Determinants of self-reporting under the European corporate leniency program

We empirically investigate the determinants of self-reporting under the European corporate leniency program. Applying a data set consisting of 442 firm groups that participated in 76 cartels decided by the European Commission between 2000 and 2011, we find that the probability of a firm becoming the chief witness increases with its character as repeat offender, the size of the expected basic fine, the number of countries active in one group as well as the size of the firm’s share in the cartelized market. Our results have important implications for an effective prosecution of anti-cartel law infringers

Benford's law predicted digit distribution of aggregated income taxes: the surprising conformity of Italian cities and regions

The yearly aggregated tax income data of all, more than 8000, Italian municipalities are analyzed for a period of five years, from 2007 to 2011, to search for conformity or not with Benford's law, a counter-intuitive phenomenon observed in large tabulated data where the occurrence of numbers having smaller initial digits is more favored than those with larger digits. This is done in anticipation that large deviations from Benford's law will be found in view of tax evasion supposedly being widespread across Italy. Contrary to expectations, we show that the overall tax income data for all these years is in excellent agreement with Benford's law. Furthermore, we also analyze the data of Calabria, Campania and Sicily, the three Italian regions known for strong presence of mafia, to see if there are any marked deviations from Benford's law. Again, we find that all yearly data sets for Calabria and Sicily agree with Benford's law whereas only the 2007 and 2008 yearly data show departures from the law for Campania. These results are again surprising in view of underground and illegal nature of economic activities of mafia which significantly contribute to tax evasion. Some hypothesis for the found conformity is presented.Comment: 18 pages, 5 tables, 4 figures, 61 references, To appear in European Physical Journal

Applying Benford’s law to detect accounting data manipulation in the banking industry

We utilise Benford’s Law to test if balance sheet and income statement data broadly used to assess bank soundness were manipulated prior to and also during the global financial crisis. We find that all banks resort to loan loss provisions to manipulate earnings and income upwards. Distressed institutions that have stronger incentives to conceal their financial difficulties resort additionally to manipulating loan loss allowances and non-performing loans downwards. Moreover, manipulation is magnified during the crisis and expands to encompass regulatory capital