Abstract
We study issues related to external validity for treatment effects using over 100 replications of the Angrist and Evans natural experiment on the effects of sibling sex composition on fertility and labor supply. The replications are based on census data from around the world going back to 1960. We decompose sources of error in predicting treatment effects in external contexts in terms of macro and micro sources of variation. In our empirical setting, we find that macro covariates dominate over micro covariates for reducing errors in predicting treatments, an issue that past studies of external validity have been unable to evaluate. We develop methods for two applications to evidence-based decision-making, including determining where to locate an experiment and whether policy-makers should commission new experiments or rely on an existing evidence base for making a policy decision.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 217-243 |
| Number of pages | 27 |
| Journal | Journal of Business and Economic Statistics |
| Volume | 39 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2021 |
Keywords
- Experiments
- Extrapolation
- Prediction
ASJC Scopus subject areas
- Statistics and Probability
- Social Sciences (miscellaneous)
- Economics and Econometrics
- Statistics, Probability and Uncertainty