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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.
Ausloos, M, Cerqueti, R and Mir, TA (2017). Data science for assessing possible tax income manipulation: The case of Italy. Chaos, Solitons and Fractals 104, pp. 238–256. DOI:10.1016/j.chaos.2017.08.012.





Davydov, D and Swidler, S (2016). Auditing Bank Financial Statements in Emerging Market Countries: The Use of the Benford Distribution. In: Risk Management in Emerging Markets, Emerald Group Publishing Limited, Boubaker, S., Buchanan, B. and Nguyen, D. (Eds.), pp. 187200. DOI:10.1108/978178635452520161018.





Davydov, D and Swidler, S (2016). Reading Russian Tea Leaves: Assessing the Quality of Bank Financial Statements with the Benford Distribution. Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(04), pp. 120. DOI:10.1142/S0219091516500211.





Fonseca, PMT da (2016). Digit analysis using Benford's Law: A Bayesian approach. Masters Thesis, ISEG  Instituto Superior de Economia e Gestão, Lisbon School of Economics & Management, Portugal.





Mantone, PS (2013). Using Analytics to Detect Possible Fraud: Tools and Techniques. John Wiley & Sons; Chapter 7 "Benford's Law, and Yes  Even Statistics" p. 237. ISSN/ISBN:9781118585627.





Mir, TA, Ausloos, M and Cerqueti, R (2014). Benford’s law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions. Eur. Phys. J. B (2014) 87: 261. ISSN/ISBN:14346028. DOI:10.1140/epjb/e2014505252.





Van Caneghem, T (2016). NPO Financial Statement Quality: An Empirical Analysis Based on Benford’s Law. International Journal of Voluntary and Nonprofit Organizations 27(6), pp. 2685–2708. DOI:10.1007/s1126601596294.




