ABSTRACT
Many, if not most, questions in the social sciences involve causal processes that unfold over time. Researchers often wonder whether events happening at some initial point in time lead to changes in other events happening in the future. For instance, does getting assigned to a small class size in first grade lead to improvements in student performance in second grade and beyond? Does attending an Ivy League college increase adult earnings? Does getting married lead to improvements in men's psychological or physical health? The potential questions of interest are endless. As such, finding and employing rigorous empirical methods able to address causal processes unfolding over time — sometimes referred to as turning points — is critical to the accumulation of social scientific knowledge. This chapter employs and illustrates one such method, inverse probability-of-treatment weighting (IPTW), to help understand our potential for estimating time-varying causes and outcomes.
