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Leveraging Social Policy Expertise to Address Educational Inequality

© Salahaldeen Nadir / World Bank

Education is fundamental in improving life chances, playing a pivotal role in alleviating poverty, and enhancing access to other fundamental rights. However, despite its profound potential, access to quality education remains a persistent challenge, with stark disparities across countries and demographic groups. These disparities are often linked to diminished wages, entry into unskilled labor markets, increased rates of criminality, substance abuse, and mental health challenges in early adulthood.¹ Given the profound impact of educational disparities on individuals and societies, it is important to design education systems that effectively pinpoint the underlying factors to devise targeted interventions. These inequalities typically arise from a confluence of socioeconomic factors, underscoring the need for comprehensive and proactive measures to address them effectively.

In light of its significance, it is imperative for people with diverse background to come together to address this challenge. Various disciplines possess unique expertise that can contribute to the solution. In recent times, there has been a growing interconnection between social policy and education. Social policy endeavors to mitigate the pervasive issues of poverty and inequality, which frequently underlie limited access to quality education. Relatedly, education serves as a potent tool in combating poverty and disrupting the cycles that social protection initiatives seek to address.

To enhance educational equity, the Development Analytics team fosters forward-thinking strategies and provides a holistic understanding of i) designing targeted interventions to address barriers in access to education, ii) providing anticipatory strategies for addressing school dropout, iii) analyzing education landscape and trends and iv) assessing learning outcomes and disparities. When applied to the realm of education, our unique expertise in understanding the distribıtional impact of social policies proves highly relevant.  Utilizing household surveys and administrative data with a specific focus on education enables us to extract valuable insights and inform targeted interventions.

The Development Analytics team has forged strategic partnerships with numerous organizations dedicated to assessing and addressing inequalities in educational access. Our collaborations have encompassed a diverse range of projects, collaborating with institutions such as the World Bank, UNICEF and COMCEC. These initiatives span several countries, including Jordan, Pakistan, Senegal, Türkiye, and Egypt.

Our Approach

To tackle the distinct challenges inherent to each country context, our team employs a multifaceted approach to addressing the range of inequalities in education amongst children, providing comprehensive research services tailored to the specific needs and priorities of our partners. This includes:

  • Analyzing Education Landscape and Trends: Our research delves into the education landscape, examining recent trends and developments. With a focus on access to quality education across different poverty statuses, household dynamics, and child-related characteristics, we provide insights into the efficacy of existing policies and programs. Additionally, we offer recommendations for enhancing interventions and services to address identified challenges effectively.

  • Designing Informed Targeted Interventions to Address Barriers in Accessing Education Programmes and Services: Our technical team is capable of conducting in-depth assessments to identify and analyze barriers that hinder children's access to education services. We specialize in designing evidence-based interventions, such as conditional cash transfers tailored to promote educational participation. By understanding these barriers, the team aims to provide insights into developing better-targeted interventions to enhance accessibility and effectiveness.

  • Assessing Learning Outcomes and Disparities: We assess children's learning outcomes and disparities in the learning environment, taking into account various factors such as socioeconomic status, access to resources, and external shocks like the pandemic. By identifying key risk factors for academic underachievement, we inform targeted interventions aimed at mitigating disparities and promoting equitable educational opportunities.

  • Leveraging Machine Learning for School-Dropout Prediction: Leveraging machine learning algorithms, we predict the likelihood of school dropout among students. Through detailed analysis of demographic, socioeconomic, and educational indicators, we identify characteristics associated with heightened dropout risk. This enables us to tailor intervention strategies to support vulnerable students, ultimately reducing dropout rates.


  • Through these collaborative efforts, we aim to generate actionable insights and evidence-based recommendations that can drive positive change and foster greater equity in education access especially in low and middle-income countries.

Case Studies

Development Analytics has led a number of mixed-methods analyses examining trends in children's vulnerabilities that impede their access to education. Our analytical approaches aim to identify and provide better opportunities, ultimately fostering increased access to quality education for all.

Some of our related projects to date include:

Documentation of Education Response in Türkiye during the Covid-19 Pandemic and its Effect on Children's Access to and Retention in Education. 

  • The global landscape is increasingly vulnerable to disruptive shocks, including pandemics and climate change.  For instance, due to the pandemic’s disruption of face-to-face education, millions of children worldwide are predicted to experience learning losses, leading to long-term consequences such as lifetime earnings loss at the rate of 14% of global GDP today.²

  • Addressing the serious setbacks brought on education by the pandemic as a disruptive shock, our study pursued two main objectives: (i) comprehensively understanding and documenting the policies enacted, alongside the challenges encountered by children, teachers, and schools during the prolonged closure of educational institutions in Türkiye, and (ii) assessing the COVID-19 pandemic's impact on children's educational achievements while pinpointing vulnerable demographic groups.

  • In a collaborative effort with UNICEF Türkiye, we developed analytical frameworks to delve into various facets of the crisis, including children's learning outcomes, dropout rates, engagement in child labor, as well as conducting simulations and estimations utilizing household-level datasets. Our analysis highlights the severity of the problem and identifies specific characteristics of children most susceptible to adverse effects, thereby aiding in targeted intervention strategies. The results of this study were published in the Journal of Vulnerable Children and Youth Studies.


© UNICEF/UN0509112/Karacan

School dropout prediction and feature importance exploration in Malawi using household panel data: machine learning approach

  • Predictive modelling for school dropouts through machine learning (ML) models has the potential to offer rich insight into educational access trends in Malawi, where the initial net enrolment rate in primary school is high at 88.8%, but the net enrolment rate in secondary school drops to 16.4% in 2019 in the country.³

  • Utilizing ML algorithms for school dropout prediction poses significant challenges, particularly in low-income countries where financial and technical constraints hinder data collection and management. To address this, the study advocates leveraging existing household panel data to forecast school dropout probabilities.

  • The study proposes a method for utilizing pre-existing household datasets, emphasizing the incorporation of sample weights in data-scarce contexts. Additionally, it underscores the importance of children's characteristics in predicting dropout likelihood, aiming to support interventions addressing the social and economic challenges faced by primary-school students in Malawi. Conducted as part of a research thesis at Tilburg University, the study was published in the Journal of Computational Social Science. 

UNICEF Malawi.jpg

© UNICEF Malawi/2024/HD Plus

If you would like to get in touch with us and discuss the details of carrying out such a study in your country, please click to arrange a meeting with our expert team.

¹ Backman, O. (2017). High School Dropout, Resource Attainment, and Criminal Convictions. Journal of Research in Crime and Delinquency, 54(5), 715-749.
Bjerk, D. (2011). Re-examining the impact of dropping out on criminal and labor outcomes in early adulthood. (No. 5995). Bonn: IZA – Institute of Labor Economics
Dragone, D., Migali, G., & Zucchelli, E. (2021). High School Dropout and the Intergenerational Transmission of Crime. (No. 14129). Bonn: IZA Institute of Labour Economics
Campolieti, M., Fang, T., & Gunderson, M. (2010). Labour Market Outcomes and Skill Acquisition of High-School Dropouts. Journal of Labour Research, 31, 39–52.
² UNESCO Institute for Statistics. (2021). Pandemic‐related disruptions to schooling and impacts on learning proficiency indicators: A focus on early grades. Montreal: UNESCO-UIS.
The World Bank, UNESCO and UNICEF (2021). The State of the Global Education Crisis: A Path to Recovery. Washington D.C., Paris, New York: The World Bank, UNESCO, and UNICEF.
³ Malawi National Statistical Office. (2020). The third integrated household panel survey 2019 report.  Zomba, Malawi: Malawi National Statistical Office.

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