LaLonde

This data set gives the outcomes a well as treatment assignments and covariates for the econometric evaluation of training programs in LaLonde (1986).

datasets

CBPS is an R package that implements the covariate balancing propensity score proposed by Imai and Ratkovic (2014; JRSSB). The propensity score is estimated such that it maximizes the resulting covariate balance as well as the prediction of treatment assignment. The method, therefore, avoids an iteration between model fitting and balance checking.  The package also implements several extensions of the CBPS beyond the cross-sectional, binary treatment setting.  The current version implements the CBPS for longitudinal settings so that it can be used in conjunction with marginal structural models (Imai and Ratkovic, 2013a), treatments with three- and four-valued treatment variables (Fong, 2013), and the situation with multiple distinct binary treatments administered simultaneously. In the future it will be extended to other settings including continuous treatments and the generalization of experimental and instrumental variable estimates.

Marc Ratkovic

CBPS

R Package for Covariate Balancing Propensity Score

LaLonde function

A data frame consisting of 5 columns (including a treatment assignment vector) and 2787 observations.

format

Data from the National Supported Work Study.  A benchmark matching dataset.  Columns consist of an indicator for whether the observed unit was in the experimental subset; an indicator for whether the individual received the treatment; age in years; schooling in years; indicators for black and Hispanic; an indicator for marriage status, one of married; an indicator for no high school degree; and reported earnings in 1974, 1975, and 1978.  1974 and 1975 earnings are pre-treatment.  1978 earnings is taken as the outcome variable.

LaLonde: LaLonde Data for Covariate Balancing Propensity Score

Description

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