| engin | R Documentation |
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)
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
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
str(engin)