Designing Humanitarian Cash Transfer Programmes to Reach the Most Vulnerable Population
© European Union, 2021 (photographer: Begüm Iman), Retrieved from: https://www.flickr.com/photos/eu_echo/51118837321/in/album-72157718952446672/
Well-targeted cash transfer programmes are crucial for swiftly delivering essential assistance to those in crisis. Nonetheless, ensuring accurate targeting of support to those most in need presents recurring challenges. This challenge is particularly evident in case of humanitarian settings, as exact targeting is impeded by substantial financial constraints on designing and delivering cash transfers and related contextual complexities. Consequently, humanitarian agencies often rely on a number of targeting mechanisms, from straightforward methods like geographic or demographic targeting, to more intricate allocation systems such as self- or community targeting, or proxy means tests (PMTs). The effectiveness of these strategies varies significantly across contexts.
Acknowledging the complexities involved, it is crucial to effectively adapt these mechanisms and better target humanitarian aid, gaining comprehensive insights into the characteristics and needs of their intended recipients. This requires collaborative effort developing forward-thinking targeting scenarios for cost-efficient and equitable approaches to cash transfer.
The Development Analytics team has partnered with organizations, such as UNHCR, IFRC, and WFP, to explore how to effectively revise cash transfer strategies to include assess poverty and household welfare, and addressing the refugee crisis in Lebanon, Türkiye, and Iraq. To tackle the unique challenges in each country, the team has created and validated microsimulation models that integrate diverse targeting methods, ranging from universal targeting to categorical targeting and proxy means testing (PMT). This multifaceted approach has entailed synthesizing prior discussions on various targeting strategies in distinct country contexts and evaluating their existing targeting practices.
Our Approach
Development Analytics has introduced layered strategies to tailor targeting scenarios to diverse country contexts. This entails integrating different targeting models with varying levels of complexity and adjusting transfer amounts accordingly. By employing this layered approach to identify eligible households and combining it with various targeting models, Development Analytics has simulated cash transfer scenarios aimed at reaching a wide array of recipient groups with differing benefit levels. In crafting these scenarios, our expert team has embraced innovative approaches such as:
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Recognizing the importance of active involvement from donors and programme implementers in designing targeting strategies for humanitarian aid, Development Analytics has developed an interactive web application. This application enables donors and programme implementers to directly engage with the data, observe the effects of different targeting scenarios, and refine their decisions accordingly. This Interactive Social Policy Simulator (ISPS) is designed to empower humanitarian agencies and governments to interact with data and simulate various outcomes without relying solely on predefined scenarios crafted by technical experts.
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The Development Analytics team has not only designed and validated proxy means test (PMT) models but has also integrated them into model selection using machine learning techniques. Therefore, the team has trained machine learning models and conducted out-of-sample validation by assessing performance metrics on test data. This enables a deeper understanding and evaluation of targeting effectiveness across various country contexts.
Case Studies
Development Analytics has led several mixed methods analyses at the intersection of revising cash transfer approaches, measuring poverty and household welfare as well as the refugee crisis in Lebanon, Iraq, and Türkiye. Development Analytics has an expert team in quantitative and qualitative research techniques and a demonstrated record of projects over the last 20 years with many international multilateral and bilateral agencies. Some case studies include:
Targeting Analysis Service for the Emergency Social Safety Net (ESSN) Assistance for Refugees in Türkiye.
The ESSN programme, run by the IFRC and Turkish Red Crescent Society (TRC) and funded by the European Union, has provided regular cash assistance to more than 1.5 million refugees living in Türkiye, as the largest humanitarian programme in the history of the EU and the largest programme ever implemented by the IFRC.
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To design future-looking targeting scenarios, we proposed adaptations to the existing targeting approach, criteria, and payment structures, considering the evolving needs, vulnerabilities, and capacities of the beneficiaries. Our recommendations also factored in financial parameters and broader strategic considerations.
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Through our holistic approach, we collaborated with IFRC and TRC to enhance the effectiveness and inclusivity of the ESSN programme, ensuring that it remains responsive to the dynamic needs of refugee populations in Türkiye.
© World Bank
Annual Re-estimation of the Proxy Means Test Regression Model Used to Target Refugees for Multipurpose Cash in Lebanon.
In Lebanon, UNHCR, WFP, and collaborating partners across sectors rely on an econometric model, specifically a Proxy Means Test Regression Model, to assess the socio-economic vulnerability of the refugee population. This model predicts household expenditures, aiding in the identification of families eligible for cash and food assistance programmes.
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To ensure the accuracy and relevance of this targeting methodology, and to maintain consistency across UNHCR's multipurpose cash programme, WFP's food assistance initiatives, and programmes led by sector partners, Development Analytics has been spearheading a comprehensive approach since 2018. This approach aims to optimize the delivery of multipurpose cash and food assistance interventions, effectively addressing the fundamental needs of refugees in Lebanon.
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By annually re-estimating the Proxy Means Test Regression Model, we ensure that the targeting methodology remains current and reflective of the evolving socio-economic landscape. This ongoing effort ensures that vulnerable refugee families receive the support they require, fostering resilience and dignity within the refugee community.
© UNICEF/UNI366049/Choufany,
Review of the Targeting Approach and Re-estimation of the Proxy Means Test (PMT) Regression Model Used to Target Refugees for Multipurpose Cash Assistance Programme in Iraq.
For decades, Iraq has grappled with prolonged displacement and instability stemming from both domestic and regional conflicts. UNHCR's objective is to provide assistance to the most vulnerable households in Iraq through its Multi-Purpose Cash Assistance (MPCA) programme.
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In addressing the complex and context-specific challenges inherent in revising the targeting approach of MPCA, the Development Analytics team has formulated a comprehensive set of analytical procedures. These steps aim to bolster the efficacy of the targeting strategy, facilitating a more nuanced and adaptable approach to address the requirements of refugees in Iraq.
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Throughout the design of the simulation model, the team ensures the integration of a holistic methodology for assessing vulnerability among refugees. This approach supports a cohesive and efficient response, tailored to meet the diverse needs of the refugee population.
© EU/ECHO/Peter Biro.
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.