From statistical associations to causation: what developmentalists can learn from instrumental variables techniques coupled with experimental data.

In this article, the authors aim to make accessible the careful application of a method called instrumental variables (IV). Under the right analytic conditions, IV is one promising strategy for answering questions about the causal nature of associations and, in so doing, can advance developmental theory. The authors build on prior work combining the analytic approach of IV with the strengths of random assignment design, whether the experiment is conducted in the lab setting or in the "real world." The approach is detailed through an empirical example about the effects of maternal education on children's cognitive and school outcomes. With IV techniques, the authors address whether maternal education is causally related to children's cognitive development or whether the observed associations reflect some other characteristic related to parenting, income, or personality. The IV estimates show that maternal education has a positive effect on the cognitive test scores of children entering school. The authors conclude by discussing opportunities for applying these same techniques to address other questions of critical relevance to developmental science.

Duke Scholars

Author Lisa A. Gennetian Sanford School of Public Policy