Using Digitized Newspapers to Address Measurement Error in Historical Data

Andreas Ferrara, Joung Yeob Ha and Randall Walsh

The Journal of Economic History, 2024, vol. 84, issue 1, 271-306

Abstract: 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 that 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 four recent economic history papers. Relative to the initial analyses, our results yield markedly larger coefficient estimates.

Date: 2024
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