Earnings after DI: evidence from full medical continuing disability reviews

Social Security Disability Insurance beneficiaries undergo periodic medical reviews to determine if they continue to be eligible for disability benefits. We examine how these reviews affect beneficiary well-being by using administrative data to track the earnings of beneficiaries for up to 5 years after their reviews. We estimate that a sizeable percentage of beneficiaries would work if their benefits were ceased in a medical review. However, many appear to be unable to maintain employment: only one in three would have earnings over the full follow-up period

How much should we trust micro-data? A comparison of the socio-demographic profile of Malawian households using census, LSMS and DHS data

This paper assesses the empirical representativeness of micro-data by comparing the Malawi 2008 census to two representative household surveys – ‘the Living Standard Measurement Survey’ and the ‘Demographic and Health Survey’ – both implemented in Malawi in 2010. The comparison of descriptive statistics – demographics, asset ownership, and living conditions – shows considerable similarities despite statistically identifiable differences due to the large samples. Differences mainly occur when wording, scope, and pre-defined answer categories diverge across surveys. Multivariate analyses are considerably less representative due to loss of observations with composite indicators yielding higher comparability as individual ones. Household-level fixed-effect specifications produce more similar results, yet are not suited for policy conclusions. Comparability of micro-data should not be assumed but checked on a case-by-case basis. Still, micro-data constitute reliable grounds for factually informed conclusions if design and context are appropriately considered

Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design

Although experimental studies are regarded as the method of choice for determining causal influences, these are not always practical or ethical to answer vital questions in health and social research (e.g., one cannot assign individuals to a “childhood trauma condition” in studying the causal effects of childhood trauma on depression). Key to solving such questions are observational studies. Mendelian Randomization (MR) is an influential method to establish causality in observational studies. MR uses genetic variants to test causal relationships between exposures/risk factors and outcomes such as physical or mental health. Yet, individual genetic variants have small effects, and so, when used as instrumental variables, render MR liable to weak instrument bias. Polygenic scores have the advantage of larger effects, but may be characterized by horizontal pleiotropy, which violates a central assumption of MR. We developed the MR-DoC twin model by integrating MR with the Direction of Causation twin model. This model allows us to test pleiotropy directly. We considered the issue of parameter identification, and given identification, we conducted extensive power calculations. MR-DoC allows one to test causal hypotheses and to obtain unbiased estimates of the causal effect given pleiotropic instruments, while controlling for genetic and environmental influences common to the outcome and exposure. Furthermore, the approach allows one to employ strong instrumental variables in the form of polygenic scores, guarding against weak instrument bias, and increasing the power to detect causal effects of exposures on potential outcomes. Beside allowing to test pleiotropy directly, incorporating in MR data collected from relatives provide additional within-family data that resolve additional assumptions like random mating, the absence of the gene-environment interaction/covariance, no dyadic effects. Our approach will enhance and extend MR’s range of applications, and increase the value of the large cohorts collected at twin/family registries as they correctly detect causation and estimate effect sizes even in the presence of pleiotropy