This paper combines causal mediation analysis with double machine learning to control for observed confounders in a data-driven way under a… [weiterlesen]

Health insurers receive millions of claims per year. Given that information asymmetries between the principal (insurer) and the agents (health care… [weiterlesen]

Assumptions that are sufficient to identify local average treatment effects (LATEs) generate necessary conditions that allow instrument validity to be… [weiterlesen]

We investigate the behavior of the Lasso for selecting invalid instruments in linear instrumental variables models for estimating causal effects of… [weiterlesen]

We study the consequences of actively raising children and simultaneously pursuing a career for mothers' health. Based on Swedish administrative data… [weiterlesen]

The Supplemental Nutrition Assistance Program (SNAP) distributes vouchers for grocery shopping to around 43 million individuals across the United… [weiterlesen]

In the construction of the GMM version of the Anderson and Rubin (AR) test statistic there is the choice to use either uncentered or centered moment… [weiterlesen]

Twin births are an important instrument for the endogenous fertility decision. However, twin births are not exogenous either as dizygotic twinning is… [weiterlesen]

Heterogeneous effects are prevalent in many economic settings. As the functional form between outcomes and regressors is generally unknown a priori, a… [weiterlesen]

Nonlinear price schedules generally have heterogeneous effects on health-care demand. We develop and apply a finite mixture bivariate probit model to… [weiterlesen]