We present a method for narrowing nonparametric bounds on treatment effects by adjusting for potentially large numbers of covariates, using generalized random forests. In many experimental or quasi-experimental studies, outcomes of interest are only observed for subjects who select (or are selected) to engage in the activity generating the outcome. Outcome data are thus endogenously missing for units who do not engage, and random or conditionally random treatment assignment before such choices is insufficient to identify treatment effects. Nonparametric partial identification bounds address endogenous missingness without having to make disputable parametric assumptions. Basic bounding approaches often yield bounds that are wide and minimally informative. Our approach can tighten such bounds while permitting agnosticism about the data-generating process and honest inference. A simulation study and replication exercise demonstrate the benefits.

We study how an intervention combining youth intergroup contact and sports affects intergroup relations in the context of an active conflict. We first conduct a randomized controlled trial (RCT) of one-year program exposure in Israel. To track effects of a multiyear exposure, we then use machine-learning techniques to fuse the RCT with the observational data gathered on multiyear participants. This analytical approach can help overcome frequent limitations of RCTs, such as modest sample sizes and short observation periods. Our evidence cannot affirm a one-year effect on outgroup regard and ingroup regulation, although we estimate benefits of multiyear exposure among Jewish-Israeli youth, particularly boys. We discuss implications for interventions in contexts of active conflict and group status asymmetry.

How do non-state armed groups (NSAGs) survive and even thrive in situations where state armed groups (SAGs) collapse, despite the former’s often greater material adversity? We argue that, optimizing under their different constraints, SAGs invest more in technical military training and NSAGs invest more in enhancing soldiers’ intrinsic payoffs from serving their group. Therefore, willingness to contribute to the group should be more positively correlated with years of service in NSAGs than in SAGs. We confirm this hypothesis with lab-in-the-field and qualitative evidence from SAG and NSAG soldiers in Nepal, Ivory Coast, and Kurdistan. Each field study addresses specific inferential weaknesses in the others. Assembled together, these cases reduce concerns about external validity or replicability. Our findings reveal how the basis of NSAG cohesion differs from that of SAGs, with implications for strategies to counter NSAG mobilization.

We address a debate over the effects of private versus customary property rights on external investment. Despite political economists’ claims that external investors favor private property rights, other experts argue that customary systems enable large-scale “land grabs.” We organize these competing claims, highlighting trade-offs due to differences in legibility versus the ability to displace existing landholders under both systems. We study a natural experiment in Liberia, where law codifies parallel private and customary property rights systems. We use this institutional boundary and difference-in-differences methods to isolate differential changes in external investment under the different property rights systems following the global food crisis of 2007–08. We find a larger increase in land clearing where private property rights prevailed, with such clearing related to more concession activity. Qualitative study of a palm oil concession reveals challenges external investors confront when navigating customary systems.