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Since the onset of the COVID-19 pandemic and resulting global recession, researchers have documented the economic impacts of the crisis, including in the form of individuals’ lost employment and income and increased poverty and food insecurity within households. To respond to these impacts, about 200 countries and territories – many with the support of the World Bank – have implemented new or adapted social protection programs in response to COVID-19, most frequently non-contributory cash transfers, followed by social insurance and labor market interventions.
Digital social protection payments, as well as other forms of social protection, have the potential to contribute to women’s economic empowerment through several pathways, including by improving economic security, reducing intra-household conflict and related stress, and increasing women’s decision-making power and agency. Existing evidence on cash transfer programs suggests that such programs insulate women and their families from poverty and food insecurity, expand their income-generating opportunities by allowing them to invest in their farms and businesses or transition to paid employment, and can reduce the risk of intimate partner violence. Harnessing digital platforms, in particular, may have the added benefit of increasing women’s privacy and autonomy over how payments are spent, saved, or invested, as well as provide a convenient, safe option for delivery in contexts where women’s mobility, security, and/or free time are limited.
That said, where not carefully designed, digital payments may exacerbate pre-existing economic and social inequalities. For example, if cash transfers are delivered through mobile phones, those lacking access to a phone – a population of disproportionately women in many contexts – are likely to be excluded from equal access. New and efficient delivery mechanisms for social protection payments, while capable of increasing the overall number of recipients of a given program, may nevertheless run the risk of leaving behind the most vulnerable. Thus, the particular identities of those able to access and benefit from digital social protection payments should be considered alongside how many people in total receive payments.
Figure 1. G2P theory of change
It is important to design and implement digital social protection programs with both the aforementioned benefits and risks in mind, taking full account of how digital cash transfer schemes can either promote women’s economic empowerment or hinder it. To that end, the G2Px Initiative has the opportunity to institute a core set of indicators to (1) support the development of inclusive social protection programs and (2) measure progress across its investments. Data collected using these indicators could inform the design and implementation of government-to-person programs, as well as shed light on the extent to which digital social protection programs implemented in the COVID-19 context are inclusive in their reach and benefits, including from a gender perspective.
Researchers at the Center for Global Development and Data2X have recently co-authored Measuring Women’s Economic Empowerment: A Compendium of Selected Tools, which maps existing tools focused on measuring various dimensions of women’s economic empowerment, whether in monitoring country-level populations or in evaluating the impact of particular programs and interventions. A core set of indicators for informing G2Px program design/implementation and monitoring program results could draw upon the compendium’s collection of indicators, identifying those that are most relevant to digital social protection programs’ intended objectives.
We propose a set of indicators that are relevant to the various stages that a social protection recipient experiences and how program designers and implementers can both effectively shape and evaluate digital social protection schemes across a delivery chain. Population monitoring indicators are those that offer information on country contexts to inform G2P program design and implementation. Monitoring and evaluation (M&E) indicators are those that could be adopted to monitor a program’s reach and impact. In cases where the M&E tools we reviewed lack indicators designed to capture particular aspects of the delivery chain (e.g., whether an individual’s food insecurity decreases after the receipt of digital social protection payments), we propose adapting population monitoring indicators to allow for the collection of that data at project-level.
Source: Lindert, Kathy; Karippacheril, Tina George; Rodriguez Caillava, Inés; Nishikawa Chavez, Kenichi. 2020. Sourcebook on the Foundations of Social Protection Delivery Systems. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/34044 License: CC BY 3.0 IGO.
The indicators we propose would rely on a range of underlying data sources. Wherever possible, we have included indicators whose underlying data should be available through governments’ administrative databases – their routine monitoring systems of social protection programs. We also make recommendations for indicators that would rely on routine M&E data, as well as household survey data, ideally collected as part of rigorous evaluation efforts.
Across this delivery chain, it is important to recognize the high risks of exclusion of eligible recipients, either because they are unaware of the existence of a program for which they are eligible, unable to access its registration system or the payments themselves, or unable to use the funds received autonomously. This exclusion is especially likely if governments lack pre-existing data systems reflecting the identities and needs of their populations. As such, we have sought to include indicators that allow for G2P program implementers to gauge the extent to which exclusion is occurring and which stages of the delivery chain are most vulnerable to drop off, to inform future decision-making regarding how to mitigate this risk.
Assess
Stage 1: Outreach & Stage 2: Intake and registration
Program designers and implementers must ensure that potential recipients are aware of digital social protection schemes and how to access them, recognizing that women may face gender-specific barriers to accessing this information. Outreach, intake, and registration efforts must therefore include channels that “meet women where they are,” such as through harnessing women’s self-help and savings groups. Where outreach, intake, and registration are conducted through digital channels, or even in person through community platforms, social protection program designers and implementers must account for gender gaps in literacy, access to technology, and freedom of mobility.
Proposed measures:
- Tools for Access to Information/Networks
- Literacy
- Mobility
Stage 3: Assessment of needs and conditions
Social protection program designers and implementers should consider recipients’ need for income support, drawing upon data reflecting individual/household insecurity and poverty levels, and whether they currently receive social protection support, which at the individual level may differ by gender and other relevant social dimensions. Social protection program designers and implementers should also account for gender differences in surrounding conditions – including gender gaps in ID, mobile phone ownership, bank/mobile money account ownership, mobility, and financial and digital literacy.
Proposed measures:
Assessment of Needs
- Poverty
- Food Insecurity
- Shelter Insecurity
- Current Social Protection Benefits
Assessment of Conditions
- Possession of Legal ID
- Tools for Access to Information/Networks
- Literacy
- Mobility
- Access to (Digital) Financial Services
Enroll
Stages 4-6: Eligibility and enrollment decisions, determination of benefits, notification, and onboarding
In these stages, program designers and implementers should reflect on the requirements imposed on potential social protection recipients to determine their eligibility, enrollment, and onboarding into digital social protection programs – and how pre-existing gender gaps in access to ID, digital technology, financial services, literacy, and mobility may result in gender-differential access.
Proposed measures:
- Possession of Legal ID
- Tools for Access to Information/Networks
- Literacy
- Mobility
- Access to (Digital) Financial Services
Provide
Stage 7: Provision of benefits
Until this stage of delivery chain, the significant majority of proposed indicators have been those aimed at population monitoring, intended to inform the design and implementation of a digital social protection program to reduce the risk of women’s exclusion. At this stage, we propose a condensed set of M&E indicators that, if applied across digital cash transfer schemes, would allow the team to track progress of programs over time at the level of the individual.
Proposed measures:
- Payments Distributed, Disaggregated by Sex and Other Relevant Social Dimensions
- Payments Withdrawn, Disaggregated by Sex and Other Relevant Social Dimensions
Manage
Stage 8: Beneficiaries compliance, updating, and grievances
The proposed indicators draw upon existing data sources, designed to reflect national governments’ capacity to deliver G2P payments. The former – the JAM index compiled for the CGD report Citizens and States: How Can Digital ID and Payments Improve State Capacity and Effectiveness? – reflects the “readiness” of a country to make inclusive digital social protection payments by assessing financial account coverage, ID possession, and mobile phone ownership in the country. The latter, a country vulnerability gender data dashboard created by Data2X and Open Data Watch, reflects the capacity for governments to respond to COVID-19, including through the provision of social protection support to vulnerable citizens. This tool provides sex-disaggregated data when available, allowing for a closer look at where countries may or may not be well prepared to ensure women’s equal inclusion in digital social protection programs reach and benefits.
The G2Px team could rely on these indicators as a means of reflecting overall system strength/capacity – and complement them with those that at a more granular level capture systems’ capacity to handle grievances and other more specific aspects of digital cash transfer schemes.
Proposed measures:
- Data/distribution systems in place to provide digital social protection payments to eligible recipients
- Systems able to reach and benefit women in the COVID context
Stage 9: Exit decisions, notifications, and case outcomes
The measures proposed below would allow social protection program implementers to gather data on case outcomes, including the extent to which digital cash transfers and any surround support have enabled reductions in poverty and other vulnerabilities and/or facilitated other aspects of economic empowerment (e.g., savings, work, agency). Tracking these outcomes is particularly important because existing evidence suggests that even if women are able to access digital social protection payments, intrahousehold and community norms may restrict their ability to save, spend, or invest the payment autonomously. Program designers and implementers should consider these restrictions on women’s agency to strengthen their delivery systems over time, incorporate design aspects that mitigate unintended consequences/risks, and track the impact of digital social protection programs on recipients’ ability to save, employment, financial security, and subjective well-being.
Proposed measures:
- Poverty
- Food Insecurity
- Shelter Insecurity
- Savings
- Work/Employment
- Agency and Well-Being
A Core Set of WEE Indicators to Inform Government-to-Person Payment Programs
Designed to Measure |
Indicator |
Indicator/Data Source |
Level of Measurement |
Type of indicator |
Number of Countries |
---|---|---|---|---|---|
Access to Information |
Percentage of women ages 25 and older who report having a mobile phone that they use to make and receive personal calls |
Gallup |
Individual, women only (Can be compared to same figure for men) |
Population monitoring |
140 |
Access to Networks |
Women’s participation in community groups/ associations/networks |
Individual Deprivation Measure; Sanyal 2009; Kuhlmann et al. 2017; Dutt & Grabe 2017; Ethiopia Farmer Innovation Fund Impact Evaluation (2012), Malapit and others (2019), Glennerster and others (2018) |
Individual |
Population monitoring/M&E |
50+ (pro-WEAI) |
Literacy |
Literacy rate among adult women (aged 15+ years) |
UNESCO Institute for Statistics Database |
Individual, women only (Can be compared to male literacy rate) |
Population monitoring |
217 economies |
Mobility |
Gender inequality in the freedom to move outside the home (categorical) |
Multidimensional Gender Inequality Index |
National |
Population monitoring |
109 |
Mobility |
Can a woman legally travel outside her home in the same way as a man? (Y/N) |
Women, Business and the Law |
National |
Population monitoring |
190 economies |
Mobility |
Workload/work balance |
Alkire and others (2013), Malapit and others (2019) |
Individual, sex disaggregated |
Population monitoring |
50+ |
Poverty |
Household asset index |
Individual Deprivation Measure |
Household |
Population monitoring/ |
5 (PM) |
Food Insecurity |
Proportion of women who report having had enough money [income] to buy food that they or their family needed in the past 12 months |
SDG Gender Index (Gallup) |
Individual, only women (Can also be compared to same figure for men) |
Population monitoring |
129 |
Shelter Insecurity |
Proportion of women who report having had enough money [income] to provide adequate shelter or housing in the past 12 months |
SGD Gender Index (Gallup) |
Individual, only women (Can also be compared to same figure for men) |
Population monitoring |
129 |
Social Protection Benefits |
Proportion of population covered by social protection floors/systems Perhaps using ASPIRE data (if sex disaggregated), this indicator could be subdivided to interrogate whether women receive specific forms of social protection: |
Government administrative databases/ILO Even without sex disaggregated ASPIRE data, select government databases (e.g., BISP in Pakistan) can reflect the extent to which women v. men are targeted with payments. |
Individual, sex disaggregated |
Population monitoring |
186 |
Savings |
Saved at a financial institution, female (% age 15+) |
World Bank Findex |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring/M&E |
140 |
Savings |
Has individual formal savings and/or safe and private savings |
World Bank Findex |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring/M&E |
140 |
Work/Employment |
Share of employment in non-agriculture, female (% of total nonagricultural employment) |
UNDP Human Development Data |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring |
191 |
Work/Employment |
Average monthly hours worked for pay by woman |
Bandiera (2014) |
Individual, women only (Can be compared to same figure for men/boys) |
M&E |
- |
Work/Employment |
Female unemployment rate (% of female labor force, modeled ILO estimate) |
World Development Indicators |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring |
217 economies |
Work/Employment |
Proportion of young women who are idle (women 15-24 who are not employed and not in school and not looking for work) |
LFS or LSMS |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring |
184 (LFS) 37 (LSMS) |
Agency/Well-Being |
Control over use of income |
Malapit and others (2019) |
Individual, sex disaggregated |
Population monitoring/M&E |
50+ |
Agency/Well-Being |
Incidence of intimate partner violence |
Bloom 2008; Villarreal 2007; Rocca et al. 2009; Ghimire et al. 2015; Grabe et al. 2015; Kotsadam et al. 2016; Miedema et al. 2016; Haile et al. 2012, Mahmud & Tasneem 2014 |
Individual, women only |
M&E |
- |
Possession of a Legal ID |
Percentage of those over 15 years old who have a national identity card |
World Bank Findex |
Individual |
Population monitoring |
140 |
Access to (Digital) Financial Services |
Used a mobile phone or the internet to access an account, female (percentage of age 15+) |
World Bank Findex |
Individual, women only (Can be compared same figure for men/boys) |
Population monitoring |
140 |
Access to (Digital) Financial Services |
Women with account at financial institution or with mobile money-service provider (% of women ages 15 and older) |
World Bank Findex |
Individual, women only (Can be compared to same figure for men/boys) |
Population monitoring |
140 |
Access to Financial Services |
Has separate savings/financial assets from husband (Y/N) |
Glennerster and others (2018) |
Individual, women only |
M&E |
- |
Distribution of Payments |
Number of payments were made (disaggregated by sex, age and other demographic characteristics where data available allows) |
Government administrative database |
Individual, sex disaggregated |
M&E |
|
Withdrawal of Payments |
Number of people withdrawing payments (disaggregated by sex, age, and other demographic characteristics where data available allows) |
Government administrative database Note: This will be possible if there is a unique receptable for G2P payments, which is quite rare, as most transfers are directed to general purpose accounts (and therefore fungible). Could also explore through recipient surveys. |
Individual, sex disaggregated |
M&E |
|
System Readiness/Capacity |
Does the government have data and distribution systems in place to provide digital social protection payments to eligible recipients? |
JAM index, CGD Citizens and States report Captures level of bank account, ID, and mobile phone ownership – though as distinct from coverage, given a single individual’s potential to own multiple phones; have multiple accounts. (Government administrative databases/World Bank Findex) |
National |
Population monitoring |
140 |
Are these systems able to reach and benefit women in the COVID context? |
Country vulnerability assessment, Data2X and Open Data Watch The country vulnerability tool draws upon data from 75 low- and lower middle-income countries on macroeconomic stability/growth, COVID-19 trends, women’s vulnerability, gender data gaps, country capacities measured by birth registration, ID and bank by sex (when available), and aid flows. |
National |
Population monitoring |
75 |
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