Judge, George, and Laura Schechter. 2009. “Detecting Problems in Survey Data Using Benford’s Law.” Journal of Human Resources 44(1): 1–24.
“It is 15:00 in Nairobi. Do you know where your enumerators are??”
Good quality data is paramount for applied economic research. If the data are distorted, corresponding conclusions may be incorrect. We demonstrate how Benford’s law, the distribution that first digits of numbers in certain data sets should follow, can be used to test for data abnormalities. We conduct an analysis of nine commonly used data sets and find that much data from developing countries is of poor quality while data from the United States seems to be of better quality. Female and male respondents give data of similar quality.
George Judge is an assistant professor in the graduate school, UC Berkeley. e-mail: judge@are.berkeley.edu. Laura Schechter is an assistant professor of agricultural and applied economics, University of Wisconsin–Madison. e-mail: lschechter@wisc.edu. The order of the authors’ names has only alphabetical significance. The authors have benefited from helpful comments from Jennifer Alix-Garcia, Wendy Cho, Joanne Lee, Ted Miguel, Michael Roberts, Elisabeth Sadoulet, two anonymous referees, and seminar participants at BREAD, Purdue, and UW Madison. John Morrow provided excellent research assistance and created the convenient online utility to test your own data against Benford’s law at http://www.checkyourdata.com. The second author received funding from USDA Hatch grant 142-1038. The Paraguayan data used in this article are available from the authors from March 2010 to February 2013. The other eight data sets can be obtained from the corresponding institutions. The authors are willing to help other scholars pursue those data.