This work is cited by the following items of the Benford Online Bibliography:

Alexander, J (2009). Remarks on the use of Benford's law. Social Science Research Network (November 13, 2009). Available at SSRN: http://ssrn.com/abstract=1505147 or . DOI:10.2139/ssrn.1505147. | ||||

Amiram, D, Bozanic, Z and Rouen, E (2015). Financial statement errors: evidence from the distributional properties of financial statement numbers. Review of Accounting Studies 20(4), pp. 1540–1593. DOI:10.1007/s11142-015-9333-z. | ||||

Baryła, M (2012). Some Remarks about Benford's Distribution. Mathematical Economics 8(15), pp. 5-15. | ||||

Fellman, J (2014). The Benford paradox. Journal of statistical and econometric methods 3(4), pp. 1-20. ISSN/ISBN:2241-0384 . | ||||

Fellman, J (2017). Benfordparadoxen. Arkhimedes 2017(4), pp. 26-33. SWE | ||||

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. | ||||

Grendar, M, Judge, G and Schechter, L (2007). An empirical non-parametric likelihood family of data-based Benford-like distributions. Physica A: Statistical Mechanics and its Applications 380, pp. 429-438. ISSN/ISBN:0378-4371. DOI:10.1016/j.physa.2007.02.062. | ||||

Holz, CA (2013). The Quality of China's GDP Statistics. Munich Personal RePEc Archive Paper No. 51864; available online at http://mpra.ub.uni-muenchen.de/51864/; last accessed June 23, 2014. | ||||

Holz, CA (2014). The quality of China’s GDP statistics. China Economic Review, vol. 30, September 2014, pp. 309–338. DOI:10.1016/j.chieco.2014.06.009. | ||||

Hürlimann, W (2015). On the uniform random upper bound family of first significant digit distributions. Journal of Informetrics, Volume 9, Issue 2, pp. 349–358. DOI:10.1016/j.joi.2015.02.007. | ||||

Hürlimann, W (2015). Benford's Law in Scientific Research. International Journal of Scientific & Engineering Research, Volume 6, Issue 7, pp. 143-148. ISSN/ISBN:2229-5518. | ||||

Jasak, Z (2010). Benfordov zakon i reinforcement učenje (Benford's Law and reinforcment learning) . MSc Thesis, University of Tuzla, Bosnia. SRP | ||||

Joenssen, DW (2013). Two digit testing for Benford's Law. Proceedings of the ISI World Statistics Congress, 59th Session in Hong Kong. | ||||

Joenssen, DW (2014). Testing for Benford's Law: A Monte Carlo Comparison of Methods. Preprint available at SSRN: https://ssrn.com/abstract=2545243; last accessed Mar 24, 2019 . DOI:10.2139/ssrn.2545243. | ||||

Judge, G and Schechter, L (2009). Detecting problems in survey data using Benford’s law. J. Human Resources 44, pp. 1-24. DOI:10.3368/jhr.44.1.1. | ||||

Kalaichelvan, M and Jie, SLK (2012). A Critical Evaluation of the Significance of Round Numbers in European Equity Markets in Light of the Predictions from Benford's Law. International Research Journal of Finance and Economics 95, pp. 196-210. ISSN/ISBN:1450-2887. | ||||

Leemann, L and Bochsler, D (2014). A systematic approach to study electoral fraud. Electoral Studies, Vol. 35, Num. 0, pp. 33-47. ISSN/ISBN:0261-3794. DOI:10.1016/j.electstud.2014.03.005. | ||||

Plaček, M (2013). Is data of Znojmo reliable?. New Trends 2013 - Proceedings of 8th international scientific conference. Private College of Economics Studies Znojmo, p.52-57. ISSN/ISBN: 978-80-87314-54-8 . CZE | ||||

Plaček, M and Krápek, M (2014). The applications of Benford´s law to macroeconomic data – Current Experience . New Trends 2014 - Proceedings of 9th international scientific conference. Private College of Economic Studies Znojmo, pp. 428-432. ISSN/ISBN:2336–7431 . CZE | ||||

Rauch, B, Brähler, G, Engel, S and Göttsche, M (2011). Fact and Fiction in EU-Governmental Economic Data. German Economic Review 12(3), pp. 243-255. DOI:10.1111/j.1468-0475.2011.00542.x. | ||||

Sadaf, R (2017). Advanced Statistical Techniques For Testing Benford'S Law. Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pp. 229-238. | ||||

Tsagbey, S, de Carvalho, M and Page, GL (2017). All Data are Wrong, but Some are Useful? Advocating the Need for Data Auditing . The American Statistician, 71, pp. 231--235. DOI:10.1080/00031305.2017.1311282. |