Deckert, J, Myagkov, M and Ordeshook, PC (2011). Benford's Law and the Detection of Election Fraud. Political Analysis 19(3), pp. 245268.
This work is cited by the following items of the Benford Online Bibliography:
Note that this list may be incomplete, and is currently being updated. Please check again at a later date.
Beber, B and Scacco, A (2012). What the Numbers Say: A DigitBased Test for Election Fraud. Political Analysis 20 (2), pp. 211234. DOI:10.1093/pan/mps003.





Berger, A and Eshun, G (2014). Benford solutions of linear difference equations. Theory and Applications of Difference Equations and Discrete Dynamical Systems, Springer Proceedings in Mathematics & Statistics Volume 102, pp. 2360. ISSN/ISBN:9783662441398. DOI:10.1007/9783662441404_2.





Berger, A and Hill, TP (2015). An Introduction to Benford's Law. Princeton University Press: Princeton, NJ. ISSN/ISBN:9780691163062.





Goodman, WM (2013). Reality Checks for a Distributional Assumption: The Case of “Benford’s Law”. JSM Proceedings. Alexandria, VA: American Statistical Association (2013), pp. 27892803.
(Also published on the Statistical Literacy website, at URL: http://www.statlit.org/pdf/2013GoodmanASA.pdf)
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Holz, C (2013). The Quality of China's GDP Statistics. Munich Personal RePEc Archive Paper No. 51864; available online at http://mpra.ub.unimuenchen.de/51864/; last accessed June 23, 2014.





Kossovsky, AE (2014). Benford's Law: Theory, the General Law of Relative Quantities, and Forensic Fraud Detection Applications. World Scientific Publishing Company: Singapore. ISSN/ISBN:9789814583688.





Leemann, L and Bochsler, D (2014). A systematic approach to study electoral fraud. Electoral Studies, Vol. 35, Num. 0, pp. 3347. ISSN/ISBN:02613794. DOI:10.1016/j.electstud.2014.03.005.





Mebane, WR Jr (2011). Comment on “Benford's Law and the Detection of Election Fraud”. Political Analysis 19(3), pp. 269272. DOI:10.1093/pan/mpr024.





Miller, SJ (ed.) (2015). Benford's Law: Theory and Applications. Princeton University Press: Princeton and Oxford. ISSN/ISBN:9780691147611.




