arXiv subjects

Rebecca Groh

Publications and source records attributed to Rebecca Groh.

3 recordsLinked to original sources

arXiv2025

Killed in and after Action: The Long-lasting Effects of Combat Exposure on Mortality

This study examines long-term mortality effects of combat exposure using the Vietnam War draft lottery as a quasi-experiment. We validate the lottery by analyzing combat fatalities, revealing that 1951-1952 cohorts had notably fewer lottery-induced deployments than 1950, limiting detectable long-term mortality impacts at the cohort level. Using deceased-only datasets, we invert standard identification by modeling draft eligibility as the outcome. We find significant excess mortality among Black men in the 1950 cohort (1.09\%, approximately 2,700 additional deaths), and null effects in later cohorts. Findings suggest that pooling cohorts with limited combat exposure may prevent detection of true treatment effects at cohort levels.

econ.GN↗

arXiv2024

Revisiting the Many Instruments Problem using Random Matrix Theory

Instrumental variables estimation with many instruments is biased. Traditional bias-adjustments are closely connected to the Silverstein equation. Based on the theory of random matrices, we show that Ridge estimation of the first-stage parameters reduces the implicit price of bias-adjustments. This leads to a trade-off, allowing for less costly estimation of the causal effect, which comes along with improved asymptotic properties. Our theoretical results nest existing ones on bias approximation and adjustment with ordinary least-squares in the first-stage regression and, moreover, generalize them to settings with more instruments than observations. Finally, we derive the optimal tuning parameter of Ridge regressions in simultaneous equations models, which comprises the well-known result for single equation models as a special case with uncorrelated error terms.

econ.EM↗

arXiv2022

Detecting Grouped Local Average Treatment Effects and Selecting True Instruments

Under an endogenous binary treatment with heterogeneous effects and multiple instruments, we propose a two-step procedure for identifying complier groups with identical local average treatment effects (LATE) despite relying on distinct instruments, even if several instruments violate the identifying assumptions. We use the fact that the LATE is homogeneous for instruments which (i) satisfy the LATE assumptions (instrument validity and treatment monotonicity in the instrument) and (ii) generate identical complier groups in terms of treatment propensities given the respective instruments. We propose a two-step procedure, where we first cluster the propensity scores in the first step and find groups of IVs with the same reduced form parameters in the second step. Under the plurality assumption that within each set of instruments with identical treatment propensities, instruments truly satisfying the LATE assumptions are the largest group, our procedure permits identifying these true instruments in a data driven way. We show that our procedure is consistent and provides consistent and asymptotically normal estimators of underlying LATEs. We also provide a simulation study investigating the finite sample properties of our approach and an empirical application investigating the effect of incarceration on recidivism in the US with judge assignments serving as instruments.

econ.EM↗