Sarah Cattan

Senior Research Economist

Institute for Fiscal Studies, United Kingdom

NLS user since 2005

  • “Identifying Sibling Influence on Teenage Substance Use,” with Joseph Altonji and Iain Ware> IFS Working Paper No. 13/04. March 2013
What I learned from NLS data

A number of studies have found substantial correlations in risky behavior between siblings, raising the possibility that adolescents may directly influence the actions of their brothers or sisters. We assess the extent to which correlations in substance use and selling drugs are due to causal effects. Our identification strategy relies on panel data, the fact that the future does not cause the past, and the assumption that the direction of influence is from older siblings to younger siblings. Under this assumption along with other restrictions on dynamics, one can identify the causal effect from a regression of the behavior of the younger sibling on the past behavior and the future behavior of the older sibling. We also estimate a joint dynamic model of the behavior of older and younger siblings that allows for family specific effects, individual specific heterogeneity, and state dependence. We use the model to simulate the dynamic response of substance use to the behavior of the older sibling. Our results suggest that smoking, drinking, and marijuana use are affected by the example of older siblings, but most of the link between siblings arises from common influences.

Why I chose NLS data

What made the NLSY 97 ideal for this research are:
- The longitudinal nature of the data
- The rich information on risky behaviours
- The fact that it has a subsample of siblings