Benford's law states that in many data sets the overall distribution of the significant digits tends to be logarithmic so that the numbers beginning with smaller significant digits occur more often than those with larger ones.  We investigate here  recent data on illicit financial flows from developing countries and reveal that the data does submit to Benford's law . Further, the general improvement in the statistical accuracy we find here supports the applicability of the two stage normalization in filtering out countries from database for which illicit financial flows are not substantial .
Benford's law states that in data sets from different phenomena leading digits tend to be distributed logarithmically such that the numbers beginning with smaller digits occur more often than those with larger ones. Particularly, the law is known to hold for different types of financial data. The Illicit Financial Flows (IFFs) exiting the developing countries are frequently discussed as hidden resources which could have been otherwise properly utilized for their development. We investigate here the distribution of the leading digits in the recent data on estimates of IFFs to look for the existence of a pattern as predicted by Benford's law and establish that the frequency of occurrence of the leading digits in these estimates does closely follow the law .
R
many data sets the overall distribution of the significant digits tends to be logarithmic so
data sets from different phenomena leading digits tend to be distributed logarithmically such
D
significant
A
Particularly, the law is known to hold for different types of financial data. The Illicit Financial Flows (IFFs) exiting the developing countries are frequently discussed as hidden resources which could have been otherwise properly utilized for their development.
A
the distribution of the leading digits in the
R
illicit financial flows from developing countries and reveal that the data does submit to
estimates of IFFs to look for the existence of a pattern as predicted by
R
. Further, the general improvement in the statistical accuracy we find here supports the applicability of the two stage normalization in filtering out countries from database for which illicit financial flows are not substantial
and establish that the frequency of occurrence of the leading digits in these estimates does closely follow the law