Alcohol Exposure In Utero and Child Academic Achievement

We examine the effect of prenatal alcohol exposure on child academic achievement. We use a genetic variant in the maternal alcohol-metabolism gene ADH1B to instrument for alcohol exposure, whilst controlling for the child’s genotype on the same variant. We show that the instrument is unrelated to an extensive range of parental characteristics and behaviour. OLS regressions suggest an ambiguous association between alcohol exposure and attainment but there is a strong social gradient in drinking, with mothers in higher socio-economic groups more likely to drink. In contrast to the OLS, the IV estimates show clear negative effects of prenatal alcohol exposur

The Many Weak Instrument Problem and Mendelian Randomization.

Instrumental variable estimates of causal effects can be biased when using many instruments that are only weakly associated with the exposure. We describe several techniques to reduce this bias and estimate corrected standard errors. We present our findings using a simulation study and an empirical application. For the latter, we estimate the effect of height on lung function, using genetic variants as instruments for height. Our simulation study demonstrates that, using many weak individual variants, two-stage least squares (2SLS) is biased, whereas the limited information maximum likelihood (LIML) and the continuously updating estimator (CUE) are unbiased and have accurate rejection frequencies when standard errors are corrected for the presence of many weak instruments. Our illustrative empirical example uses data on 3631 children from England. We used 180 genetic variants as instruments and compared conventional ordinary least squares estimates with results for the 2SLS, LIML, and CUE instrumental variable estimators using

Evidence of detrimental effects of prenatal alcohol exposure on offspring birthweight and neurodevelopment from a systematic review of quasi-experimental studies

Background: Systematic reviews of prenatal alcohol exposure effects generally only include conventional observational studies. However, estimates from such studi

Estimating marginal medical care expenditures using genetic variants as instrumental variables: Mendelian Randomization in economic evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming a

Mortality and the Business Cycle: Evidence from Individual and Aggregated Data

There has been much interest recently in the relationship between economic conditions and mortality, with some studies showing that mortality is pro-cyclical, while others find the opposite. Some suggest that the aggregation level of analysis (e.g. individual vs. regional) matters. We use both individual and aggregated data on a sample of 20–64 year-old Swedish men from 1993 to 2007. Our results show that the association between the business cycle and mortality does not depend on the level of analysis: the sign and magnitude of the parameter estimates are similar at the individual level and the aggregate (county) level; both showing pro-cyclical mortality