There is interest in learning about the causal effects of family planning (FP) on empowerment-related outcomes. Data related to this question are available from studies in which FP programs increase access to FP, but such interventions do not necessarily result in uptake of FP. In addition, women impacted by such programs may differ systematically from target populations of interest in ways that alter the effect of FP. To assess the causal effect of FP on empowerment-related outcomes, we developed a 2-step approach. We use principal stratification and Bayesian Additive Regression Trees (BART) to non-parametrically estimate the effect in the source population among women affected by a FP program. We generalize the results to a broader population by taking the expectation of conditional average treatment effects from the selective sample over the covariate distribution in the target population. To estimate (uncertainty in) the covariate distribution from survey data with a complex sampling design, we use a Bayesian bootstrap (BB). We apply the approach to estimate the causal effect of modern contraceptive use on employment among urban women in Nigeria and Senegal and find strong effects and effect heterogeneity. Sensitivity analyses suggest robustness to violations of assumptions for internal and external validity.

翻译：学界对探究计划生育（FP）对赋权相关结局的因果效应存在研究兴趣。相关数据来自通过计划生育项目提升避孕可及性的研究，但此类干预并不必然导致计划生育的实际采用。此外，受项目影响的女性可能在改变计划生育效应的重要维度上系统性区别于目标人群。为评估计划生育对赋权相关结局的因果效应，我们开发了一种两步法：首先运用主分层法和贝叶斯加性回归树（BART）对受计划生育项目影响的源人群进行非参数效应估计；随后通过将选择性样本的条件平均处理效应在目标人群协变量分布上求期望，将结果推广至更广泛人群。为基于复杂抽样设计的调查数据估计协变量分布（及其不确定性），我们采用贝叶斯自助法（BB）。应用该方法评估现代避孕措施对尼日利亚和塞内加尔城市女性就业的因果效应，发现了显著的效应及效应异质性。敏感性分析表明，该方法对内部与外部效度假设的违背具有稳健性。