From Whence Commeth Data Misreporting? A Survey of Benford’s Law and Digit Analysis in the Time of the COVID-19 Pandemic

Author:

Vâlsan Călin1ORCID,Puiu Andreea-Ionela2ORCID,Druică Elena2ORCID

Affiliation:

1. William School of Business, Bishop’s University, Sherbrooke, QC J1M 1Z7, Canada

2. Department of Applied Economics and Quantitative Analysis, Faculty of Business and Administration, University of Bucharest, 030018 Bucharest, Romania

Abstract

We survey the literature on the use of Benford’s distribution digit analysis applied to COVID-19 case data reporting. We combine a bibliometric analysis of 32 articles with a survey of their content and findings. In spite of combined efforts from teams of researchers across multiple countries and universities, using large data samples from a multitude of sources, there is no emerging consensus on data misreporting. We believe we are nevertheless able to discern a faint pattern in the segregation of findings. The evidence suggests that studies using very large, aggregate samples and a methodology based on hypothesis testing are marginally more likely to identify significant deviations from Benford’s distribution and to attribute this deviation to data tampering. Our results are far from conclusive and should be taken with a very healthy dose of skepticism. Academics and policymakers alike should remain mindful that the misreporting controversy is still far from being settled.

Funder

The Senate Research Committee of Bishop’s University, Canada

Publisher

MDPI AG

Reference49 articles.

1. Nigrini, M.J. (2012). Benford’s Law: Applications for Forensic Accounting, Auditing, and Fraud Detection, Wiley.

2. A Benford’s Law Based Methodology for Fraud Detection in Social Welfare Programs: Bolsa Familia Analysis;Azevedo;Phys. A Stat. Mech. Its Appl.,2021

3. Benford Law: A Fraud Detection Tool Under Financial Numbers Game: A Literature Review;Noorullah;Soc. Sci. Humanit. J.,2020

4. The Effective Use of Benford’s Law to Assist in Detecting Fraud in Accounting Data;Durtschi;J. Forensic Account.,2004

5. Performance of Public Health Surveillance Systems during the Influenza A(H1N1) Pandemic in the Americas: Testing a New Method Based on Benford’s Law;Idrovo;Epidemiol. Infect.,2011

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3