- Remediation: approximately 60 percent of the school loss will be fully remediated.

- Mitigation: approximately 40 percent of the school loss while schools are closed will be fully mitigated in High-income countries, but for the developing world, 30 percent.

## `o` Intermediate

- Remediation: approximately 30 percentage of the 70 percent school loss will be fully remediated.

- Mitigation: approximately 20 percent of the school loss while schools are closed will be fully mitigated in High-income countries, but in the developing world, 15 percent.

- Pessimistic

- Remediation: no remediation.

- Mitigation: approximately 10 percent of the school loss while schools are closed will be fully mitigated in High-income countries, but in the developing world, 7 percent.

# Data: Coverage, description, and indicators

The simulations use the same underlying data used to construct the original learning poverty measures, covering 80 percent of children in low- and middle-income countries.<sup>43</sup> These countries had at least one learning assessment at the end of primary, carried out in the past eight years, that is of sufficient quality<sup>44</sup> to be used for SDG monitoring (table 6).<sup>45</sup> The 80 percent population coverage for the global baseline value of learning poverty is much higher than the population coverage for the global monetary poverty indicator when it was first launched in the 1990s, with data going back to 1981.<sup>46</sup> The main exceptions are the nine countries for which NLA data were used. Only three could be included in the simulations—India, Pakistan and Bangladesh. The NLAs not used are for Afghanistan, Cambodia, China, Ethiopia, the Kyrgyz Republic, Malaysia, Sri Lanka, Uganda, and Vietnam. And three PASEC countries in Africa for which microdata have not yet been made available—the Democratic Republic of Congo, Madagascar, and Mali—were not included in the simulations. The main reason for not including NLAs in these simulations is the unavailability of public use microdata files or even grouped data required to run the simulation models.

The simulation results were rescaled to match our baseline values, given the countries listed above.<sup>47</sup> On average, our simulation baseline result was 1.4 percentage points higher, with the reported baseline of

> 43 World Bank 2019.

> 44 Quality is assessed in this context in terms of design, implementation, comparability, frequency, timeliness, documentation, and data access.

> 45 The number of countries with adequate learning assessments for the learning poverty indicator is considerably lower than this population-weighted figure.

> 46 This level of data scarcity is not unprecedented.  In 1981, when global monetary poverty was first reported at a global scale, only 55 percent of the global population was covered by household surveys, with several regions not even reaching the 40 percent reporting benchmark. For most of the 2000s, thanks to the impetus generated by the Millennium Development Goals process, this number has increased, remaining close to 90 percent. For more information see <u>http://iresearch.worldbank.org/PovcalNet/home.aspx.</u>

> 47 World Bank 2019.

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