Work in Progress
The Cost of Complexity: How Communication Frictions Affect Patient Mortality (latest version here)
This paper examines how the complexity of medical discharge instructions influences patient mortality. Using data on 239,878 hospital admissions from a large U.S. academic medical center, I measure textual complexity on a standard readability scale where higher values indicate greater difficulty. A one-standard-deviation increase in complexity is associated with a 0.15 percentage point rise in 28-day mortality, representing an 8.7 percent increase relative to the baseline rate. Moving from the 25th to the 75th percentile of complexity generates a 0.18 percentage point increase. In contrast, I find no significant effects on in-system hospital readmissions and emergency department visits. The mortality effects are highly heterogeneous and concentrated among patients requiring intensive self-management, particularly those with heart failure. Importantly, the association persists even within subsamples of notes containing identical self-care instructions, demonstrating that the effect operates beyond pure task assignment. These findings identify communication clarity as a modifiable input in the health production function that can improve post-discharge survival.
Testing identification in mediation and dynamic treatment models (with Martin Huber and Lukas Laffers) - arXiv Preprint
We propose a test for the identification of causal effects in mediation and dynamic treatment models that is based on two sets of observed variables, namely covariates to be controlled for and suspected instruments, building on the test by Huber and Kueck (2022) for single treatment models. We consider models with a sequential assignment of a treatment and a mediator to assess the direct treatment effect (net of the mediator), the indirect treatment effect (via the mediator), or the joint effect of both treatment and mediator. We establish testable conditions for identifying such effects in observational data. These conditions jointly imply (1) the exogeneity of the treatment and the mediator conditional on covariates and (2) the validity of distinct instruments for the treatment and the mediator, meaning that the instruments do not directly affect the outcome (other than through the treatment or mediator) and are unconfounded given the covariates. Our framework extends to post-treatment sample selection or attrition problems when replacing the mediator by a selection indicator for observing the outcome, enabling joint testing of the selectivity of treatment and attrition. We propose a machine learning-based test to control for covariates in a data-driven manner and analyze its finite sample performance in a simulation study. Additionally, we apply our method to Slovak labor market data and find that our testable implications are not rejected for a sequence of training programs typically considered in dynamic treatment evaluations.
Long-term Effects of Growing Up with a Disabled Sibling (with Maria Hofbauer Pérez and Felicia Stokke)
Growing up with a disabled sibling presents challenges and opportunities for non-disabled siblings. While these siblings may experience reduced parental attention, they may also develop valuable skills that are beneficial in adulthood. This paper examines the long-term effects of growing up with a sibling with a disability on labor market outcomes, utilizing comprehensive Swedish administrative data. We estimate an across-family effect (total exposure effect) using double machine learning, and a within-family comparison that controls for unobservable time-invariant family characteristics. Our within-family estimates show no statistically significant effect on 9th-grade GPA and exert no discernible impact on subsequent labor income or on the likelihood of entering social or medical occupations. By contrast, our across-family (total exposure) estimates document a negative effect on 9th-grade GPA and uncover a pronounced reduction in labor income, an effect that is substantially attenuated once social transfers are included, and a very small but statistically significant rise in the probability of choosing a social sector career.
Household Labor Supply Elasticities: Evidence from Cross-Border Workers (with Sarah Lein, Andreas Peichl, Kurt Schmidheiny, and Peter Zorn)
After the Swiss National Bank unexpectedly abandoned a minimum exchange rate policy in 2015, the Swiss franc appreciated by more than 10 percent against the Euro. The appreciation implied a sudden increase in real wage incomes for over 40,000 Germancross-border commuters into Switzerland because these workers consume in Euros with a nominal wage in Swiss Francs. We use this exchange rate shock to estimate the own-wage and cross-spouse labor supply elasticities from administrative tax returns data and find a 5% drop in taxable income in CHF for cross-border workers and a 3% reduction in taxable income for cross-border worker spouses. We provide evidence for intensive margin adjustments in hours worked consistent with these estimates. This suggests that the uncompensated labor supply elasticity is small but negative and that joint household decisions matter for labor supply.