The Jobs dataset by LaLonde [36] is a widely used benchmark in the causal inference community, where the treatment is job training and the outcomes are income and employment status after training. The dataset includes 8 covariates such as age, education, and previous earnings. Our goal is to predict unemployment, using the feature set of Dehejia and Wahba [37]. Following Shalit et al. [8], we combined the LaLonde experimental sample (297 treated, 425 control) with the PSID comparison group (2490 control).
Variants: Jobs
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Causal Inference | CFR MMD | Estimating individual treatment effect: generalization … | 2016-06-13 |
| Causal Inference | CFR WASS | Estimating individual treatment effect: generalization … | 2016-06-13 |
| Causal Inference | BART | BART: Bayesian additive regression trees | 2008-06-19 |
Recent papers with results on this dataset: