Poor implementation frequently impedes social protection delivery in low-state-capacity settings. In such environments, reducing managers' information acquisition costs may improve their grasp of frontline issues and program performance. However, in the presence of managerial rent-seeking,...

Millions of people lose access to safety-net programs each year because they do not complete the required administrative processes. In a large-scale field experiment, we randomized outreach offering personalized assistance during the Medicaid renewal window to identify the impact of transaction...

Concerns about fraud in welfare programs common arguments worldwide against such programs. We conducted a survey experiment with over 28,000 welfare program administrators and over 19,000 beneficiaries in Indonesia to elicit the 'marginal disutility from corruption,' i.e., the trade-between more...

We develop and estimate a life-cycle consumption savings model in which observed genetic variation is allowed to affect wealth accumulation through several distinct channels. We focus on genetic markers that predict educational attainment, aggregated into a predictive index called a polygenic...

We provide new evidence that cash transfers following the birth of a first child can have large and long-lasting effects on that child's outcomes. We take advantage of the January 1 birthdate cutoff for U.S. child-related tax benefits, which results in families of otherwise similar children...

The composition and quality of the child care workforce may be uniquely sensitive to changes in the complementarities between home production and market work. This paper examines whether the expansion of oral contraceptives and abortion access throughout the 1960's and 1970's influenced the...

When should travellers leave for the airport? This paper develops a model for optimal airport arrival timing when travellers face uncertain travel times and can potentially board earlier flights. We show that access to earlier flights creates a ``recourse option" that fundamentally changes...

We argue that comprehensive out-of-sample (OOS) evaluation using statistical decision theory (SDT) should replace the current practice of K-fold and Common Task Framework validation in machine learning (ML) research. SDT provides a formal framework for performing comprehensive OOS evaluation...

Empirical researchers frequently rely on normal approximations in order to summarize and communicate uncertainty about their findings to their scientific audience. When such approximations are unreliable, they can lead the audience to make misguided decisions. We propose to measure the failure...

In medical treatment and elsewhere, it has become standard to base treatment intensity (dosage) on evidence in randomized trials. Yet it has been rare to study how outcomes vary with dosage. In trials to obtain drug approval, the norm has been to specify some dose of a new drug and compare it...