Using Digitized Newspapers to Refine Historical Measures: The Case of the Boll Weevil

This paper shows how to remove attenuation bias in regression analyses due to measurement error in historical data for a given variable of interest by using a secondary measure which can be easily generated from digitized newspapers. We provide three methods for using this secondary variable to deal with non-classical measurement error in a binary treatment: set identification, bias reduction via sample restriction, and a parametric bias correction. We demonstrate the usefulness of our methods by replicating two recent studies on the effect of the boll weevil. Relative to the initial analysis, our results yield markedly larger coefficient estimates.