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A Review of the analytical income classification

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This post originally appeared on Let's Talk Development.

The World Bank’s classification of economies as low-, lower-middle-, upper-middle-, or high-income has a long history. Over the years these groupings have provided a useful way of summarizing trends across a wide array of development indicators. Although the income classification is sometimes confused with the World Bank’s operational guidelines, which set lending terms and are determined only in part by average income, the classification is provided purely for analytical convenience and has no official status.

The classification is based on gross national income per capita, calculated annually in U.S. dollars using a three-year average exchange rate, the so-called Atlas methodology. Because the thresholds are frozen in real terms while real incomes have risen, the number of countries in the low- and lower-middle-income groupings have decreased and poverty rates have declined, even as hundreds of millions of people remain in absolute poverty. This is hardly news. When China crossed the threshold from low- to middle-income twelve years ago, a quarter of the world’s poorest people moved with it. And after India crossed the same threshold nine years later, a majority of the people living on less than $1.25 a day lived in middle-income economies. In another decade it is likely that no country will remain below the current low-income threshold, even though absolute poverty, whether measured by dollars or life expectancy or education levels, will certainly persist. As Martin’s note suggests, this calls into question the usefulness of the current classification scheme.
For this reason the Data Group at the World Bank is reviewing income classification system. To inform this review, we welcome inputs from all users and colleagues in the research and development community. We would appreciate any comments or suggestions on the following questions:

  1. Does a classification of economies by development status have some usefulness in analysis and research? 
  2. Should the classification be based on average income or some other indicator or combination of indicators? Should income be measured by exchange rates or purchasing power parities (PPP). Should we go “beyond GDP,” and, if so, how should such a measure be constructed?
  3. Should  poverty rates be used as a classification criterion? Does Martin’s analysis of “capacity for redistribution” have any application?
  4. How should the categorical thresholds be set? Are there “natural” dividing lines between categories measured along a GNI per capita scale or by some other indicator?
  5. How and how frequently should the classification be updated? Should the thresholds be updated or only the rankings of countries?

Please send your inputs to


Shaida Badiee

Co-Founder and Managing Director, Open Data Watch

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