The lost secret of aid efficiency

By Simon Scott, Counsellor, OECD Statistics Directorate

Wilson Schmidt
Wilson Schmidt (1927-81). Photo courtesy of Lisa Hill Corley and George Mason University

In 1963 John Pincus of the RAND Corporation suggested redefining aid to reduce all forms of aid to their value as grant or subsidy, and in 2014 the OECD’s Development Assistance Committee (DAC) agreed to his suggestion. (See an earlier post about this evolution.)

Of course, in the meantime, DAC members had not just been sitting around for 51 years. In 1969 they used Pincus’ “grant equivalent” method in a Recommendation to soften the terms of aid, and in 1972 they used it again to decide which loans were soft enough to count as official development assistance. The World Bank and the IMF also used the method in measures to keep the lid on developing countries’ debt, and the Paris Club used it to equalise creditors’ efforts under different debt relief options.

Yet one potential use of grant equivalents has been thoroughly neglected. Ironically it was the very application of the method that was most discussed 50 years ago, namely its potential to ensure the most efficient use of aid funds.

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Improving sustainable development data is a task for all

by Martine Durand, OECD Chief Statistician and Director of the OECD Statistics Directorate


This article is featured in the Development Co-operation Report 2017: Data for Development to be released on 17 October 2017. Read the report and find out more about data for development.


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In an era of fake news and alternative facts, statisticians have a special responsibility. As the custodians of the evidence base for policy making, they must stand up for the right of all citizens to true, reliable and accessible information.

This is especially the case in the development field, and even more so since world leaders adopted the extraordinarily ambitious and wide-ranging 2030 Agenda for Sustainable Development in September 2015. At the heart of this global “plan of action for people, planet and prosperity” are 17 Sustainable Development Goals (SDGs) that “are integrated and indivisible and balance the three dimensions of sustainable development: the economic, social and environmental”, with the ultimate objective to leave no one behind. Achieving the SDGs will require informed choices about priorities and strategies, and for this we will need a better evidence base than we have today.

But statisticians – and especially statisticians in developing countries – cannot do this job alone.

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On Deaton and development: consumption, poverty and well-being

By Marcelo Neri, Director of FGV Social, Professor at EPGE-Fundação Getulio Vargas, Former Brazilian Minister of Strategic Affairs, Executive Secretary of the CDES Council for Economic and  Social Development and President of Ipea Institute for Applied Economic Research

The Royal Sweden Academy of Sciences titled Angus Deaton’s Nobel prize “Consumption, Poverty and Welfare.” The evaluation commission organised Deaton’s scientific contributions during the last 40 years under three headings: i) demand models for groups of consumption expenditures, such as food, housing, etc., that already had earned  his mentor, Sir Richard Stone (1913-1991), a Nobel in 1984; ii) the study of the choice between consumption and saving, which was the object of the prizes awarded to Franco Modigliani (1918-2003) in 1985 and Milton Friedman (1912-2006) in 1976; and iii) studies about “poverty” and “welfare” that already had conferred Amartya Sen with a Nobel in 1998. I would include a fourth element of Deaton’s work, not cited by the commission, on “subjective indicators and well-being” for which Daniel Kahneman earned a Nobel in 2002.

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