In this paper we present a technique for assessing data quality based on conformity with Benford's Law, which states that the first digits of numbers generated from natural phenomena do not occur with equal frequency. If data do not conform to the Benford distribution, then questions arise about the process that generated it. Because neutral transformations should preserve conformity to Benford's Law, any macroeconomic adjustment that destroys this conformity should make those calculations suspect.Benford's Law is applied to one of the most commonly used data sets in economics: international macroeconomic statistics. We find that the World Bank international GDP data and purchasing power parity (PPP) corrected Penn World tables for OECD countries conform well to Benford's Law. But some subsets of the data – particularly GDP figures from the developing world -- show non-conformity consistent with deliberate manipulation of the underlying series. The test also flags potential problems with a variety of standard macro transformations of the data.