Paul Seabright: Narrative and Statistical Explanations in History and the Social Sciences

Narrative social science seeks to make social processes intelligible in terms of the actions and predicaments of recognizable human beings facing recognizably human challenges – birth, childhood, wandering, struggle, work, love, parenthood, ageing, sickness, death. Formal modeling as in economics is not necessarily anti-narrative, since many models use ““representative agents”“ whose behavior is mirrored in the aggregate behavior of groups and whole societies. Statistical models, however, are very different, since societies can behave in ways that resemble the behavior of none of their members. All members of a society grow older, but the society itself can grow younger. Societies can collectively know things that none of their members know, and can collectively choose things that none of their members have chosen. Contrary to common claims, recent social science is not on a trajectory away from narrative and towards statistics, notwithstanding the massive increase in techniques of analyzing big data. On the contrary, many forms of social science still require storytelling to be interpretable. Many novel scientific techniques illuminate particular events and not just statistical aggregates. This presentation will illustrate this claim with examples from history, economics, political science, archaeology and epidemiology.