Key findings:
Targeted social protection interventions can play a valuable role in supporting the achievement and realization of universal social protection. Both targeted and universal programs support broader social policy.
Targeting is an effective tool used in social protection to make the most of limited fiscal space. For a given budget, prioritizing poorer households can generate more progress in poverty and inequality reduction, income smoothing, and other aspects of welfare such as human capital .
There is no single targeting method that fits all situations. Context and policy goals will drive the choice. The decision to use methods such as self-targeting, geographic targeting, demographic targeting, and family welfare-based targeting methods should be based on your circumstances and capabilities.
Regardless of the targeting method, a robust social protection delivery system can help:
- reducing transaction costs and beneficiary bias;
- Minimize inclusion errors,
- promote crisis response;
- Improve access to social assistance, especially for the poorest and most vulnerable people, including indigenous peoples, migrants and people living with disabilities.
Advances in technologies such as ICT, big data, artificial intelligence, and machine learning promise to significantly improve targeting accuracy, but they are not a panacea. Better data may be more important than more sophisticated data usage.
As new data, technology and other innovations emerge, the way social protection targets are set is also changing.