Authors: Valentina Barca and Rodolfo Beazley
The economic impact of the COVID-19 pandemic has led to an unprecedented use of social protection systems to support affected populations. More than 181 countries have implemented so far more than 870 social protection measures, according to the living paper by Gentilini et al. (2020).
What is interesting compared to past crisis responses is the large number of these measures that build on existing data, information systems and registration capacity – some of these enabling very swift expansions of caseloads. Among the extensive body of research on ‘Shock Responsive Social Protection’, we had published a paper in early 2019 with the Australian Government’s Department of Foreign Affairs and Trade (Barca and Beazley, 2019), reviewing the role of social assistance data and broader information systems – such as Social Registries – in identifying beneficiaries and delivering benefits in the aftermath of a large-scale shock (Chirchir and Barca, 2020). At the time, we had stressed there were hardly any examples of countries leveraging data on potential beneficiaries to expand to new caseloads in the aftermath of a shock – and for “good reasons”: existing registries often have low coverage, are out of date, do not necessarily have relevant information to support meaningful targeting, are often hard to access and pose data protection issues (among other challenges).
What has changed (and what hasn’t)? How are the ongoing social protection responses to COVID-19 providing new insights? This blog attempts to provide an answer.
The COVID-19 challenge: identifying and reaching (very) new caseloads
The adverse effects of the COVID-19 crisis are so widespread that many different segments of the population have been affected, not just the ‘usual suspects’. Not only the sheer extent of the support required has imposed a challenge to the social protection sector, but also the need for safety/ health measures, which affect the delivery of services.
This has also happened at unprecedented speed, requiring timely action. Countries have therefore been scrambling to identify and reach those who are not beneficiaries or eligible for any routine social protection programme (social insurance or social assistance). In some countries with low routine coverage, this amounts to a large majority of the population: the ‘missing middle’.
Swiftly reaching and ‘targeting’ these new caseloads is first and foremost a policy and fiscal space decision, but this is limited by the design and implementation feasibility of putting that decision into practice – a balancing act between ‘objective’ information on who has most been affected and the political and practical feasibility of that choice. How does this play out with COVID-19?
- An unprecedented percentage of countries’ populations have been affected, including ‘harder to reach’ population groups such as informal workers (e.g. home-based enterprises) and those with precarious livelihoods, especially in urban areas (most often not covered by routine programmes);
- There is therefore widespread consensus this is not the time for complex poverty-targeting mechanisms, but for a ‘no-regrets’ approach . Responses should aim to reach as many people as quickly as possible and should rely on simple and transparent mechanisms.
- Responding swiftly may therefore imply:
- relying on registries/data that were designed for other purposes (and that have substantial accuracy errors when targeting regular social assistance for the poor, for example). However, in this context, these may allow reaching a substantial proportion of the population ‘quickly’, while complementing and sequencing this strategy with others, to ensure that nobody is left behind.
- leveraging broader information systems and interoperability agreements, e.g. to enable fast authentication of new beneficiaries, and registration capacity.
- All of this doesn’t mean that such approaches are most suitable for regular and/or lesser shocks. However, what is certainly true as an early lesson is that fast responses may benefit from leveraging on what is available – at least in an initial phase.
How to identify and reach new caseloads quickly?
What is certain, is that the challenge of identifying and reaching new caseloads in response to the impact of C19 has led to many innovations in the social protection sector, including a) systematic use of existing data where this is trusted and ‘high enough’ quality (again, all the routine criteria apply – see Barca and Beazley, 2019), and; b) flexible high-tech mass registration processes.
Below we go through some of the main strategies implemented so far – noting a summary of all of these (pointing out strengths, weaknesses, prerequisites and examples) can be found on SPACE (2020).
- Leveraging social protection beneficiary registries, in creative ways
Beneficiary registries (and their Management Information Systems or Beneficiary Operations Management Systems) track data on beneficiaries and benefits to support programme management and implementation. These registries only (or mostly) contain data on programme beneficiaries, and therefore leveraging these primarily enables reaching routine beneficiaries.
The most obvious way of leveraging beneficiary data is a ‘vertical expansion’: giving more to those who already receive. Gentilini et al (2020) report this has happened within 68 programmes across 46 countries to date, in response to COVID-19.
What is more ‘interesting’ is the use of beneficiary data in ways we have rarely seen in the past (SPACE, 2020):
- Expanding to past beneficiaries (e.g. likely in Zambia)
- Expanding to people who had been put on waiting lists (e.g. Sri Lanka, Iraq)
- Expanding to those who were eligible but had previously been rejected as beneficiaries for different reasons (e.g. lack of requirements) (e.g. likely in North Macedonia)
The advantage of leveraging beneficiary registries is that, in theory, this should be a fairly ‘easy’ strategy to implement. However, in our 2019 paper Barca and Beazley, 2019), we reviewed many experiences and concluded that there are often substantial delays even in the implementation of simple top-ups, mostly because of lack of preparedness (adequate financing, protocols and process, roles and responsibilities, etc).
It is also clear that responses that only reach existing beneficiaries (and some former and pre-identified future beneficiaries) will not help to solve the coverage gap posed by COVID-19. As a consequence, many countries are complementing this type of response with others.
2. Leveraging social registries and data on ‘potential beneficiaries’
Social registries are typically used for the assessment of needs and conditions to determine potential eligibility for multiple social assistance programmes. They contain socio-economic data of all potential beneficiaries.
While leveraging social registries has always been seen as promising in terms of timeliness and cost-effectiveness of emergency responses to higher caseloads (with examples such as Kenya’s HSNP being hailed as a ‘solution’), our 2019 paper found that this type of strategy had been rarely implemented (Barca and Beazley, 2019). The main reasons were that few countries have social registries with high coverage and high-quality data (see Leite et al., 2017; Barca, 2017), together with a lack of planning and preparedness for this type of response (e.g. the HSNP is ‘prepared’ as it not only pre-registers but also pre-enrols caseloads for expansion).
However, as stressed above, the COVID-19 crisis has changed things drastically in this regard too.
The scale of the shock is so large that most, if not all, the people in the social registry are likely to be affected to some degree. For this reason (and also because the response required timely action and safeguarding social distancing - minimizing data collection processes that often rely on census sweeps or face to face approaches), many countries have decided to leverage social registry data (not worrying too much about inclusion and exclusion errors at the start).
Countries such as Brazil, Cape Verde, Colombia, Costa Rica, Dominican Republic, Ecuador, Indonesia, Mauritius, and Peru, among others, have leveraged social registry data by lifting eligibility rules partially or entirely providing support to much wider caseloads. This was often complemented by SMS notifications and/or online registration platforms to share payment preferences. A good overview can be found within the May 22 edition of the Gentilini et al paper (Gentilini et al., 2020).
However, this type of response is not an option for many countries, which lack social registries with substantial coverage. Some of these countries had to rely on other information sources. Moreover, even countries with strong social registries in place had to rely on complementary strategies to reach those who had been left out.
3. Leveraging other information sources
The scale of the COVID-19 crisis called for broadening the scope of the registries used, going beyond the social protection sector. Countries have been creative in this regard too, triggering or complementing registration with data from ID systems/civil registration and vital statistics (Singapore, Japan, Hong Kong), informal worker organizations/municipal chambers of commerce/cooperative registration mechanisms (Cape Verde), farmer registries, financial inclusion programmes (e.g. India), the energy sector (e.g. Guatemala), the health sector (e.g. Morocco), taxes (USA) and from mobile money providers.
Leveraging other registries depends on a number of conditions, including the accessibility of those registries and the quality of their data. Moreover, a unique, foundational, national ID is usually the backbone that enables this type of data exchange.
4. Rapid mass registrations
Leveraging existing data has the intrinsic limitation of reaching those who are already ‘in the system’. Therefore countries have been setting up innovative mechanisms for registering large segments of the population quickly, while also safeguarding social distancing: from online platforms (e.g. Argentina, Thailand and several others) or via helplines or USSD technology (e.g. Namibia, Peru and Pakistan), to relying on local government offices (Pakistan).
Importantly, many countries have combined these different strategies in order to give applicants the choice to decide what is best according to their circumstances. They have also supported the ‘last mile’ of registration using the local capacity of CSOs, NGOs and worker organisations – acknowledging those who face the highest barriers to access are likely to be most in need.
The characteristics of the COVID-19 crisis have helped countries take a step back from their routine ‘tunnel vision’ – while also stressing once again the importance of system preparedness: the more high quality (see key dimensions in Figure 2 below) and inclusive information systems countries had and could leverage - and the more they had thought about this in advance - the better. Many strategies adopted during COVID-19 were rarely adopted before, pushing the social protection sector to break new ground.
Source: extract from DFAT and OPM (2019)
Many lessons will emerge from this experience, which will hopefully contribute to improving social protection information systems for regular programming as well as for shock response (abiding by Data Quality and protection principles)– while also setting the foundations for a more inclusive social protection system that caters to both idiosyncratic (affecting one or few people) and covariate (affecting many) shocks (Chirchir and Barca, 2020; Barca and Beazley, 2019).
List of References
Australia - Department of Foreign Affairs and Trade, DFAT and Oxford Policy Management, OPM (2019) Thinking of using social assistance data and information systems to support targeting for shock response? Four key steps! Access here.
Barca, V. (2017). Integrating data and information management for social protection: social registries and integrated beneficiary registries. Australia - Department of Foreign Affairs and Trade, DFAT and Oxford Policy Management. Access here.
Barca V. and Beazley R. (2019) Building on Government Systems for Shock Preparedness and Response: the role of social assistance data and information systems. Australia - Department of Foreign Affairs and Trade, DFAT (2019a). Access here.
Bowen et al. (2020). Adaptive Social Protection: Building Resilience to Shocks. World Bank. Access here.
Chirchir, R. and Barca, V. (2020) Building an integrated and digital social protection information system (Technical paper). UK Department for International Development, DFID, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ) (2020). Access here.
Dercon, S. (2020). No-Regret Policies for the COVID-19 Crisis in Developing Countries. Center for Global Development. Access here.
Duflo, E. and Barnerjee, A. (2020). Coronavirus is a crisis for the developing world, but here's why it needn't be a catastrophe. The Guardian. Access here.
Gentilini, U. et al (2020). Social Protection and Jobs Responses to COVID-19: A Real-Time Review of Country Measures. Living paper version 10, 22 May 2020. Access here.
Leite, P. et al (2017). Social Registries for Social Assistance and Beyond: A Guidance Note & Assessment Tool. World Bank. Access here.
O’Brien et al. (2018). Shock-Responsive Social Protection Systems Toolkit: Appraising the use of social protection in addressing large-scale shocks. Oxford Policy Management and the UK Department for International Development, DFID. Access here.
Ravallion, M. (2020) On the virus and poor people in the world. Economics & Poverty. Access here.
SPaN (2019). Social Protection across the Humanitarian-Development Nexus: A Game Changer in Supporting People through Crisis (Summary). Access here.
Social Protection Approaches to COVID-19 - Expert Advice Helpline, SPACE (2020). SPACE Guidance Note on Rapid Expansion of Social Protection Caseloads. Access here.
UNICEF (2020). Strengthening Shock Responsive Social Protection Systems: UNICEF Programme Guidance. Access here.
 We had summarized that in an infographic listed as a reference as DFAT and OPM (2019).
Note1: We are grateful to DFAT, and in particular to Jacqui Powell, for supporting this blog post and the Barca V. and Beazley R. (2019) paper it builds on.
Note2: This blog post builds on work carried out as part of the current SPACE - Social Protection Approaches to COVID-19: Expert advice helpline, implemented by DFID and GIZ (see the SPACE (2020) document). The authors are both working with SPACE as experts, but the views expressed here are entirely their own and do not necessarily represent DFID or GIZ’s views or policies.