This paper forecasts the life-cycle treatment effects on health of a high-quality early childhood program. Our predictions combine microsimulation using non-experimental data with experimental data from a midlife long-term follow-up. The follow-up incorporated a full epidemiological exam. The...

We present experimental evidence on the effects of four U.S. reemployment programs for youth Unemployment Insurance (UI) recipients during the Great Recession. The three programs that emphasized monitoring and service referrals reduced UI receipt but had minimal effects on employment and...

In empirical research, measuring correctly the benefits of welfare interventions is incredibly relevant for policymakers as well as academic researchers. Unfortunately, the endogenous program participation is often misreported in survey data and standard instrumental variable techniques are not...

Proximity augments homeless students' educational outcomes. Homeless K-8 graders whose families are placed in shelters near their schools have 8 percent (2.4 days) better attendance, are a third (18 percentage points) less likely to change schools, and exhibit higher rates of proficiency and...

Using an original administrative dataset in the context of a scarcity induced-natural experi-ment in New York City, I find that families placed in shelters in their neighborhoods of origin remain there considerably longer than those assigned to distant shelters. Locally-placed families also...

How well do program participants assess program performance ex-post? In this paper we compare participant evaluations based on survey responses to econometric impact estimates obtained using data from the experimental evaluation of the U.S. Job Training Partnership Act. We have two main...

This paper examines a broad set of short- and long-term impacts of Individual Placement and Support (IPS) for disability benefit recipients with severe mental disabilities. IPS is a specific intervention that first aims to place an individual in employment and subsequently trains the worker on...

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection on observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric estimator that...