This paper proposes a nonparametric method for evaluating treatment effects in the presence of both treatment endogeneity and attrition/non-response bias, using two instrumental variables. Making use of a discrete instrument for the treatment and a continuous instrument for...

Using UK longitudinal data on dual-earner couples, this paper estimates a model of intrahousehold housework decisions, which combines a randomized experimental framework eliciting counterfactual choices with gender norms differences across ethnicities and cohorts to identify the impacts of...

Using UK longitudinal data on dual-earner couples, this paper estimates a model of intrahousehold housework decisions, which combines a randomized experimental framework eliciting counterfactual choices with gender norms differences across ethnicities and cohorts to identify the impacts of...

Centralized school assignment algorithms must distinguish between applicants with the same preferences and priorities. This is done with randomly assigned lottery numbers, nonlottery tie-breakers like test scores, or both. The New York City public high school match illustrates the latter, using...

Randomized control trials are often considered the gold standard to establish causality. However, in many policy-relevant situations, these trials are not possible. Instrumental variables affect the outcome only via a specific treatment; as such, they allow for the estimation of a causal effect....

Since identification, instrumental variables and variables exclusion, core concepts in econometrics, are entwined, several questions arise: How is identification related to the existence of IVs? How are identification criteria related to omitted variables? Is omission/inclusion of variables from...

This note discusses the application of segmented multinomial logit models (MNL) for the analysis of discrete choice experiments. It is shown how the segmentation can be achieved by relying on the model-based recursive partitioning framework and how it can be carried out in R. The approach is...

We analyse stated preference data over nursing jobs collected from two leading types of best-worst discrete choice experiments (DCEs): a traditional DCE involving choice over alternative jobs (BWL) and a newly-developed DCE where respondents choose best and worst job attributes (BWT). The latter...

In stated choice (SC) data inconsistent and lexicographic choice behavior is often observed. It is sometimes recommended to remove data with these characteristics from the analysis. In this paper we reconsider this recommendation. In our data many respondents have inconsistent choice patterns,...