Time preferences are reliable across time-horizons and verbal versus experiential tasks.

Individual differences in delay-discounting correlate with important real world outcomes, for example education, income, drug use, and criminality. As such, delay-discounting has been extensively studied by economists, psychologists and neuroscientists to reveal its behavioral and biological mechanisms in both human and non-human animal models. However, two major methodological differences hinder comparing results across species. Human studies present long time-horizon options verbally, whereas animal studies employ experiential cues and short delays. To bridge these divides, we developed a novel language-free experiential task inspired by animal decision-making studies. We found that the ranks of subjects' time-preferences were reliable across both verbal/experiential and second/day differences. Yet, discount factors scaled dramatically across the tasks, indicating a strong effect of temporal context. Taken together, this indicates that individuals have a stable, but context-dependent, time-preference that can be reliably assessed using different methods, providing a foundation to bridge studies of time-preferences across species. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Cohort of birth modifies the association between FTO genotype and BMI.

A substantial body of research has explored the relative roles of genetic and environmental factors on phenotype expression in humans. Recent research has also sought to identify gene-environment (or g-by-e) interactions, with mixed success. One potential reason for these mixed results may relate to the fact that genetic effects might be modified by changes in the environment over time. For example, the noted rise of obesity in the United States in the latter part of the 20th century might reflect an interaction between genetic variation and changing environmental conditions that together affect the penetrance of genetic influences. To evaluate this hypothesis, we use longitudinal data from the Framingham Heart Study collected over 30 y from a geographically relatively localized sample to test whether the well-documented association between the rs993609 variant of the FTO (fat mass and obesity associated) gene and body mass index (BMI) varies across birth cohorts, time period, and the lifecycle. Such cohort and period effects integrate many potential environmental factors, and this gene-by-environment analysis examines interactions with both time-varying contemporaneous and historical environmental influences. Using constrained linear age-period-cohort models that include family controls, we find that there is a robust relationship between birth cohort and the genotype-phenotype correlation between the FTO risk allele and BMI, with an observed inflection point for those born after 1942. These results suggest genetic influences on complex traits like obesity can vary over time, presumably because of global environmental changes that modify allelic penetrance.

A genetic instrumental variables analysis of the effects of prenatal smoking on birth weight: evidence from two samples.

There is a large literature showing the detrimental effects of prenatal smoking on birth and childhood health outcomes. It is somewhat unclear though, whether these effects are causal or reflect other characteristics and choices by mothers who choose to smoke that may also affect child health outcomes or biased reporting of smoking. In this paper we use genetic markers that predict smoking behaviors as instruments to address the endogeneity of smoking choices in the production of birth and childhood health outcomes. Our results indicate that prenatal smoking produces more dramatic declines in birth weight than estimates that ignore the endogeneity of prenatal smoking, which is consistent with previous studies with non-genetic instruments. We use data from two distinct samples from Norway and the United States with different measured instruments and find nearly identical results. The study provides a novel application that can be extended to study several behavioral impacts on health and social and economic outcomes.

Genetic lotteries within families.

Drawing on findings from the biomedical literature, this paper introduces the idea that specific exogenously inherited differences in the genetic code between full biological siblings can be used to test within-family estimators and potentially improve our understanding of economic relationships. These points are illustrated with an application to identify the causal impact of several poor health conditions on academic outcomes. We present evidence that family fixed effects estimators by themselves cannot fully account for the endogeneity of poor health when estimating education production functions. Further, our analysis elucidates the situations under which genetic markers can serve as instrumental variables for specific health conditions.

The impact of poor health on academic performance: New evidence using genetic markers.

This paper examines the influence of health conditions on academic performance during adolescence. To account for the endogeneity of health outcomes and their interactions with risky behaviors we exploit natural variation within a set of genetic markers across individuals. We present evidence that specific genetic markers have good statistical properties to identify the impacts of ADHD, depression and obesity. These markers help reveal a new dynamism from poor health to lower academic achievement with substantial heterogeneity in their impacts across genders. Our investigation further exposes the considerable challenges in identifying health impacts due to the prevalence of comorbid health conditions, with clear implications for the health economics literature.

Worker sorting, compensating differentials and health insurance: evidence from displaced workers.

This article introduces an empirical strategy to the compensating differentials literature that (i) allows both individual observed and unobserved characteristics to be rewarded differently in firms based on health insurance provision, and (ii) selection to jobs that provide benefits to operate on both sides of the labor market. Estimates of this model are used to directly test empirical assumptions that are made with popular econometric strategies in the health economics literature. Our estimates reject the assumptions underlying numerous cross sectional and longitudinal estimators. We find that the provision of health insurance has influenced wage inequality. Finally, our results suggest there have been substantial changes in how displaced workers sort to firms that offer health insurance benefits over the past two decades. We discuss the implications of our findings for the compensating differentials literature.