MIP network member Joseph Ferrie recently spoke with HCEO to discuss how he uses longitudinal data to study economic mobility.
"There's a real need for data that follows people over long spans of time," he says. Having data that allows you to look at what happened to people early in life and how those things affected their life cycle outcomes is crucial, yet there are barriers to obtaining such data. "Following people from a cohort that you draw today for the next 80 years is just real tough to do."
Instead of gathering data in real time, Ferrie's work looks at data retrospectively. For example, one project has a sample of people born between 1890-99, who entered US census records in 1940, the first year the Census Bureau began collecting housing data.
"Based on where they were born, we also can figure out how much lead they were exposed to in the drinking water in the cities where they lived," Ferrie says. This is calculated using the pH of the water supply and information on what pipes were used in the cities people were born. "We see clearly that people who were in places that would have received a larger dose of lead in their early years, up until age 10, do considerably worse in terms of income, educational attainment, hours and weeks worked, and we can do the same with IQ."
In the interview, Ferrie discusses his use of historical data with other projects, and what it says about social mobility across generations.
Ferrie is a Professor of Economics and History at Northwestern University.