A. Spending Adequacy

Spending adequacy refers to whether total SSN spending is sufficient to achieve a government’s social policy objectives. While these objectives can be numerous, poverty alleviation is typically seen as the primary objective of SSNs so that spending adequacy can be initially analyzed by using the level of SSN spending required to eliminate poverty as a useful benchmark. This is typically done by specifying a relevant poverty line and then calculating the aggregate transfers required to bring all poor households at least to this income threshold (Box 4). Such estimates depend on where the poverty line is drawn and implicitly assume perfect targeting (that is, all SSN spending goes to poor households and benefit levels reflect poverty gaps), which ignores the inevitable leakage of benefits to nonpoor households due to weak administrative capacity or political and social constraints in the use of targeting methods. Indeed, in the presence of such costs, perfect targeting is not necessarily optimal. Allowing for these factors, this approach to estimating spending adequacy benchmarks should be treated as a lower bound, that is, the minimum level of spending required to eliminate poverty. To the extent that SSN objectives go beyond poverty alleviation, including promoting human capital formation, this may also require higher spending.

SSN spending levels vary considerably across countries and regions.

• Advanced economies. Spending on SSN programs and passive labor market programs (unemployment income support) averages about 2 percent of GDP, although there is significant variation across countries (Figure 1).⁷ For example, while Canada, Finland, and France spend almost 4 percent of GDP on these policies, Lithuania, Korea, the Slovak Republic, and the United States spend less than 1 percent. The bulk of spending, averaging about 1.4 percent of GDP, is related to SSN programs, with family allowances accounting for about half of this. However, one expects that spending on labor market programs becomes relatively more significant during economic downturns.⁸

• Emerging and developing economies. While SSN spending in emerging and developing Europe and Latin America and the Caribbean countries is similar to that in advanced economies, spending is substantially lower in emerging and developing Asia and sub-Saharan Africa (SSA) (Figure 2).⁹ There is also significant variation across countries within regions. For instance, among emerging and developing Europe, Ukraine and Kosovo spend over 4 percent of GDP, while Montenegro spends only about 0.6 percent of GDP. In sub-Saharan Africa, while Lesotho spends more than 5 percent of GDP in SSN programs, several countries, including Cameroon, Guinea-Bissau, and South Sudan, spend less than 0.2 percent (although they may have subsidies on consumption of goods such as fuel and food). Low SSN spending in many EMDEs translates into a combination of low program coverage and benefit levels, in the face of large poverty levels and gaps. Poverty levels, which reflect the incidence (share of the population that are poor) and poverty gaps which reflect the intensity (how far the income of the poor is from the poverty line) of poverty, are higher in emerging and developing Asia (and especially SSA) compared to other regions (Figure 3, panel a). Similarly, SSN coverage of low-income households (that is, the share of the population in the poorest quintile covered by SSN programs) remains quite low in many developing countries, with coverage gaps being especially pronounced in SSA (Figure 3, panel b). In addition, SSN benefit levels are usually low relative to needs in many LICs.

Spending on SSN and Passive Labor Market Programs in Selected Advanced Economies

(Share of GDP, latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: The chart includes spending on passive labor market policies (unemployment income support) and SSN spending, which includes family allowances, housing assistance, and other social assistance and income support. Categories are ultimately shaped by countries’ specific benefit architecture and some types of support may be categorized differently across countries.

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Spending on SSN and Passive Labor Market Programs in Selected Advanced Economies

(Share of GDP, latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: The chart includes spending on passive labor market policies (unemployment income support) and SSN spending, which includes family allowances, housing assistance, and other social assistance and income support. Categories are ultimately shaped by countries’ specific benefit architecture and some types of support may be categorized differently across countries.

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Spending on SSN and Passive Labor Market Programs in Selected Advanced Economies

(Share of GDP, latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: The chart includes spending on passive labor market policies (unemployment income support) and SSN spending, which includes family allowances, housing assistance, and other social assistance and income support. Categories are ultimately shaped by countries’ specific benefit architecture and some types of support may be categorized differently across countries.

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SSN Spending in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank ASPIRE database—The Atlas of Social Protection; and IMF staff calculations.Note: Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean.

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SSN Spending in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank ASPIRE database—The Atlas of Social Protection; and IMF staff calculations.Note: Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean.

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SSN Spending in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank ASPIRE database—The Atlas of Social Protection; and IMF staff calculations.Note: Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean.

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Poverty and Social Safety Nets in Emerging and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet (panel a); ASPIRE—Atlas of Social Protection (panel b); and IMF staff calculations.Note: In panel a, the poverty gap is the mean shortfall in income or consumption from the poverty line (counting the non-poor as having zero shortfall), expressed as a percentage of the poverty line. Estimates consider poverty lines of $1.90 international dollars a day using 2011 PPP conversion rates for low-income countries, $3.20 for lower middle income, and $5.50 for upper middle income and high-income countries. Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean. In panel b, dashed line denotes median value. Coverage is defined as the share of the population in the poorest quintile covered by SSN programs. Benefit adequacy is defined as the SSN benefit amount divided by household income before transfers.

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Poverty and Social Safety Nets in Emerging and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet (panel a); ASPIRE—Atlas of Social Protection (panel b); and IMF staff calculations.Note: In panel a, the poverty gap is the mean shortfall in income or consumption from the poverty line (counting the non-poor as having zero shortfall), expressed as a percentage of the poverty line. Estimates consider poverty lines of $1.90 international dollars a day using 2011 PPP conversion rates for low-income countries, $3.20 for lower middle income, and $5.50 for upper middle income and high-income countries. Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean. In panel b, dashed line denotes median value. Coverage is defined as the share of the population in the poorest quintile covered by SSN programs. Benefit adequacy is defined as the SSN benefit amount divided by household income before transfers.

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Poverty and Social Safety Nets in Emerging and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet (panel a); ASPIRE—Atlas of Social Protection (panel b); and IMF staff calculations.Note: In panel a, the poverty gap is the mean shortfall in income or consumption from the poverty line (counting the non-poor as having zero shortfall), expressed as a percentage of the poverty line. Estimates consider poverty lines of $1.90 international dollars a day using 2011 PPP conversion rates for low-income countries, $3.20 for lower middle income, and $5.50 for upper middle income and high-income countries. Box plots with 10th percentile and 90th percentile boundaries. Line denotes median and diamond denotes mean. In panel b, dashed line denotes median value. Coverage is defined as the share of the population in the poorest quintile covered by SSN programs. Benefit adequacy is defined as the SSN benefit amount divided by household income before transfers.

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If addressing absolute poverty is the primary objective of SSNs, in most EDMEs SSN spending should increase significantly to achieve this objective. The additional spending required to eliminate poverty in EMDEs, even assuming perfect targeting, is sizable, especially relative to existing spending on SSNs (Figure 4). Given large poverty gaps, estimates suggest that to eliminate poverty countries in sub-Saharan Africa will need to spend about 10 percent of GDP on average, in addition to current spending. Of course, estimates that take account of the inevitable leakage of benefits to nonpoor households would result in even larger spending needs—for example, if half of the transfer budget leaks to nonpoor households, then spending needs would be doubled. In addition, these estimates are static and rely on current poverty rates. In many developing countries, a considerable proportion of the population remains vulnerable to falling into poverty, so negative shocks could significantly increase the spending required to eliminate poverty. In addition, achieving the broader objectives of SSNs, such as enhancing investment in human capital by poor and vulnerable households, would further increase spending needs.

Estimated Additional Spending Required to Eliminate Poverty in EMDEs, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet; and IMF staff calculations.Note: Estimates consider poverty lines of $1.90 international dollars using 2011 PPP conversion rates for low-income countries, $3.20 for lower-middle income, and $5.50 for upper-middle income and high-income countries. The poverty gap index is calculated over the whole population. Therefore, to obtain the aggregate poverty gap for each country, we apply the following formula: Poverty Gap Index × Poverty Line × 365 × Population. Box plots with 10th percentile and 90th percentile boundaries. Horizontal lines denote median values and diamonds denote means.

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Estimated Additional Spending Required to Eliminate Poverty in EMDEs, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet; and IMF staff calculations.Note: Estimates consider poverty lines of $1.90 international dollars using 2011 PPP conversion rates for low-income countries, $3.20 for lower-middle income, and $5.50 for upper-middle income and high-income countries. The poverty gap index is calculated over the whole population. Therefore, to obtain the aggregate poverty gap for each country, we apply the following formula: Poverty Gap Index × Poverty Line × 365 × Population. Box plots with 10th percentile and 90th percentile boundaries. Horizontal lines denote median values and diamonds denote means.

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Estimated Additional Spending Required to Eliminate Poverty in EMDEs, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: World Bank PovcalNet; and IMF staff calculations.Note: Estimates consider poverty lines of $1.90 international dollars using 2011 PPP conversion rates for low-income countries, $3.20 for lower-middle income, and $5.50 for upper-middle income and high-income countries. The poverty gap index is calculated over the whole population. Therefore, to obtain the aggregate poverty gap for each country, we apply the following formula: Poverty Gap Index × Poverty Line × 365 × Population. Box plots with 10th percentile and 90th percentile boundaries. Horizontal lines denote median values and diamonds denote means.

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While relative poverty gaps also remain in advanced economies, the additional spending needs to eliminate these gaps are relatively small, especially compared to existing spending (and tax) levels. In advanced economies, the incidence of extreme absolute poverty (per capita income below $1.90 per day) is very low and concerns about social inclusion, better captured by relative poverty, are more relevant (see Box 4). The additional SSN spending required to eliminate relative poverty in advanced economies, based on a poverty line equal to half the median household income of the total population and assuming perfect targeting, would average about 1 percent of GDP, although there is significant variation across countries (Figure 5). Spending needs would likely be greater to the extent that SSNs have broader objectives beyond poverty alleviation. While countries with relatively low tax and total spending levels can consider increasing SSN spending to reduce remaining poverty gaps (for example, financed through expanding progressive taxation), for many countries there may also be substantial room to address remaining poverty gaps through improving targeting efficiency (for example, through greater use of means testing).

Estimated Spending Required to Eliminate Relative Poverty in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: Estimates consider a poverty line equivalent to half the median household income of the total population.

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Estimated Spending Required to Eliminate Relative Poverty in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: Estimates consider a poverty line equivalent to half the median household income of the total population.

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Estimated Spending Required to Eliminate Relative Poverty in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.Note: Estimates consider a poverty line equivalent to half the median household income of the total population.

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Assessing the adequacy of SSN spending in advanced economies also requires an analysis of ALMPs, since these programs interact with and complement SSN programs. In advanced countries, spending on these programs averages 0.3 percent of GDP (Figure 6).¹⁰ However, there is large variation in ALMP spending across countries, with spending reaching almost 2 percent of GDP in Denmark and less than 0.2 percent of GDP in several countries (including Australia, Greece, Italy, and Japan). On average, training and public employment services account for most of the spending in ALMPs. The adequacy of ALMP spending will depend on the share of unemployed workers receiving these benefits. Going forward, many countries may need to scale up ALMP programs to promote job mobility amid ongoing changes in the nature of work and to avoid labor market scarring following the pandemic. There is large heterogeneity across programs, and careful attention to the design and implementation of these programs is crucial for their effectiveness (see Box 2). ALMPs in advanced economies are often closely integrated with SSN programs with, for example, continued eligibility for SSN benefits being conditional on participation in programs that offer job search support or skills training. In many cases, this integration is intended to ameliorate the labor disincentives that may arise from means-tested programs. However, such integration requires significant administrative capacity.

Government Spending on Active Labor Market Policies in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.

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Government Spending on Active Labor Market Policies in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.

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Government Spending on Active Labor Market Policies in Selected Advanced Economies

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: OECD; and IMF staff calculations.

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B. Spending Efficiency

SSN spending is efficient if it meets the government’s policy objective in a cost-effective manner and without causing undue labor (or other) market distortions. The design of SSN programs, as well as their implementation, can significantly affect their efficiency as well as their effectiveness in fighting poverty. Spending inefficiencies can arise through various channels, including:

• Targeting efficiency. The ability of SSN programs to pursue, for example, the typical objective of alleviating poverty depends on the number of poor households that they reach (thus avoiding errors of exclusion) as well as on providing benefits that are large enough to bring poor households above the poverty line. Conversely, for a given transfer budget, leakage of benefits to nonpoor households can result in low coverage of poor households and low benefit levels. An evaluation of targeting efficiency also needs to consider how transfers are financed since, for example, financing through progressive taxes helps to claw back much of the transfers received by high-income groups (Coady and Le 2020).

• Administrative and implementation costs. All transfer programs incur administrative costs. These costs relate to the collection and analysis of data to identify the targeted groups, the creation of a beneficiary registry, the development of an infrastructure for delivering benefits, and the continuous monitoring of actual and potential beneficiaries to determine eligibility. While these costs can generate benefits (for example, in terms of targeting efficiency and coverage of the poor), they can become unnecessarily high, especially in the presence of multiple, duplicating, and fragmented programs. Efficient implementation also requires strong PFM systems to ensure allocated financing is available to SSN programs in a predictable and timely manner.

• Work disincentives. Targeting of benefits using means testing (that is, the withdrawal of benefits as income increases) introduces work disincentives which can result in lower labor force participation and reduced incentives to increase earnings when in work. This, in turn, undermines the objective of poverty alleviation.

Targeting Efficiency

While the targeting efficiency of SSN spending varies substantially across countries and regions, a significant share of transfers accrues to nonpoor households in both advanced countries and EMDEs. Reflecting their primary objective of poverty alleviation, the targeting efficiency of SSN spending is typically evaluated by looking at the benefit incidence of SSN transfers, that is, the share of transfers going to poor (or lower-income) households. However, such an evaluation should also allow for any broader objectives of SSN spending, such as consumption smoothing across the life cycle and promoting investment in human capital (see Annexes 2 and 3), as well as how transfers are financed.

• Advanced economies. Targeting performance can be expected to be relatively high in advanced economies with stronger administrative capacity to implement means-tested transfers. However, among high-income European countries, on average only around 28.3 percent of all SSN transfers accrue to the poorest 20 percent of the population and less than 49 percent accrue to the poorest 40 percent (Figure 7, panel a). While means-tested transfers are better targeted (Figure 7, panel b), only around one-third of SSN transfers in high-income European countries are means tested (Coady and others 2021). Even then, in half of the countries in the sample, less than 50 percent of means-tested transfers accrue to the poorest 20 percent of the population. Therefore, if warranted (for example, by fiscal consolidation pressures), there is ample room for improvements in targeting efficiency through increasing the share of means-tested transfers in total transfers or even improving the targeting of means-tested programs.

• EMDEs. In EMDEs, the targeting efficiency of SSN spending also varies significantly both within and across regions (Figure 8). But in a large share of countries there is significant leakage of transfers to nonpoor households, especially in LICs. For example, in half of all countries in emerging and developing Asia and sub-Saharan Africa, less than 35 (55) percent of transfers accrue to the poorest 20 (40) percent of the population, which is not much better than what would result from a universal (untargeted) transfer program (that is, 20 and 40 percent, respectively). In many cases, leakage of SSN transfers to nonpoor households arises due to deficiencies in program design and implementation as well as difficulties in verifying and monitoring incomes. Leakage may also reflect an explicit decision to target a broader population, either because programs have broader objectives than poverty reduction or because the costs of narrowly targeting transfers based on means tests (including administrative, social, and political costs) are deemed too high.

Benefit Incidence of Total and Means-Tested Benefits in European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: EUROMOD; and IMF staff calculations.Note: EUROMOD means-tested transfer data may include both contributory and non-contributory transfers. Definition varies for each country but, e.g., for Belgium, benefits include: child benefits, birth allowance, income support, income support for the elderly, permanent disability benefits, sickness related benefits, scholarships and grants, housing related benefits, unemployment benefits, parental leave, maternity leave.

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Benefit Incidence of Total and Means-Tested Benefits in European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: EUROMOD; and IMF staff calculations.Note: EUROMOD means-tested transfer data may include both contributory and non-contributory transfers. Definition varies for each country but, e.g., for Belgium, benefits include: child benefits, birth allowance, income support, income support for the elderly, permanent disability benefits, sickness related benefits, scholarships and grants, housing related benefits, unemployment benefits, parental leave, maternity leave.

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Benefit Incidence of Total and Means-Tested Benefits in European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: EUROMOD; and IMF staff calculations.Note: EUROMOD means-tested transfer data may include both contributory and non-contributory transfers. Definition varies for each country but, e.g., for Belgium, benefits include: child benefits, birth allowance, income support, income support for the elderly, permanent disability benefits, sickness related benefits, scholarships and grants, housing related benefits, unemployment benefits, parental leave, maternity leave.

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Benefit Incidence of SSN Transfers in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE-Atlas of Social Protection; and IMF staff calculations.Note: Benefit incidence is defined as the share of total transfers going to poor households.

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Benefit Incidence of SSN Transfers in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE-Atlas of Social Protection; and IMF staff calculations.Note: Benefit incidence is defined as the share of total transfers going to poor households.

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Benefit Incidence of SSN Transfers in EMDEs, by Region

(Latest available data)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE-Atlas of Social Protection; and IMF staff calculations.Note: Benefit incidence is defined as the share of total transfers going to poor households.

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Large differences in targeting efficiency, both across countries and programs, suggest that SSN spending efficiency could be increased by improving program design or reallocating spending across programs. The large variation in targeting efficiency across countries shown in Figures 8 and 9 suggests that countries with lower targeting efficiency could improve program design by learning from the best practices of more efficient countries. There are also large differences in efficiency across programs of different types, even when considering countries with similar levels of development (Figure 9). Conditional cash transfers, in particular, seem to have higher benefit-cost ratio compared with other SSN programs (World Bank 2018). Public work programs also appear to have relatively high benefit-cost ratios in emerging market economies. These large variations suggest that there is room to increase SSN efficiency by expanding programs that are better targeted, possibly by reallocating resources from other programs, by improving program design, or by applying the targeting design of well-targeted programs to other programs. Targeting efficiency can be increased in some cases by relying on local governments, which may have better information to identify those in need. However, in some countries, lack of administrative capacity and weak governance at the local level may result in higher costs and “elite program capture,” and therefore the right level of decentralization is likely to vary across countries.

Benefit-Cost Ratio of Social Safety Net Transfers by Type of Social Safety Net Program

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE—Atlas of Social Protection; and IMF staff calculations.Note: Benefit-cost ratio is defined as (poverty gap before transfer—poverty gap after transfer)/total transfer amount). Box plots with 25th percentile and 75th percentile boundaries. Line denotes median and diamond denotes mean. The end of upper and

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Benefit-Cost Ratio of Social Safety Net Transfers by Type of Social Safety Net Program

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE—Atlas of Social Protection; and IMF staff calculations.Note: Benefit-cost ratio is defined as (poverty gap before transfer—poverty gap after transfer)/total transfer amount). Box plots with 25th percentile and 75th percentile boundaries. Line denotes median and diamond denotes mean. The end of upper and

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Benefit-Cost Ratio of Social Safety Net Transfers by Type of Social Safety Net Program

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Sources: ASPIRE—Atlas of Social Protection; and IMF staff calculations.Note: Benefit-cost ratio is defined as (poverty gap before transfer—poverty gap after transfer)/total transfer amount). Box plots with 25th percentile and 75th percentile boundaries. Line denotes median and diamond denotes mean. The end of upper and

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Work Disincentives

The design and generosity of SSN benefits can create work disincentives, especially when benefits are means tested. SSN benefits, irrespective of the targeting criteria used for determining eligibility, can generate work disincentives through an income effect (higher out-of-work income). Means-tested benefits can generate additional work disincentives through a substitution effect, as the returns to work decrease if higher labor income leads to the withdrawal of benefits. Thus, means-tested benefits can reduce employment take-up and the number of hours worked. Whether such financial disincentives actually affect employment outcomes will depend on both labor demand and supply responses (Coady and others 2021). The magnitude of the work disincentives created by SSN programs will also depend on how these programs interact with social insurance programs, the tax system, and other types of social spending (for example, education and health). The magnitude of these disincentives may also differ across individuals. Indeed, empirical evidence finds that work disincentives in advanced economies are particularly important for low-income and secondary (typically female) workers (Meghir and Phillips 2010). There is also suggestive evidence that eligibility criteria and generosity of benefits can affect the choice between formal and informal employment (Bosch and Manacorda 2012). However, empirical evidence suggests that work disincentives from SSN transfers in developing countries are relatively small, partly reflecting low benefit levels. On the contrary, substantial evidence suggests that SSN transfers generate a range of positive externalities (Banerjee and others 2017; Bastagli and others 2016; Handa and others 2018; Samson 2009).

The work disincentives created by means-tested SSN programs vary significantly across countries and are often quite high. The magnitude of work disincentives created by means-tested SSN programs can be estimated based on participation tax rates (PTRs) and marginal effective tax rates (METRs) (Coady and others 2021). The PTR is defined as the share of additional household income from moving into employment that is lost due to reductions in benefits and income taxation. The METR is defined as the share of additional household income from an increase in earnings that is lost due to reductions in benefits and income taxation. PTRs and METRs therefore depend on household composition, the level of earnings, the generosity of benefits, the rate at which means-tested benefits are tapered, and the interaction with the tax system. OECD estimates for selected high-income European countries show that PTRs (Figure 10, panel a) and METRs (Figure 10, panel b) vary across household types and are quite high in many countries, suggesting possible room to reduce these to provide stronger work incentives.

Participation Tax Rates and Marginal Effective Tax Rates in High-Income European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: Coady et al. (2021).Note: Analysis considers guaranteed minimum income schemes in 24 high-income European countries. Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentiles of the distribution and the horizontal line denotes the median.

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Participation Tax Rates and Marginal Effective Tax Rates in High-Income European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: Coady et al. (2021).Note: Analysis considers guaranteed minimum income schemes in 24 high-income European countries. Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentiles of the distribution and the horizontal line denotes the median.

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Participation Tax Rates and Marginal Effective Tax Rates in High-Income European Countries

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: Coady et al. (2021).Note: Analysis considers guaranteed minimum income schemes in 24 high-income European countries. Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentiles of the distribution and the horizontal line denotes the median.

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A key challenge for the design of means-tested SSN programs is how to best manage the inherent trade-off between poverty reduction (equity) and work disincentives (efficiency). Countries adopt various approaches to limit the magnitude of work disincentives, including (1) restricting the generosity of benefits, (2) tapering the withdrawal of benefits, and (3) providing additional in-work income support (that is, wage subsidies). Many countries only reduce SSN means-tested transfers gradually as income increases to avoid so-called cliff-edge effects where earning a marginal amount of income could lead to the complete loss of a benefit and therefore very high disincentives for entering employment and increasing earnings. However, while more gradual benefit withdrawal reduces the work disincentive effects, it also increases the fiscal costs of transfers. Additional in-work income support (that is, wage subsidies) can further strengthen work incentives and can be effectively combined with lower out-of-work benefits for certain groups (for example, single working-age individuals). However, while low benefit levels can provide strong incentives to take up employment, this can undermine the primary poverty-alleviation objective of SSN programs. To reduce work disincentives without undermining poverty alleviation, countries can use complementary labor market activation policies, strengthening program conditions such as mandated job search and acceptance of employment offers. Conditionalities can also include mandatory participation in training programs that aim to ensure that recipients are both equipped and incentivized to participate in the labor market (International Labour Organization 2021b), although this may require significant administrative capacity.

Unemployment insurance programs also need to be carefully designed to incentivize return to work and manage fiscal costs (IMF 2012). Structuring unemployment benefits so that they decline over time motivates workers to undertake more intensive job searching. Initial replacement rates should be set below full replacement to reduce incentives to enter unemployment, but high enough to facilitate an initial period of intensive job search aimed at improving job match quality and thus worker productivity. Increased use of individual unemployment savings accounts could help to reduce the incidence and duration of unemployment. Under this system, part of the unemployment insurance contribution is credited to an individual account on which a person receives interest. During a period of unemployment, individuals can draw money from their account. Once the account is exhausted, individuals can borrow from the government at the same interest rate. Individual accounts are used in a number of emerging economies, including Brazil and Chile (Hijzen and Venn 2011). These could be combined with the use of layoff taxes or “experience rating,” whereby firms with higher layoffs in a previous year face higher unemployment contribution rates. Countries could be encouraged to use experience rating instead of employment protection legislation to reduce incentives for layoffs (Blanchard and Tirole 2004).

C. Fiscal Sustainability

SSN spending is sustainable if it can be financed without undermining government debt sustain-ability or crowding out other high-priority spending. Assessing sustainability therefore requires a comprehensive assessment of current and planned SSN spending within an integrated MTFF that reflects existing spending pressures and revenue mobilization capacity. Both advanced economies and EMDEs face challenges that will need to be addressed to ensure their SSNs can achieve their objectives in a fiscally sustainable manner. When fiscal space is limited, SSN spending may be increased gradually over time as policy reforms are introduced aimed at enhancing revenue mobilization or reallocating spending. Understanding how SSN spending will be financed (for example, new taxation or lowering other spending) is also important since the financing side can also have a direct impact on poverty.

Advanced economies and some emerging market economies face challenges that will restrict the fiscal space available for SSN spending while creating additional upward pressure on SSN spending. These challenges arise from high debt levels, increasing age-related spending pressures, and a changing world of work.

• High debt levels. In response to the COVID-19 pandemic, advanced economies (Figure 11) and emerging market economies (Figure 12) have provided significant fiscal support, resulting in higher gross financing needs and government debt levels. Between 2019 and 2020, the increase in government debt from already high levels is unprecedented, with debt-to-GDP ratios in advanced economies averaging 82.6 percent in 2020, and the change in the debt to GDP ratio averaging 12.6 percent. For emerging market economies, the change in the debt to GDP ratio was 13.1 percent, on average.

• Increasing age-related spending pressures. Advanced economies (Figure 13) and some emerging market economies (Figure 14) face significant spending pressures due to aging populations, with government priority outlays for pensions and health care expected to increase by 1.6 percent of GDP in advanced economies and 1.8 percent of GDP in EMDEs, on average, between 2020 and 2030.

• A changing world of work. Structural changes transforming the nature of work create challenges for contributory employment and social insurance programs in advanced economies and may lead to SSN spending pressures. Less stable employment relations put a premium on SSNs centered on workers rather than jobs and point to the need for labor market and social insurance reforms.

Debt to GDP Ratios for Selected Advanced Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021 (IMF, 2021b).

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Debt to GDP Ratios for Selected Advanced Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021 (IMF, 2021b).

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Debt to GDP Ratios for Selected Advanced Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021 (IMF, 2021b).

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Debt to GDP Ratios for Selected Emerging Market Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021.Note: Selected countries are those with change in debt to GDP ratio (2019 and 2020) above the median (10.37 percent of GDP) for emerging market economies.

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Debt to GDP Ratios for Selected Emerging Market Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021.Note: Selected countries are those with change in debt to GDP ratio (2019 and 2020) above the median (10.37 percent of GDP) for emerging market economies.

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Debt to GDP Ratios for Selected Emerging Market Economies (2019 and 2020)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: World Economic Outlook, October 2021.Note: Selected countries are those with change in debt to GDP ratio (2019 and 2020) above the median (10.37 percent of GDP) for emerging market economies.

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Projected Change in Age-Related Government Spending for Advanced Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Projected Change in Age-Related Government Spending for Advanced Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Projected Change in Age-Related Government Spending for Advanced Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Projected Change in Age-Related Government Spending for (Select) Emerging Market Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Projected Change in Age-Related Government Spending for (Select) Emerging Market Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Projected Change in Age-Related Government Spending for (Select) Emerging Market Economies (2021–30)

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: April 2022 Fiscal Monitor (IMF, 2022b).

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Age-related spending pressures, coupled with high debt burdens, could require sharp rationalization of other public spending or necessitate large tax increases that could hamper economic growth. Countries with relatively low tax ratios may have room to increase fiscal space by increasing progressive taxation and its efficiency (for example, better integration of personal income tax and corporate income tax systems to reduce tax evasion and avoidance, addressing the challenge posed by increasing international mobility of the tax base, and greater use of carbon taxes). Countries with already high tax ratios should focus on improving efficiency of SSN and other spending, including through spending reallocation.

EMDEs face challenges to increase SSN coverage and spending to eliminate poverty and address other SSN objectives given their low tax revenues and competing priority spending needs, especially when facing high debt levels.

• Weak tax systems. Expanding tax revenues is crucial for increasing and sustaining SSN spending in many EMDEs while avoiding crowding out of other priority public spending. Many emerging market economies and most developing countries have low tax capacity and low tax effort (given their existing capacity), reflecting administrative constraints and significant scope to improve tax policy, including through broad-based consumption and progressive income taxes. More than half of LICs, and a third of emerging market economies, have tax-to-GDP ratios below 15 percent, a level that is associated with moving to a higher growth path (Gaspar, Jaramillo, and Wingender 2016). The large variation in tax-to-GDP ratios across EMDEs suggests that many countries have room for increasing tax revenues (Figure 15, panel a). Indeed, in most EMDEs there is a large gap between current tax revenues and estimated tax capacity—the predicted maximum taxation in an economy given its macroeconomic, demographic, and institutional features (Figure 15, panel b). Even closing part of the gap could substantially increase available resources (IMF 2021c). International experience suggests that increasing the tax-to-GDP ratio by about 3–7 percentage points over time through comprehensive policy and administration reforms is an ambitious but achievable goal for many low-income developing countries (Akitoby and others 2019). Increasing tax revenues will require an expansion of broad-based consumption taxes and selective excise taxes, as well as the development of progressive income tax systems. The cyclical nature of SSN spending, which needs to increase during economic downturns, requires reliable and sustained financing sources over the long term. In LICs that lack the capacity to mobilize revenues in the short term, emergency financing from international financial institutions and donors will remain crucial to mitigate the impact of large negative systematic shocks. SSNs may need to be strengthened gradually in LICs and fragile and conflict-affected states given their limited administrative and fiscal capacity.

• Competing priority spending needs. Low-income developing countries have significant development challenges that require higher and sustained public spending on physical and human capital investment, which are crucial for promoting inclusive growth and for longer-term poverty reduction. Estimates suggest that meeting the Sustainable Development Goals in five key areas—health, education, roads, electricity, and water and sanitation—by 2030 would require increasing annual government spending on average by almost 5 and 17 percentage points of GDP in EMEs and low-income developing countries, respectively (Figure 16).¹² Incorporating the costs of addressing climate change and health pandemics would substantially increase spending needs in affected countries.

• Weak PFM systems. Eliminating poverty would require significant increases in SSN spending in many EMDEs, representing a serious fiscal challenge given low current tax collection and other spending pressures. Successfully addressing this challenge will require credible MTFFs that set out social spending measures, a strategy to increase tax effort, and reliable external financing options. A credible MTFF that sets out spending priorities is crucial to ensure that additional SSN spending needs do not crowd out spending needs in other areas (for example, health, education, and infrastructure). Strong commitment from country authorities, backed by a clear medium-term revenue strategy, to enhance tax capacity and increase tax collection is necessary to help finance additional spending needs. To increase the credibility of reforms, the MTFF should also reflect reliable financing options with the proper mix of domestic, foreign, public, and nonpublic funding sources capable of financing the scale-up of SSN spending in response to shocks (Beegle, Coudouel, and Monsalve 2018). PFM systems, particularly in LICs, may need enhancements to be able to translate the government’s policy priorities into budgetary allocations to deliver SSN programs efficiently. A robust monitoring and evaluation system, including a systematic use of spending reviews, will be critical to judging the program effectiveness as well as funding needs. External financing from international financial institutions and donors can play an important role in financing upfront investments in strengthening SSN institutional capacity. In low-income and fragile states, external financing may also be required to finance transfers until countries develop capacity to increase tax revenues.

Tax Systems in Emerging Markets and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF 2021c.Note: Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentile of the distribution and the horizontal line denotes the median. Figure 15b depicts median by region.

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Tax Systems in Emerging Markets and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF 2021c.Note: Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentile of the distribution and the horizontal line denotes the median. Figure 15b depicts median by region.

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Tax Systems in Emerging Markets and Developing Economies

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF 2021c.Note: Box plot limits indicate the 10th (bottom limit) and 90th (upper limit) percentile of the distribution and the horizontal line denotes the median. Figure 15b depicts median by region.

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Government Spending Required to Meet the Sustainable Development Goals in Selected Sectors by 2030, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF staff estimates.

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Government Spending Required to Meet the Sustainable Development Goals in Selected Sectors by 2030, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF staff estimates.

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Government Spending Required to Meet the Sustainable Development Goals in Selected Sectors by 2030, by Region

Citation: Technical Notes and Manuals 2022, 007; 10.5089/9798400222504.005.A001

Source: IMF staff estimates.

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Resource-rich countries face the additional challenge of managing highly volatile commodity revenues to maintain fiscal space for SSN spending. Financing the expansion of SSN spending through short-term revenue windfalls from a sharp increase in commodity prices is not fiscally sustainable. The expansion of SSN spending should be clearly embedded in an MTFF anchored on conservative assumptions of international commodity price trends. SSNs should also be carefully designed to facilitate temporary expansion in response to commodity price shocks. This requires that resource-rich countries build fiscal buffers during periods of commodity price increases. It also points to the need to strengthen broader tax capacity to decrease reliance on narrow revenue sources.

A. General Considerations

Discussions of SSN issues in country papers should aim at assessing the macro-criticality of such issues and, where relevant, provide a clear analysis of policy concerns and advice. Discussions in country reports should cover the following principles and basic questions (Table 1):

• Assessing macro-criticality. This requires evaluating the SSN system and reforms through the three channels of macro-criticality: adequacy, efficiency, and sustainability. SSN issues can be deemed macro-critical through any one or combination of these three channels. Country reports should ideally conduct this evaluation by assessing the overall SSN system rather than individual SSN programs. Macro-criticality might refer to the status quo or to prospective situations, for example, to protect the vulnerable population from planned and desirable economic and structural reforms. As the COVID-19 pandemic has made clear, the macro-criticality of SSN issues can also reflect the need to address temporary shocks. Country reports should explain why a specific SSN issue is considered macro-critical. If SSN issues are not deemed macro-critical in a specific country, no coverage is expected.

• Providing key facts about the existing SSN and reform proposals. If SSN issues are assessed to be macro-critical, the analysis should start by considering the objectives of the SSN and clarifying coverage and benefit levels (including trends and comparison with peer groups), modalities of delivery, and financing sources in the context of strengthening the SSN. The consistency between the SSN objectives, design, and capacity to deliver should also be assessed, in particular in the context of the timeline needed to strengthen the SSN.

• Identifying specific policy concerns and linking them to policy recommendations. Policy concerns may derive from the assessment of the adequacy, efficiency, and sustainability of the SSN, and clear links between concerns and policy advice should be established. Policy advice should reflect the analyses and recommendations of IMF staff, including through IMF technical assistance, and government reports. Staff should also draw on the expertise of IMF development partners working on the country (for example, the World Bank, the United Nations Children’s Fund, and the International Labour Organization). The analysis should include an assessment of the institutional capacity or other conditions constraining policy implementation and how to minimize such constraints, including areas that might require additional technical assistance.

• Assessing macroeconomic and political implications of recommended policies. The assessment should cover the likely impact of SSN spending on macroeconomic performance and stability and whether policy design and implementation plans are consistent with the government’s overall macroeconomic strategy and implementation capacity. It should also discuss the level of public trust and political consensus supporting SSN measures.

^{Table 1.}

Illustrative Questions on SSN Issues in Surveillance and Program Work

^{Table 1.}

Illustrative Questions on SSN Issues in Surveillance and Program Work

Establish macro-criticality	Lay out the facts and proposed measures	Identify specific policy concerns	Formulate policy options	Integrate into broader macroeconomic analysis
Are SSN spending and benefits levels adequate to achieve its objective?	What are the key characteristics and objectives of the current SSN system and/or reform proposals?	Where do concerns lie? Is it with the design? Coverage inadequate? The capacity to implementation? With its impact?	If SSN is inadequate to meet social objectives, is there fiscal space to increase them? If not, find measures to increase fiscal space.	How do policy recommendations fit in with IMF advice on fiscal consolidation and the team’s macro framework? What are the options to alleviate the possible tradeoffs or inconsistencies?
How efficient is SSN? Is inefficiency related to design or implementation?	Why are changes needed? Why is this specific proposal on the table?	Have these concerns been articulated in previous IMF reports (that is, Article IV)? Are they new? Are there analytical gaps?	If SSN is inefficient, identify measures to increase value for money such as better monitoring and control mechanisms.	What are the main political economy considerations? How widespread is stakeholder buy-in for the SSN design/change?
Is the SSN system, including reform proposals, fiscally sustainable? Does existing SSN spending levels or proposed spending increases threaten macroeconomic stability? Is it urgent, time-sensitive, or vital for political stability?	What is the role of the SSN in the broader social protection system?	Are SSN measures eroding fiscal sustainability?	If the SSN system is unsustainable, what is the size and timing of needed adjustment?	Is the proposed timing and sequencing realistic or feasible?

View Table

^{Table 1.}

Illustrative Questions on SSN Issues in Surveillance and Program Work

Establish macro-criticality	Lay out the facts and proposed measures	Identify specific policy concerns	Formulate policy options	Integrate into broader macroeconomic analysis
Are SSN spending and benefits levels adequate to achieve its objective?	What are the key characteristics and objectives of the current SSN system and/or reform proposals?	Where do concerns lie? Is it with the design? Coverage inadequate? The capacity to implementation? With its impact?	If SSN is inadequate to meet social objectives, is there fiscal space to increase them? If not, find measures to increase fiscal space.	How do policy recommendations fit in with IMF advice on fiscal consolidation and the team’s macro framework? What are the options to alleviate the possible tradeoffs or inconsistencies?
How efficient is SSN? Is inefficiency related to design or implementation?	Why are changes needed? Why is this specific proposal on the table?	Have these concerns been articulated in previous IMF reports (that is, Article IV)? Are they new? Are there analytical gaps?	If SSN is inefficient, identify measures to increase value for money such as better monitoring and control mechanisms.	What are the main political economy considerations? How widespread is stakeholder buy-in for the SSN design/change?
Is the SSN system, including reform proposals, fiscally sustainable? Does existing SSN spending levels or proposed spending increases threaten macroeconomic stability? Is it urgent, time-sensitive, or vital for political stability?	What is the role of the SSN in the broader social protection system?	Are SSN measures eroding fiscal sustainability?	If the SSN system is unsustainable, what is the size and timing of needed adjustment?	Is the proposed timing and sequencing realistic or feasible?

The analysis of SSN issues in country papers should follow a sequence of key steps relevant to both surveillance and program design.

• Verify that sufficient data are available to lay out key facts for in-depth policy assessment. With different SSN programs running together, and possibly overlapping, the data availability assessment should focus on the SSN system as a whole and cover at least the most important programs.¹³ Basic information needed includes total SSN spending, how many individuals and households are covered by multiple programs and the whole SSN system, including differences in how programs define eligibility, how effective programs are in reaching the intended beneficiaries and avoiding errors of exclusion, delivery mechanisms, and targeting methods (for example, including social registries, national identification, etc.). In LICs, the analysis may need to go beyond government data since donors, nongovernmental organizations, or local partners (for example, civil or religious groups) may operate and finance programs outside the budget. Country teams should work closely with authorities, including specialized public agencies, development partners, and other stakeholders, to validate SSN spending numbers and confirm their reliability.

• Identify the focus of macro-criticality. SSNs can be macro-critical through any or some combination of the three channels mentioned earlier, and the assessment should be tailored to country-specific characteristics. In LICs, for example, where the SSN systems are less developed and coverage typically low, the evaluation could naturally start with assessing benefit adequacy (for example, benefit amount as a share of household income before transfers), coverage (for example, share of poor households receiving SSN benefits), and targeting performance (for example, share of SSN benefits accruing to poor households). In advanced economies where SSN spending is relatively high, evaluations may generally have a greater focus on efficiency, sustainability, and long-term financing. The implications for work incentives should be discussed, particularly where means-testing is widely used. Macro-criticality can also arise from plans to strengthen and reform the SSN, for example, where coverage or benefits need to be expanded in response to an economic shock (for example, resulting from lockdown during the COVID-19 crisis) or to protect low-income households during periods of macroeconomic adjustment.

• Ensure scope and depth of analysis is adequate. The scope and depth of the SSN analysis depends on various factors, including the size of the SSN and its interactions with other social spending programs, their potential macroeconomic impact, the vulnerabilities of targeted groups, available financial resources, authorities’ policy priorities and planned reforms, and the IMF’s in-house expertise and resources. In addition to establishing the key features of the SSN system and identifying macro-criticality and policy concerns, the analysis should investigate delivery methods, including the use of technology and related infrastructure, as they may affect the efficiency of the SSN. Monitoring procedures and targeting mechanisms should also be evaluated to ensure that SSN schemes are serving their intended purposes. If feasible, analyzing the distributional effects of key programs and unintended consequences (for example, regional and gender disparities, and work incentives) would help assess the impact of the SSN. An assessment of how the SSN system might interact with the tax system and other government programs may at times also be important, especially from the perspectives of work incentives and fiscal cost.

• Clarify the time horizon of analysis. The time horizon of the analysis depends on the nature of the issues analyzed and the time to implement policies. For example, where information and delivery systems are strong, scaling up the SSN coverage and establishing a new SSN scheme to address urgent needs and existing shortcomings is likely to require a relatively short time horizon. Where information and delivery systems are weak, enhancing the adequacy and efficiency of SSN schemes, including better targeting and expanded coverage, may require improving design and implementation capacity, which may take time to achieve. Likewise, establishing an SSN for the elderly may involve an analysis of the long-term impact of the policy taking into account the pace of population aging. In addition, the human capital impacts arising from improved schooling, childhood nutrition, and women’s empowerment can take a long time to emerge but are especially important for inclusive growth in LICs.

• Discuss the financing of the SSN. The analysis should cover how to finance any strengthening of the SSN and whether the financing is fiscally sustainable. Discussions should cover whether SSN spending should be financed out of general revenue or through specific financing sources (for example, foreign aid) or whether, for specific programs, local government financing is available and appropriate, and which components of the SSN should rely on social contributions as opposed to general revenue (for example, pensions and unemployment transfers). Where SSN programs are partially financed off-budget (for example, grants), such financing should be taken into account, and ideally brought into the budget, to avoid concerns about the sustainability of essential SSN spending. Financing options for any expansion of the SSN or to fill in existing financing gaps are also typically part of policy discussions on fiscal sustain-ability. Staff should also examine whether the financing is sustainable over the medium and long term, for example, where existing financing is donor funded or domestic revenues are very volatile.

• Consider country-specific circumstances. The analysis of SSN spending cannot abstract from country-specific circumstances that may affect the assessment and policy advice. Such circumstances include the country’s development level, macroeconomic conditions, capacity constraints, social preferences, specific SSN objectives (for example, protect specific groups from the effects of reforms), and political economy. Also, staff should not overlook other possible important factors such as the role of nonstate actors, including civil society and the private sector, any complexities in implementing new policies, and the history of ongoing or past reforms.

• Leverage outside knowledge and create effective coordination with development partners. With different technical expertise at play in examining the macroeconomic impact of SSN spending, IMF analysis would benefit greatly from leveraging the knowledge of, and seeking collaboration with, other institutions with deeper micro and sectoral expertise on SSN issues. Such collaborations are likely to be more fruitful if these institutions have designed or already assessed SSN policies and reforms as part of their mandate (for example, World Bank’s Public Expenditure Reviews), although collaboration in new areas could be also sought (for example, mapping spending needs to financing options). Collaboration could be particularly useful in exploring and assessing complex data and data reliability issues (see previous discussion). Such collaborations should complement the support received through IMF functional departments and capacity development (CD) activities.¹⁴

B. Surveillance

Engagement on macro-critical SSN issues in the surveillance context should be driven by an integrated assessment of the potential impact on macroeconomic stability. An issue or policy would be considered critical to bilateral surveillance and warrant IMF engagement if it affects or has the potential to affect domestic (for example, growth, inflation, fiscal sustainability), external, or global stability.¹⁵ This assessment should be risk-based, and the depth and breadth of engagement need to balance the level of risk and macro-criticality with the urgency of the issues and internal resources available. Staff should also routinely assess whether economic and social developments, new events (for example, pandemics and disasters), and material changes to the SSN system (affecting adequacy, efficiency, and sustainability of the system) may raise new policy concerns that warrant engagement.

SSN analyses should not be limited to short-term considerations and may require a long-term approach. This would help take into account the long-term impact of SSN spending and reforms on, for example, macroeconomic performance, human capital formation, and income distribution. Certain structural developments (for example, population aging and labor market developments) may also require a long-term view about the effect on and the role of SSN programs.

Discussions of SSN issues should be framed in the context of existing MTFFs and rules. Existing and proposed SSN spending should be consistent with the annual budget, the MTFF, and fiscal sustain-ability rules. Implementation and operationalization of SSN policies and reforms may involve policy trade-offs and may call for adjustments within existing fiscal frameworks and rules to preserve fiscal sustainability or require revisiting how trade-offs are managed.

Examples of past engagements on SSN issues in surveillance cases can offer insights on the nature, modality, and extent of possible engagement and the role of collaboration with other institutions. The focus, breadth, and depth of IMF engagement on SSN issues have been adapted to country-specific circumstances, as shown by several recent country cases (Box 5).

C. IMF-Supported Programs

Engagement on macro-critical SSN issues in the context of IMF-supported programs should focus on the role of SSNs in achieving program goals. While the impact of SSN programs and reforms might extend beyond the duration of programs, specific SSN reforms can directly contribute to achieving the overall program objectives, and program documents should clearly establish such linkages. For example, improving efficiency may require administrative efforts over a long period of time (for example, social registries), but initial actions could also have immediate tangible effects. In some cases, SSN reforms (for example, expanding existing cash transfer programs) are needed to mitigate the adverse impact of needed macroeconomic adjustment on vulnerable households, and therefore instrumental in supporting program success and to maintaining reform momentum. More recently, the COVID-19 pandemic has helped reinforce the need for strong SSNs, which has translated into countries temporarily increasing SSN support (for example, Burkina Faso, Madagascar, and Mali) or permanently scaling up existing SSNs (for example, Ecuador 2020 Extended Fund Facility [IMF 2020b] and Senegal 2020 Policy Coordination Instrument and 2021 Stand-by Arrangement and Standby Credit Facility [IMF 2021f]) to better protect the vulnerable population during shocks.

Authorities’ ownership, country-specific circumstances, and local capacity are key considerations when including SSN reforms in a program context. The primary responsibility to define the objectives of the SSN and design reforms lies with the authorities, and their ownership is critical for the success of reform implementation. The formulation of a clear strategy to strengthen the SSN would reinforce ownership and place reforms on a politically sustainable path. Strong ownership would also facilitate the consideration of country-specific factors, including domestic social context and vulnerabilities, implementation capacity, and the political and historical setting. Hence, the identification of the vulnerable segments of the population and policy advice may vary across countries and programs.

Effective coordination with other multilateral institutions to leverage their technical knowledge is critical to the successful design of SSN reforms in IMF-supported programs. In addition to in-house analysis, staff can leverage the analysis and expertise of other international organizations providing policy advice, technical assistance, or financing for SSN reforms. This knowledge can be used to improve the design of conditionality, although the IMF remains responsible for establishing and monitoring compliance with program conditionality. However, while responsibility for the design of conditionality and for monitoring and assessing conditionality compliance cannot be delegated to other institutions, their input can be important in this process. Moreover, where key specific reform measures are required to secure donor disbursements, these should be clearly identified in staff reports. Collaboration with partners to develop plans to strengthen the SSN over time is especially relevant in the context of LICs and fragile and conflict-affected states where administrative capacity and fiscal space are usually very limited and take time to build up.

Conditionality on SSN reforms can be used in IMF-supported programs if reforms are critical to achieving program objectives or for monitoring program implementation. The establishment of program conditionality, including on SSN issues, is subject to standards set forth in the Guidelines on Conditionality.¹⁶ In general, and in the SSN area, conditionality can take the form of quantitative conditions as well as key policy milestones to introduce and implement reforms (that is, prior actions and structural benchmarks [SBs]), and these different types of conditionality can complement each other (for example, Ecuador 2020 Extended Fund Facility [IMF 2020b] and Madagascar 2021 Extended Credit Facility [IMF 2022g]). While quantitative conditions are not typically set on SSN spending directly, SSN spending targets are often embedded in other spending targets (for example, on overall social spending). Quantitative conditions on, for example, expanding the coverage of specific SSN programs, are also often used. When designing conditionality, assessing capacity constraints and ability to timely monitoring data becomes vital. Specifically,

• Quantitative conditionality, such as performance criteria (PCs) and indicative targets (ITs), are often set on general social spending that contains selected SSN expenditure.¹⁷ PCs and ITs are typically set to ensure spending adequacy (for example, in the form of spending floors) or to track spending efficiency. PCs are used for clearly specified variables or measures that can be objectively monitored by the staff and are critical for the achievement of program goals. ITs are used if variables of interest cannot be established as PCs because of substantial uncertainty about economic trends. The coverage of SSN spending under such targets can vary to reflect country- and program-specific priorities and the need for timely and reliable data availability for monitoring purposes. A broad coverage of SSN spending would be appropriate where protecting all budgetary resources associated with the SSN is critical in achieving program objectives. At times, it may be more effective to narrowly focus the coverage of SSN spending on selected SSN schemes, to protect or expand key SSN programs during shocks, or to focus reform efforts on the best-performing programs during the program period (for example, Ecuador 2020 Extended Fund Facility [IMF 2020b] and Pakistan 2019 Extended Fund Facility [IMF 2019d]). Using PCs should be avoided if there are concerns about data quality. If a country cannot effectively monitor social spending and hence a quantitative condition (IT or PC) cannot be established, the program documents are expected to explain why and include capacity development measures to enhance data quality and timeliness.

• SBs can be set for key milestones in implementing SSN reforms critical to achieving program objectives. Examples of SBs include development of a strategy for strengthening the SSN, introducing new SSN programs, expanding the coverage of existing SSN schemes (for example, Ecuador 2020 Extended Fund Facility [IMF 2020b], Madagascar 2021 Extended Credit Facility [IMF 2022g], and Mauritania 2021 Extended CreditFacility [IMF 2017a]), and developing social registries and centralized information systems to improve SSN management and monitoring (for example, Costa Rica 2021 Extended Fund Facility [IMF 2022h] and Senegal 2020 Policy Coordination Instrument and 2021 Stand-by Arrangement and Standby Credit Facility [IMF 2021f]). Where such actions require increases in SSN spending, these spending increases could be incorporated in ITs. SSN reforms can also be specified as prior actions when their upfront implementation is critical for the successful implementation of the program. The adoption of SBs is guided by the general principles of conditionality, such as parsimony, criticality of meeting program objectives, or monitoring the program’s implementation. SSN measures that are not critical in this sense, but that the authorities wish to highlight, can be established as commitments in the Letter of Intent and Memorandum of Economic and Financial Policies with clear implementation timelines. At times, correct sequencing may require conditionality in other areas, for example, if implementing SSN reforms requires first strengthening PFM capacity (Senegal 2020 Policy Coordination Instrument and 2021 Stand-by Arrangement and Standby Credit Facility [IMF 2021f]).

In recent years, SSN reforms have gained increased emphasis in IMF-supported programs as measures to support inclusive growth and protect the vulnerable during economic adjustment, often in collaboration with development partners. This emphasis has translated into SSN-related program commitments increasingly supported by quantitative conditionality on, for example, social spending and SSN reforms. The increased use of conditionality has occurred both in Poverty Reduction and Growth Trust–supported programs for LICs, which are intended to reduce poverty and protect the vulnerable, and in General Resources Account–supported programs. During 2017–20, about 90 percent of Poverty Reduction and Growth Trust–supported programs included quantitative social spending conditionality (up from about 65 percent in 2012–14), and the percentage of General Resources Account–supported programs with such conditionality has almost doubled over the last 10 years to 45 percent over 2017–20 (up from 20 percent over 2012–14). Several recent programs have introduced SSN conditionality to support the implementation of key reforms and address the economic hardship created by the COVID-19 pandemic (Box 6). Collaboration with development partners in this area has been key both in the design of reforms and to support the authorities in advancing reforms associated with IMF-program conditionality.

D. Dialogue with Country Authorities

This section discusses considerations that country teams may find useful in their communication with country authorities in the context of SSN spending. The focus is specifically on communication of analytical results and policy advice based on the authorities’ underlying policy objectives. The relative emphasis placed on any specific issue will, of course, depend on country-specific circumstances regarding macroeconomic conditions, political economy context, and SSN spending pressures. In communicating with authorities, staff should consider that SSN reforms and discussions may involve different institutional stakeholders. With regard to communication to the public, ultimately it is the authorities who have the most detailed knowledge of local conditions and who should decide their preferred communication strategies.

Communication of policy advice should be clearly embedded within the macrofiscal context of the country. The following discussion provides examples of how to communicate policy advice drawing on specific instances of IMF analytical work and country-level engagement on SSN issues. A key feature of such communication is that country teams typically engage on SSN issues from some combination of the three macro-critical perspectives: fiscal sustainability, spending adequacy, and spending efficiency. Moreover, it is important that advice explicitly recognizes the nature of tradeoffs that are encountered in different country contexts and a recognition that the appropriate choice of reforms will reflect government preferences and constraints.

Policy advice should be presented in a manner that helps the authorities develop their own communication efforts. Communication should therefore focus on the underlying motivations for the policy reform and its benefits. In the context of SSN reform, these often focus on strengthening the SSN to reduce poverty and protect lower-income households from potentially ill-designed reforms or from the unintended consequences of reforms needed to promote inclusive growth or macroeconomic stability (such as energy subsidy reform, consumption tax reforms, and labor market reforms). Since SSN reforms can help to build political support for these other reforms, it is therefore important that both sets of reforms are communicated as a package. To facilitate government communication efforts, it is important that staff present the case for reform in both technical terms and using arguments which the government itself can incorporate into its dialogue with stakeholders and, through the media, to the public.

Where SSN reforms are motivated by the need to improve targeting efficiency to reduce leakage to higher-income households and avoid errors of exclusion, it is important to communicate the benefits of such reforms. When formulating communication strategies around SSN reforms, it is important to emphasize the need to focus not only on spending levels (adequacy) but also on spending better (efficiency). Improvements in targeting efficiency to reduce leakage to the nonpoor can lead to improvements in benefit levels for other beneficiaries and in coverage of the poor and most vulnerable. Improvements in targeting efficiency can also lead to additional fiscal space which can be used to address spending needs in other critical areas and reduce high tax rates where these are deemed excessive. Enhancing the progressivity of financing (for example, through increasing progressive income taxes or reducing regressive tax expenditures) can also help strengthen overall targeting efficiency. The presentation of policy recommendations, and the findings of supporting technical analysis, should therefore support such communication.

Where SSN reform is motivated by the need to address fiscal pressures, communication of reforms needs to be explained in terms of trade-offs within the constraints of government’s financing capacity. For example, in the context of the need for fiscal consolidation, communication could emphasize that reforms are focused on reducing leakage of benefits to higher-income households while also addressing any existing gaps for protecting more vulnerable households. For instance, this is often achieved through increasing the use of means testing in place of universal categorical transfers. Communication can also emphasize that such reforms also help to protect other priority spending during periods of fiscal consolidation, such as education and health spending. This communication helps to clarify the opportunity cost of “no policy reforms.” Box 7 presents some selected examples of communicating policy advice to country authorities in different contexts.