Equivalent Years of Schooling: A Metric to Communicate Learning Gains in Concrete Terms

52 Pages Posted: 20 Feb 2019 Last revised: 21 Feb 2019

Date Written: February 19, 2019


In the past decade, hundreds of impact evaluation studies have measured the learning outcomes of education interventions in developing countries. The impact magnitudes are often reported in terms of "standard deviations," making them difficult to communicate to policy makers beyond education specialists. This paper proposes two approaches to demonstrate the effectiveness of learning interventions, one in "equivalent years of schooling" and another in the net present value of potential increased lifetime earnings. The results show that in a sample of low- and middle-income countries, one standard deviation gain in literacy skill is associated with between 4.7 and 6.8 additional years of schooling, depending on the estimation method. In other words, over the course of a business-as-usual school year, students learn between 0.15 and 0.21 standard deviation of literacy ability. Using that metric to translate the impact of interventions, a median structured pedagogy intervention increases learning by the equivalent of between 0.6 and 0.9 year of business-as-usual schooling. The results further show that even modest gains in standard deviations of learning -- if sustained over time -- may have sizeable impacts on individual earnings and poverty reduction, and that conversion into a non-education metric should help policy makers and non-specialists better understand the potential benefits of increased learning.

Keywords: Educational Sciences, Educational Institutions & Facilities, Inequality, Rural Labor Markets, Labor Markets

Suggested Citation

Evans, David and Yuan, Fei, Equivalent Years of Schooling: A Metric to Communicate Learning Gains in Concrete Terms (February 19, 2019). World Bank Policy Research Working Paper No. 8752, Available at SSRN: https://ssrn.com/abstract=3338189

David Evans (Contact Author)

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Fei Yuan

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

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