Economic analysis and statistical disclosure limitation
Brookings Papers on Economic Activity, (2015)Abstract
This paper explores the consequences for economic research of methods used by statistical agencies to protect confidentiality of their respondents. We first review the concepts of statistical disclosure limitation for an audience of economists who may be unfamiliar with these methods. Our main objective is to shed light on the effects of statistical disclosure limitation for empirical economic research. In general, the standard approach of ignoring statistical disclosure limitation leads to incorrect inference. We formalize statistical disclosure methods in a model of the data publication process. In the model, the statistical agency collects data from a population, but published a version of the data that have been intentionally distorted. The model allows us to characterize what it means for statistical disclosure limitation to be ignorable, and to characterize what happens when it is not. We then consider the effects of statistical disclosure limitation for regression analysis, instrumental variable analysis, and regression discontinuity design. Because statistical agencies do not always report the methods they use to protect confidentiality, we use our model to characterize settings in which statistical disclosure limitation methods are discoverable; that is, they can be learned from the released data. We conclude with advice for researchers, journal editors, and statistical agencies.