TODAY'S hottest economics blogpost is a fascinating piece of analysis by Jialan Wang, built around the statistical regularity known as Benford's law. Named for physicist Frank Benford, the law notes that within sets of numbers that span orders of magnitude, the distribution of first digits is strikingly regular: numbers beginning in 1 occur about 30% of the time, those beginning in 2 about 18% of the time, falling to roughly 5% of the time for the number 9. The law shows up across a wide range of number sets—economic datapoints like prices, natural ones like the height of mountains or length of rivers, physical addresses—and persists across units of measurement.

This regularity has been used to identify cases of fraud in public documents. Someone cooking books is likely to choose numbers somewhat randomly, generating a distribution of digits far more uniform than Benford's law would predict. Any divergence that shows up sets off alarm bells in those looking for funny business.

That takes us to Ms Wang, a finance professor at Washington University. She conducted an analysis of quarterly accounting data from over 20,000 firms and tested how their figures stacked up against Benford's law. Sure enough, reported assets and revenues fell into the familiar pattern. Of course, the relationship wasn't exactly as Benford's law would predict; there were small deviations in the numbers. Ms Wang then decided to put together a chart showing the path of those deviations over time. Here's what she got:

As Ms Wang notes, this isn't decisive proof of misbehaviour. It is suggestive, however, of the possibility that systematic number-fudging has been on the upswing in recent decades. Moreover, it's an excellent use of clever statistical analysis to provide a new perspective on an economic question.