Detecting Problems in Military Expenditure Data Using Digital Analysis

Rauch, Bernhard; Göttsche, Max; Langenegger, Stephan

doi:10.1080/10242694.2013.763438

Cited by 9 publications

(6 citation statements)

References 37 publications

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“…Articles investigating EM at a macro-level perspective principally used the stock-flow adjustments approach, defined as the difference between the budget deficit and the change in public debt (von Hagen and Wolff, 2006;Reischmann, 2016;Maltritz and W€ uste, 2020) or used Benford's law (e.g. Rauch et al, 2011Rauch et al, , 2014. Six articles (about 8%) used other research methods, such as structured equation modeling (e.g.…”

Section: Methodsmentioning

confidence: 99%

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Earnings management in public-sector organizations: a structured literature review

Bisogno

Donatella

2021

JPBAFM

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PurposeResearch dealing with earnings management in the public-sector context is expanding. This paper aims to review the existing literature to understand how research is developing and points out gaps deserving further investigation.Design/methodology/approachThis study uses the structured literature methodology to investigate the state-of-the-art and future directions of the literature on earnings management in the public sector. In total, 78 articles were explored.FindingsThe critical analysis of the literature shows that different but related streams of literature are emerging, focused on both a macro- and a micro-level perspective (mainly local governments and state-owned enterprises).Originality/valueThis study is the first that offers a comprehensive review of the literature on the emerging topic of earnings management in the public-sector context. The structured literature review enables the identification of future directions for the literature in this field.

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Section: Methodsmentioning

confidence: 99%

“…about 38% in both cases). Nine articles investigated America, while three studies concentrated on a sample of countries from several continents (Rauch et al , 2014; Reischmann, 2016; Kartiko et al , 2018).…”

Section: Research On Earnings Management In the Public Sector: Insigh...mentioning

confidence: 99%

Earnings management in public-sector organizations: a structured literature review

Bisogno

Donatella

2021

JPBAFM

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“…& Stoltz 2013, Nye & Moul 2007), and military expenditures (Rauch et al 2014). Interestingly, of the 27 countries reporting military data to the United Nations, the United States and United Kingdom had the lowest conformance with Benford's law, indicating the lowest data quality.…”

Section: Percentage Of Observations Per Binmentioning

confidence: 99%

Forensic Accounting

Honigsberg

2020

Annu. Rev. Law. Soc. Sci.

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Forensic accounting serves as a regulatory and investment tool that allows interested professionals to predict whether firms are engaged in financial reporting misconduct. Financial reporting misconduct has severe economic and personal consequences. Not only does such misconduct distort the allocation of economic resources, but investors and employees of these firms incur substantial financial and psychological harms. In essence, forensic accounting aims to mitigate these harms by predicting the likelihood a firm has committed financial reporting misconduct—thus allowing for early detection of such misconduct. In this review, I provide an overview of the most popular forensic accounting techniques in the literature and the effectiveness of such techniques. Although traditional forensic models tended to focus on behavioral characteristics of the executives who commit financial misconduct or to take a purely numerical approach based on financial data, more recent models combine big data analysis with psychological intuitions. Expected final online publication date for the Annual Review of Law and Social Science, Volume 16 is October 13, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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“…Google Scholar (http://scholar.google.com) reports that the RGBE paper has 57 citations. Rauch, Göttsche, and Langenegger (2014) analyzed military expenditures reported to the United Nations Office for Disarmament Affairs. They concluded that the United States and the United Kingdom have the lowest quality military data because they had the worst conformity to Benford.…”

Section: Analysis Of Data Subsetsmentioning

confidence: 99%

Persistent Patterns in Stock Returns, Stock Volumes, and Accounting Data in the U.S. Capital Markets

Nigrini

2015

Journal of Accounting, Auditing & Finance

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Benford's Law gives the expected frequencies of the digits in tabulated data. The expected frequencies show a large bias toward the low digits. An analysis of the Center for Research in Security Prices (CRSP) data shows that the daily returns have a near-perfect fit to Benford's Law. The daily volumes also have a close fit to Benford's Law but there are deviations due to round lot trading and the fact that some of the data are rounded to the nearest hundred. An analysis of Compustat data also shows a close fit to Benford's Law with some explainable deviations. The expected returns and the abnormal returns used in event studies over an extended period showed that these numbers also conformed to Benford's Law. Recent studies have divided a population into subsets and then tested the subsets for conformity to Benford's Law. The conclusions are that the subsets with the weakest fit to Benford were fraudulent. The problems with this approach are discussed, and these include statistical considerations, issues with using Compustat data, other plausible explanations for a lack of conformity, and the fact that there is no clear link between a change in the leading digit of a number and the materiality of the dollar value of the change.

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Detecting Problems in Military Expenditure Data Using Digital Analysis

Cited by 9 publications

References 37 publications

Earnings management in public-sector organizations: a structured literature review

Earnings management in public-sector organizations: a structured literature review

Forensic Accounting

Persistent Patterns in Stock Returns, Stock Volumes, and Accounting Data in the U.S. Capital Markets

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