On this R-data statistics page, you will find information about the nswdemo data set which pertains to Labour Training Evaluation Data. The nswdemo data set is found in the DAAG R package. You can load the nswdemo data set in R by issuing the following command at the console data("nswdemo"). This will load the data into a variable called nswdemo. If R says the nswdemo data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the nswdemo R data set. The size of this file is about 23,450 bytes.
Labour Training Evaluation Data
nswdemo data frame contains 722 rows and 10 columns. These data are pertinent to an investigation of the way that earnings changed, between 1974-1975 and 1978, for an experimental treatment who were given job training as compared with a control group who did not receive such training.
psid1 data set is an alternative non-experimental "control" group.
psid3 are subsets of
psid1, designed to be better matched to the experimental data than
psid1. Note also the
cps3 datasets (DAAGxtras) that have been proposed as non-experimental controls.
This data frame contains the following columns:
a numeric vector identifying the study in which the subjects were enrolled (0 = Control, 1 = treated).
age (in years).
years of education.
(0 = not black, 1 = black).
(0 = not hispanic, 1 = hispanic).
(0 = not married, 1 = married).
(0 = completed high school, 1 = dropout).
real earnings in 1974.
real earnings in 1975.
real earnings in 1978.
Dehejia, R.H. and Wahba, S. 1999. Causal effects in non-experimental studies: re-evaluating the evaluation of training programs. Journal of the American Statistical Association 94: 1053-1062.
Lalonde, R. 1986. Evaluating the economic evaluations of training programs. American Economic Review 76: 604-620.
Smith, J. A. and Todd, P.E. 2005,"Does Matching overcome. LaLonde?s critique of nonexperimental estimators", Journal of Econometrics 125: 305-353.
Dehejia, R.H. 2005. Practical propensity score matching: a reply to Smith and Todd. Journal of Econometrics 125: 355-364.
Dataset imported from https://www.r-project.org.