1 1 0 0 0 ...
#> $ college : int 0 0 0 0 0 0 0 0 0 0 ...
#> $ grad : int 0 0 0 0 0 0 0 1 0 1 ...
#> $ polytech: int 0 0 0 0 0 0 0 0 1 0 ...
#> $ highdrop: int 0 0 0 0 0 0 0 0 0 0 ...
#> $ lswage : num 9.33 9.45 9.33 9.33 9.33 ...
#> $ pexpersq: int 0 9 0 0 1 441 529 9 100 4 ...
#> $ mleeduc : int 0 0 0 0 0 0 0 17 15 19 ...
#> $ mleeduc0: int 0 0 0 0 0 0 0 3 1 5 ...
#> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"