| jtrain2 | R Documentation |
Wooldridge Source: R.J. Lalonde (1986), “Evaluating the Econometric Evaluations of Training Programs with Experimental Data,” American Economic Review 76, 604-620. Professor Jeff Biddle, at MSU, kindly passed the data set along to me. He obtained it from Professor Lalonde. Data loads lazily.
data('jtrain2')
A data.frame with 445 observations on 19 variables:
train: =1 if assigned to job training
age: age in 1977
educ: years of education
black: =1 if black
hisp: =1 if Hispanic
married: =1 if married
nodegree: =1 if no high school degree
mosinex: # mnths prior to 1/78 in expmnt
re74: real earns., 1974, $1000s
re75: real earns., 1975, $1000s
re78: real earns., 1978, $1000s
unem74: =1 if unem. all of 1974
unem75: =1 if unem. all of 1975
unem78: =1 if unem. all of 1978
lre74: log(re74); zero if re74 == 0
lre75: log(re75); zero if re75 == 0
lre78: log(re78); zero if re78 == 0
agesq: age^2
mostrn: months in training
Professor Lalonde obtained the data from the National Supported Work Demonstration job-training program conducted by the Manpower Demonstration Research Corporation in the mid 1970s. Training status was randomly assigned, so this is essentially experimental data. Computer Exercise C17.8 looks only at the effects of training on subsequent unemployment probabilities. For illustrating the more advanced methods in Chapter 17, a good exercise would be to have the students estimate a Tobit of re78 on train, and obtain estimates of the expected values for those with and without training. These can be compared with the sample averages.
Used in Text: pages 18, 340-341, 626
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
str(jtrain2)