The dollar-a-day method, applied in monitoring the UN's development goals against poverty, provides no confidence interval for the official figures of global poverty reduction, a practice that does not allow statistical testing. Using Monte Carlo simulations we construct confidence intervals that reflect, to a large extent, the data and methodological uncertainties involved, particularly the error introduced by the process of determining the International Poverty Line.
These estimates identify a reduction of less than 5% between 1990 and 2015 at 95% confidence level, in stark contrast with the remarkable 73% reduction of global poverty reported in the World Bank official statistics published on September 18, 2018. At the same time, MDG1 obtains with a 77% confidence level. The cost-of-basic-needs method paints a more promising picture identifying a 34.4% reduction at 95% confidence level, while the confidence level at which poverty in 2015 was half of 1990 stands at 46%.