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Wang, D, Chen, F, Mao, J, Liu, N and Rong, F (2022). Are the official national data credible? Empirical evidence from statistics quality evaluation of China's coal and its downstream industries . Energy Economics, p. 106310.

This work cites the following items of the Benford Online Bibliography:

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. View Complete Reference Online information Works that this work references Works that reference this work
Badal-Valero, E, Alvarez-Jareño, JA and Pavía, JM (2018). Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case. Forensic Science International 282, pp. 24-34. DOI:10.1016/j.forsciint.2017.11.008. View Complete Reference Online information Works that this work references Works that reference this work
Banks, DG (2000). Get M.A.D. with the Numbers! Moving Benford's Law from Art to Science. Fraud Magazine, September/October 2000. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L, Cerasa, A, Cerioli, A and Perrotta, D (2018). Goodness-of-fit testing for the Newcomb-Benford law with application to the detection of customs fraud. Journal of Business & Economic Statistics 36(2), pp. 346-358. DOI:10.1080/07350015.2016.1172014. View Complete Reference Online information Works that this work references Works that reference this work
Barney, BB and Schulzke, KS (2016). Moderating "Cry Wolf" events with excess MAD in Benford's law research and practice. J. Forensic Account. Res. 1 (1), A66–A90. DOI:10.2308/jfar-51622. View Complete Reference Online information Works that this work references Works that reference this work
Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Cho, WKT and Gaines, BJ (2007). Breaking the (Benford) law: Statistical fraud detection in campaign finance. American Statistician 61(3), pp. 218-223. ISSN/ISBN:0003-1305. DOI:10.1198/000313007X223496. View Complete Reference Online information Works that this work references Works that reference this work
Demir, B and Javorcik, B (2020). Trade Policy Changes, Tax Evasion and Benford’s Law. Journal of Development Economics, 144. DOI:10.1016/j.jdeveco.2020.102456. View Complete Reference Online information Works that this work references Works that reference this work
Fewster, RM (2009). A Simple Explanation of Benford's Law. American Statistician 63(1), pp. 26-32. DOI:10.1198/tast.2009.0005. View Complete Reference Online information Works that this work references Works that reference this work
Garlick, R, Orkin, K and Quinn, S (2019). Call Me Maybe: Experimental Evidence on Frequency and Medium Effects in Microenterprise Surveys. World Bank Economic Review, forthcoming. View Complete Reference Online information Works that this work references Works that reference this work
Hill, TP (1995). A Statistical Derivation of the Significant-Digit Law. Statistical Science 10(4), pp. 354-363. ISSN/ISBN:0883-4237. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
Horton, J, Kumar, DK and Wood, A (2020). Detecting academic fraud using Benford law: The case of Professor James Hunton. Research Policy 49(8), 104084 . DOI:10.1016/j.respol.2020.104084. View Complete Reference Online information Works that this work references Works that reference this work
Huang, Y, Niu, Z and Yang, C (2020). Testing firm-level data quality in China against Benford’s Law. Economics Letters 192, 109182. DOI:10.1016/j.econlet.2020.109182. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
Kaiser, M (2019). Benford’s Law As An Indicator Of Survey Reliability—Can We Trust Our Data?. Journal of Economic Surveys Vol. 00, No. 0, pp. 1–17. DOI:10.1111/joes.12338. View Complete Reference Online information Works that this work references Works that reference this work
Lesperance, M, Reed, WJ, Stephens, MA, Tsao, C and Wilton, B (2016). Assessing Conformance with Benford’s Law: Goodness-Of-Fit Tests and Simultaneous Confidence Intervals. PLoS One 11(3): e0151235; published online 2016 Mar 28. DOI:10.1371/journal.pone.0151235. View Complete Reference Online information Works that this work references Works that reference this work
Lu, F and Boritz, JE (2005). Detecting Fraud in Health Insurance Data: Learning to Model Incomplete Benford’s Law Distributions. Machine Learning: ECML 2005 (Proceedings). Lecture Notes in Artificial Intelligence 3270, pp. 633-640. ISSN/ISBN:0302-9743. View Complete Reference Online information Works that this work references Works that reference this work
Newcomb, S (1881). Note on the frequency of use of the different digits in natural numbers. American Journal of Mathematics 4(1), pp. 39-40. ISSN/ISBN:0002-9327. DOI:10.2307/2369148. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Nigrini, MJ (2012). Benford's Law: Applications for Forensic Accounting, Auditing, and Fraud Detection . John Wiley & Sons: Hoboken, New Jersey. ISSN/ISBN:978-1-118-15285-0. DOI:10.1002/9781119203094. View Complete Reference Online information Works that this work references Works that reference this work
Qu, H, Steinberg, R and Burger, R (2020). Abiding by the Law? Using Benford's Law to Examine the Accuracy of Nonprofit Financial Reports. Nonprofit and Voluntary Sector Quarterly 49(3), pp. 548-570. DOI:10.1177/0899764019881510. View Complete Reference Online information Works that this work references Works that reference this work
Riccioni, J and Cerqueti, R (2018). Regular paths in financial markets: Investigating the Benford’s law. Chaos, Solitons and Fractals 107, pp. 186-194. DOI:10.1016/j.chaos.2018.01.008. View Complete Reference Online information Works that this work references Works that reference this work
Rodriguez, RJ (2004). Reducing False Alarms in the Detection of Human Influence on Data. Journal of Accounting, Auditing & Finance 19(2), pp. 141-158. DOI:10.1177/0148558X0401900202. View Complete Reference Online information Works that this work references Works that reference this work
Sambridge, M and Jackson, A (2020). National COVID numbers — Benford’s law looks for errors. Nature 581(7809), p. 384. DOI:10.1038/d41586-020-01565-5. View Complete Reference Online information Works that this work references Works that reference this work
Slepkov, AD, Ironside, KB and DiBattista, D (2015). Benford’s Law: Textbook Exercises and Multiple-Choice Testbanks. PLoS ONE 10(2): e0117972. DOI:10.1371/journal.pone.0117972. View Complete Reference Online information Works that this work references Works that reference this work
Wallace, WA (2002). Assessing the quality of data used for benchmarking and decision-making. The Journal of Government Financial Management 51(3), pp. 16-22. View Complete Reference Online information Works that this work references Works that reference this work