Detecting Problems in Survey Data Using Benford’s Law
"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.
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- Philipson, Tomas & Malani, Anup, 1999. "Measurement errors: A principal investigator-agent approach," Journal of Econometrics, Elsevier, vol. 91(2), pages 273-298, August.
- John Morrow, 2014.
"Benford's Law, families of distributions and a test basis,"
LSE Research Online Documents on Economics
60364, London School of Economics and Political Science, LSE Library.
- John Morrow, 2014. "Benford's Law, Families of Distributions and a Test Basis," CEP Discussion Papers dp1291, Centre for Economic Performance, LSE.
- Nye John & Moul Charles, 2007. "The Political Economy of Numbers: On the Application of Benford's Law to International Macroeconomic Statistics," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-14, July.
- Grendar, Marian & Judge, George & Schechter, Laura, 2007. "An empirical non-parametric likelihood family of data-based Benford-like distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 429-438.
- Paul Glewwe & Hai-Anh Hoang Dang, 2008. "The Impact of Decentralized Data Entry on the Quality of Household Survey Data in Developing Countries: Evidence from a Randomized Experiment in Vietnam," World Bank Economic Review, World Bank Group, vol. 22(1), pages 165-185, January. Full references (including those not matched with items on IDEAS)
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