include the UNICEF WCARO tool,<sup>4</sup> CARICOM costing model,<sup>5</sup> Estimator Cost Analysis Tool,<sup>6</sup> Brookings Childhood Cost Calculator,<sup>7</sup> ILO Care Policy Investment Simulator,<sup>8</sup> and UNESCO’s SDG 4.2 costing model.<sup>9</sup> For the case of Pakistan, UNICEF’s ECE Accelerator Costing and Simulation Model was preferred over other available models because it is open source, easy to adapt, and allows the planners and decision-makers to use the model iteratively.

The ECE accelerator simulation model was developed in 2021. Governments have been using the tool for ECE sub-sector planning. For example, Lesotho used the results of the simulation exercise to undertake focused advocacy with the government and public representatives to increase funding for ECE. The resulting analysis suggested that universal expansion would not be feasible given available resources. The government instead opted to support the expansion of one year of ECE. The costing exercise also resulted in leveraging additional funding from development partners for ECE.

# **Data and Methods**

## The approach

This paper analyzes data from the Pakistan Bureau of Statistics (2017 Census)<sup>10</sup> and the provincial Education Management Information Systems<sup>11</sup> on the population size, enrollment rates, and achievement rates (dropout and retention rates) in ECE. Data on existing infrastructure, human resources, ECE and education financing, and unit rates for key inputs such as teachers and basic ECE supplies were also collected from each provincial government. These inputs were categorized under 3 heads: salary, non-salary (such as payment of electricity bills), and development (such as construction of classrooms). Policy options and targets for ECE were then defined based on best practices and in line with national and provincial policies and implied service standards. Enrollment estimates from the PSLM were updated. Using data on population growth and enrollment in public and private ECE we use an estimated enrollment rate of 31% for all scenarios in this paper. Enrollment rates were then projected for 2023-2035 using the population projections contained in the most recent published census files.<sup>12</sup> Infrastructure and human resource

> 4https://www.ece-accelerator.org/resources/unicef-west-and-central-africas-regional-prototype-supporting-costeffective-policy-development-early-childhood-development

> 5 https://www.humanitarianlibrary.org/sites/default/files/2014/02/ECD-CoNo30-rev.pdf

> 6 https://www.costtoolkit.org/

> 7 https://www.brookings.edu/articles/the-childhood-cost-calculator-c3/

> 8 https://www.ilo.org/globalcare/?language=en#simulator 9https://bangkok.unesco.org/sites/default/files/assets/article/Early%20Childhood%20Care%20and%20Education/file <u>s/Costing%20and%20Financing%20SDG%204.2%20Webinar/2.1_Kristy%20Bang.pdf</u>

10 https://www.pbs.gov.pk/content/final-results-census-2017 11 <u>http://www.emis.gob.pk/; https://semis.rsu-sindh.gov.pk/; https://open.punjab.gov.pk/schools/; https://ese.kp.gov.pk/page/education_management_information_system_emis; http://hrmis.fde.gov.pk/;</u> 12 The rates used for each province are available online at https://www.pbs.gov.pk/content/final-results-census-2017- <u>0, Table 1. These are 2.4 for Pakistan overall, 2.13 percent for Punjab, 2.89 percent for KP, 2.41 for Sindh, and 3.37</u> for Balochistan. While newer population growth rates are available from the 2023 census, age-wise population estimates are not yet published. Hence these newer growth rates were not used.

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