Published online by Cambridge University Press: 03 April 2018
Big data is an exciting prospect for the field of economic history, which has long depended on the acquisition, keying, and cleaning of scarce numerical information about the past. This article examines two areas in which economic historians are already using big data – population and environment – discussing ways in which increased frequency of observation, denser samples, and smaller geographic units allow us to analyze the past with greater precision and often to track individuals, places, and phenomena across time. We also explore promising new sources of big data: organically created economic data, high resolution images, and textual corpora.
We thank the editors of the Journal for the opportunity to undertake this review, and for their comments and feedback throughout the writing of the paper. Jeremy Mikecz provided assistance in the research on agriculture and environment data. Evan Roberts gratefully acknowledges support from the Minnesota Population Center (Project 5R24HD041023), funded through grants from the Eunice Kennedy Shriver National Institute for Child Health and Human Development. Myron Gutmann acknowledges support from the University of Colorado Population Center funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (Project 2P2CHD066613-06) for research and administrative support.