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Reviewing the World Bank’s Analytical Country Classification: An Update

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On July 1, we updated the analytical country classification, which groups economies of the world into four categories based on 2012 GNI per capita estimates: low income, lower-middle income, upper-middle income, and high income. This has prompted some questions related to the review of this classification scheme, which we announced late last year and for which we solicited and received your feedback. I thought it would be useful to post an update.

First let me reiterate an important point that I made in my original post, and appears to have been misunderstood by some readers: the focus of this review is the analytical country classification, which is provided purely for the purposes of analysis. Possible uses include the calculation of aggregate indicator values for each of the four groups, or tracking the change in the classification of specific countries over time. Please note that this classification system is not used by the World Bank for resource allocation purposes.

Our work on the analytical classification so far has gathered perspectives of various users inside and outside the Bank, and has identified three main areas of priority focus that we will examine further. These are:

  • Relative vs absolute groupings. Some users prefer a system which maintains constant, “absolute” thresholds over time, while others would prefer a relative method of classification. Methods for creating relative groupings range from simple country rankings to statistical techniques such as cluster analysis.
  • Use of other variables instead of – or as well as – GNI per capita. Some users have expressed interest in a classification based on various measures of welfare, poverty, or economic and social progress, while others find the current measure fit for their purpose.
  • Adjusting the current methodology to take account of changing circumstances, including the availability of improved data. Options include a change to the method used to convert GNI per capita to a common currency, particularly to consider the use of the new purchasing power parity estimates that will be released by the International Comparison Program in December 2013; methods to reduce the sensitivity of the classification to revisions of estimates of GDP or population size, and to exchange rate movements, especially for countries that are close to each threshold value; and improvements in the method used to maintain the threshold values constant in real terms.

Going forward, we intend to examine each of these issues more closely, including conducting empirical work to examine the impact of any change. It is clear from our initial work that the analytical classification is very important to many more users than we originally knew, so we will proceed deliberately and carefully, and will aim to post findings of the work as it progresses. Users should be aware that the review will take some time, especially since we will need to fully evaluate the results of the 2011 ICP following the expected release of new benchmark purchasing power parities in December 2013. Consultations with users remain central to us as we move ahead, thus I would welcome your feedback on the priority areas identified so far, and any other comments on whether the analytical classification is fit for your purpose; while we have tried to identify as many users as possible in our initial review, we do not know all the uses to which the classification is put. I encourage you to post your comments on this blog, or write to either myself ( or the project manager for this review, William Prince (


Shaida Badiee

Co-Founder and Managing Director, Open Data Watch

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