In this paper, the world distribution of personal incomes (WDPI) is estimated using a global sample comprising country sample clones. A clone is a random sample that reproduces – with predetermined high probability and precision – an unknown survey sample using information that is 'encoded' in the estimated parameters of a country's personal income distribution. The clone creation method is based on the sequential probability ratio test. The clones discussed in this paper are generated from the lognormal distribution using information encoded in countries' Gini indices, and are scaled to both per capita GDP and per capita household final consumption expenditures (HFCE). Statistical analysis of a global sample from the WDPI in the 1990-2010 period shows the following. The WDPI exhibited a twin-peaks shape in the initial years, but such bimodality disappeared in subsequent years. Inequality and poverty decreased in accordance with a three-phase pattern over the period. Whether clones are scaled to GDP or HFCE matters when evaluating inequality and poverty levels, but not when determining the general direction of their trends.
global income distribution global inequality global poverty estimation sequential analysis