Bernhard Rauch

Fact and Fiction in EU-Governmental Economic Data

Abstract To detect manipulations or fraud in accounting data, auditors have successfully used Benford’s law as part of their fraud detection processes. Benford’s law proposes a distribution for first digits of numbers in naturally occurring data. Government accounting and statistics are similar in nature to financial accounting. In the European Union (EU), there is pressure to comply with the Stability and Growth Pact criteria. Therefore, like firms, governments might try to make their economic situation seem better. In this paper, we use a Benford test to investigate the quality of macroeconomic data relevant to the deficit criteria reported to Eurostat by the EU member states. We find that the data reported by Greece shows the greatest deviation from Benford’s law among all euro states.

Detecting Problems in Military Expenditure Data Using Digital Analysis

The UN asks governments to report key figures of their annual military budgets with the aim of creating trust among member states. This goal can only be achieved if the data reported is accurate. However, although there are many reasons for governments to falsify data, the UN does not check for manipulation. In this paper, we apply Benford’s law to the military expenditure data of 27 states taken from the UN register. Our analysis of the first digits shows that the states with the greatest deviations from the expected Benford distribution and therefore the lowest data quality are the USA and the UK.

Deficit versus social statistics: empirical evidence for the effectiveness of Benford’s law

When analysing the quality of data, nonconformity with Benford’s law can be a useful indicator of poor data quality, which may be a result of fraud or manipulation. In this article, we use Benford’s law to compare government social security statistics with deficit related data reported by the EU member states to Eurostat. Unlike deficit related data, social security statistics are not subject to the fiscal monitoring connected with excessive deficit procedures (EDP) and the incentive to manipulate such statistics is therefore lower. Our results show that, across all but one 27 EU member states, the deviations from the Benford distribution in the social security statistics are considerably smaller than those shown by the deficit data. This leads us to conclude that, as would be expected, European governments behave in accordance with the incentives, i.e. while the quality of the social security statistics appears to be higher, there is a widespread tendency to report incorrect deficit data. We therefore consider our results to be evidence of the effectiveness of Benford’s law in identifying manipulated data.

LIBOR Manipulation – Empirical Analysis of Financial Market Benchmarks Using Benford's Law

The London inter-bank offered rate (LIBOR) serves as a benchmark for many financial transactions worldwide today. These rates have been subject to manipulative conduct, false reporting and collusion. In forensic accounting, the Benford test has been implemented to successfully detect manipulated data. In this paper, we develop an approach to enable the application of the Benford method to LIBOR and other financial market benchmarks. The test results for all 150 LIBOR rates show a concentration of notably high deviations from the Benford distribution in single periods and currencies. Moreover, we find that the LIBOR quotes deviate much more than the banks’ credit default swap spreads. We conclude that all banks are presumably involved in the submission of manipulated data. Furthermore, we show that other financial benchmarks are worthy of closer scrutiny.

Empirical Methods in Competition Analysis – Applying Benford's Law to the Western Australian Petroleum Market

In this paper, we develop a robust empirical indicator for screening and detecting statistical anomalies that may provide circumstantial evidence of explicit collusion between companies or a cartelized market. The paper deals with the question of whether in the context of forensic research on cartels a Benford test can be used to improve target selection in order to increase effectiveness and efficiency in identifying companies and markets worthy of closer scrutiny. In various contexts it has been shown that a deviation from the Benford distribution can indicate fraud or data manipulation. We apply Benford’s law to released price data of the Western Australian petroleum market from 2004 to 2012. We show that the deviation from the Benford distribution in relative margin changes is positively correlated with well known indicators of collusion and conclude that anti-competitive behavior can be identified by the Benford method. Moreover, we identify periods, brands and petroleum products showing a concentration of notably higher deviations from Benford’s law.