New UN modelling estimates lead to increase in school-age population: What are the implications for education indicators?

Calculating population-based indicators for monitoring progress towards education goals depends on having reliable and high-quality population data for the number of students at each age-group and education level. The UNESCO Institute for Statistics (UIS) uses two sources of population data: administrative data from countries based on observed head count and estimates based on statistical modelling by the United Nations Department of Economic and Social Affairs (UNDESA) Population Division (UNPD) based on different parameters. The challenge is combining these two, sometimes disparate, sources of population data into indicators and not distort countries’ realities because of artefacts that may result from statistical modelling.

In this blog, we will explore the size of the changes in population estimates and the potential implications for indicator values, while ensuring that the data for the UIS core indicators system, including Sustainable Development Goals’ population-based indicators under its custodianship* remain accurate and reliable.


Recent revisions to the UNPD global population estimates in the World Population Prospects (WPP) 2022 have made this issue even more urgent. Figure 1 illustrates the new projections by age group. The most important change is the increase in the global school-age population (SAP) by almost 20 million primary-aged children between WPP 2019 and WPP 2022. According to the UNPD, the SAP also increased for other levels of education, but to a lesser extent: 6.5 million more in pre-primary, almost 5 million more students in both lower and upper secondary, and 3.6 million additional students in tertiary education.

Figure 1 New projections of world population by age group 

Source: UNPD, World Population Prospects 2022 Table 1 shows the increase in the SAP since the previous revision (WPP 2019), along with the absolute and relative differences. The methodological changes to UNPD statistical modelling are explained in detail the World Population Prospects 2022.
Revisions to the UNPD statistical methodology include change to the reference date, the framework of age groupings, age range, and assumptions about migration and population exposures. While the change in the reference date for the population estimates from 1 July to 1 January is a possible explanation for the increase in the SAP, it is far more likely that the increase is due to changes in the population estimation methodology itself. This becomes clear when comparing both WPP 2019 with WPP 2022 for a 1 July reference date see the last column of Table 1. The comparison results in a relative increase for primary-aged SAP of 2.7%, a very similar magnitude and just slightly lower than the 2.9% obtained when comparing WPP 2019 and WPP 2022 with a refence date of 1 January. The same observation with UNPD data is also noticed at the country level.

Impact on UIS population-based indicators

Given the large change in the UNPD modelling estimates and their impact on population-based indicators, the UIS is working towards finding a solution to ensure that data remain accurate and reliable. While we welcome the upgrades to the UNPD methodology intended to improve technical standards and increase inclusivity and transparency, it is important to note that the observed data from countries did not show considerable fluctuations in school enrolment over the last two years.

Why is this important? The variation in the UNPD estimates and country administrative data implies different results for indicators whose denominator uses UNPD estimates, for example enrolment rates, and rates and number out-of-school children. One immediate question is how to manage the change (increase or decrease) in the denominator (UNPD) for a given country and year given that the numerator (for the same country and year), based on observed data, has not changed?

To be clear, let’s take the example of Country A reflected in Table 2. Country A in 2020 had 100 students in the official age-group corresponding to a given level of education (the observed headcount reported to the UIS based on the national EMIS database) and according to the WPP 2019 estimates, the SAP corresponding to that level of education used as a denominator was 110. Now, according to the revised WPP 2022, the new estimate produced for the same year and country has 125 children for the same age group. Using one or the other denominator has a clear impact on enrolment rates and also on total numbers of children out of school for the given level of education.

This simple example using a hypothetical Country A summarizes the challenge the UIS faces, as the new UNPD estimates have additional implications to the operational ones related to substituting one set of estimates with a new one. More concretely: Are those new 15 students enrolled in school or not? Should they be prorated?

These questions are relevant for producing coherent and consistent education indicators. Prior to our September Global Education Data Release, the UIS had already begun the process of exploring the use of national data in the population-based indicators – based on country preferences and UIS verification that national data corresponds to established standards for quality and reliability.

To facilitate countries’ requests, the UIS has prepared a proposal including guidance and table format for countries to submit the necessary population data and metadata. Countries’ data must comply with the proposed standard criteria for accepting national population data, if it does not, the UIS would continue to use UNPD population estimates.

For now, the UNPD remains the standard source of population data at the UIS as described in the Background Information on Statistics in the UIS Database. Going forward, however, UIS data releases may incorporate more national administrative data. The most important result is that the population-based education indicators reflect countries’ realities so that the data are a helpful tool for national education planning and goal setting.

UIS Resources Background

* In addition to being used to calculate SDG 4 population-based indicators, population data are required for the calculation of SDG indicator 9.5.2 (researcher, in full-time equivalent, per million inhabitants), SDG indicators 11.4.1 (total per capita expenditure on the preservation, protection and conservation of all cultural and natural heritage), as well as a range of Other Policy Relevant Indicators related to culture and education, including research & development.

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