In this paper we examine how policymakers and practitioners should interpret the impact evaluation literature when presented with conflicting experimental and non-experimental estimates of the same intervention across varying contexts. We show three things. First, as is well known,...

We propose inverse probability weighted estimators for the distribution functions of the potential outcomes under the unconfoundedness assumption and apply the inverse mapping to obtain the quantile functions. We show that these estimators converge weakly to zero mean Gaussian processes. A...

This paper investigates the effect that covariate measurement error has on a treatment effect analysis built on an unconfoundedness restriction in which there is conditioning on error free covariates. The approach uses small parameter asymptotic methods to obtain the approximate effects of...

This paper considers treatment evaluation in a discrete time setting in which treatment could start at any point in time. A typical application is an active labor market policy program which could start after any elapsed unemployment duration. It is shown that various average effects on survival...

To increase mother’s participation in the labour market and enhance child development, the Canadian province of Québec developed from 1997 a large scale low-fee childcare network. Previous studies have shown that the policy has significantly increased the labour force participation and annual...

This paper develops and estimates a model with multiple schooling choices that identifies the causal effect of different levels of schooling on health, health-related behaviors, and labor market outcomes. We develop an approach that is a halfway house between a reduced form treatment effect...

In this paper we study doubly robust estimators of various average treatment effects under unconfoundedness. We unify and extend much of the recent literature by providing a very general identification result which covers binary and multi-valued treatments; unnormalized and normalized weighting;...

Agro-environmental schemes (AES), which pay farmers to adopt greener practices, are increasingly important components of environmental and agricultural policies both in the US and the EU. Here we study the French implementation of the EU AES program. We estimate additional and windfall effects...

This paper evaluates the impact of a cassava research-for-development program on farm level outcomes. The program was implemented in the Democratic Republic of Congo from 2001 to 2009. We apply propensity score matching, Rosenbaum bounds on treatment effects, Altonji et al. method of selection...

This paper studies the problem of treatment choice between a status quo treatment with a known outcome distribution and an innovation whose outcomes are observed only in a representative finite sample. I evaluate statistical decision rules, which are functions that map sample outcomes into the...