Evidence Base for the Costs of Poverty Targeting

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Evidence Base for the Costs of Poverty Targeting

There has been a gradual accretion of evidence on the costs of poverty targeting. There is an increasingly firm body of knowledge on labor disincentives in the impact evaluation literature. There is much less in quantity and rigor on the other topics because the main data sources are process evaluations, which tend to be buried in the archives of program documents rather than the stuff of journal articles, but the available evidence is fairly consistent.

Labor Disincentives

Theory and intuition supports the notion that targeting that reduces benefits as a household’s or individual’s earnings rise could decrease work effort. In richer countries with programs that tend to use means testing, benefit differentiation, and sometimes offer significant levels of benefits, incentive issues are a noticeable feature of concern in the literature and policy debates. This is especially the case where families may be eligible for multiple programs, each with its own means test or sliding scale of benefits. Moffitt (2015) compiles evidence on the largest programs in the United States. The marginal tax rates across individual programs vary and also across income levels. For example, the Supplemental Nutrition Assistance Program (commonly known as food stamps) has a nominal 30 percent marginal tax rate, but it is effectively 24 percent because of earnings exclusion provisions. The Earned Income Tax Credit generates a marginal tax rate as high as −45 percent at the bottom of the scale, but it is 21 percent in the phaseout range. Cumulative marginal tax rates for families in the Supplemental Nutrition Assistance Program and facing federal and state income and payroll taxes, which implicitly include the Earned Income Tax Credit and child tax credits, show a range depending on family composition, earnings, number of workers, and so forth. For families with earnings below 50 percent of the poverty line, the marginal tax rate varies from −3 to 35 percent, with a median of 13 percent. For families with earnings between 150 and 200 percent of the poverty line, the marginal tax rates range from 22 to 51 percent, with a mean of 31 percent. The empirical evidence on impacts on work effort shows no significant effects overall but some for single-mother households.

So far in developing countries, few programs have a combination of features that would trigger a high level of concern about work effects and/or there are countervailing features at work in labor decisions. Many programs do not determine eligibility based only or principally on current earnings. Few adjust benefits at all as income rises, and those that do tend to do so with one or two steps or with earnings disregards. Few programs

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reassess eligibility frequently. Many programs pay such low benefits that households that are capable of work effort have plenty of incentive to work to increase their incomes. Moreover, the evaluation evidence shows that transfers can release constraints to work. For example, by paying regularly, the programs may help households buy inputs they need for their farms or microenterprises and thus make work more productive, or they may make it easier for households to afford the resources needed for job search.

Indeed, a body of evidence built over the past decade around work incentives shows that the concern is overblown with respect to social assistance in developing countries. For example, in Bastagli et al.’s (2016) review of 74 studies on cash transfers, for just over half of the studies reporting on adult work, the cash transfer does not have a statistically significant impact. Among the studies reporting a significant effect among working-age adults, the majority find an increase in work participation and intensity. In the cases where a reduction in work participation or work intensity is reported, it reflects a reduction in participation among the elderly or those caring for dependents or is linked to reductions in casual work. Banerjee et al. (2017) analyze data from randomized controlled trials of cash transfer programs in six developing countries and find no systematic evidence that the programs discourage work. Baird, McKenzie, and Özler (2018) provide a narrative review of the extensive literature and find that prime-age adults show very little change in the amount they work or the amount they earn when receiving unconditional cash transfers, conditional cash transfers, or charitable grants. Transfers that enable people to find jobs in different places and to start new businesses have resulted in more labor and higher income for the recipients.

Although it is more nascent, the behavioral economics literature suggests various ways in which social assistance may improve work effort or its fruits. There is fairly conclusive evidence that financial concerns can reduce mental bandwidth and thereby cognitive capacity and executive control, with implications for risk taking and decision making, and that these affect the poorer more than the less poor (Schilbach, Schofield, and Mullainathan 2016). If the causality runs in the opposite direction as well, that a bit more money via a transfer can unlock bandwidth, then transfers may raise productivity. The evidence on these effects is still nascent. In an experimental study in India, Kaur et al. (2018) vary the timing of payments to workers doing piece-rate work. Those who received their pay early, and thus were less pressed about money, increased their hourly output and had fewer attentional errors. In a possibly proximate chain from transfers to psychosocial welfare to behavior, Attah et al. (2016) show that cash transfers in four African countries had positive impacts on psychosocial well-being, which led to further positive impacts on educational performance, participation in social life, and empowerment for decision making. In Pakistan,

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Kosec and Mo (2017) study the effects of extremely heavy rainfall and widespread flooding during the 2010 monsoon. They conclude that social protection not only restored livelihoods and replaced damaged assets, but also had an enduring effect by easing mental burdens and raising aspirations for the future.

Administrative Costs

An often cited argument against differentiating eligibility or benefits by welfare is that household-specific eligibility assessments require prohibitively higher administrative costs than programs that differentiate eligibility by characteristics that are simpler to observe, such as age or place of residence. Besley and Kanbur (1990) posit that the marginal costs of eligibility determination become prohibitive if a program strives to achieve close-toperfect targeting.

This hypothesis is largely refuted by the available cost data. In most cases, administrative costs represent a small portion of the total program budget, even for programs that differentiate eligibility or benefits by welfare level. The administrative costs associated with eligibility determination methods are a subset of that low total. This pattern is also observed for the cost of social registries relative to the social assistance programs they serve.

Calculating and comparing administrative costs is a bit tricky and thus requires some definitions. The administrative costs of a social assistance program include all the expenditures needed to design and implement the program—all the costs over and above the cost of the transfers but not including services that may also be provided (counseling, coaching, and training). Administrative costs are incurred by all social assistance programs, be they narrowly targeted or not. Such costs include the costs of planning and information systems, mechanisms for payments, grievance redress, audits, monitoring and evaluation, and so forth. In addition, narrowly targeted programs would incur other (somewhat higher) costs associated with eligibility determination and recertification. These are the marginal administrative costs associated with narrow targeting, which drive Besley and Kanbur’s (1990) theoretical argument.

There is scant information on the level of administrative costs of social assistance programs in low- and middle-income countries because it is quite difficult to collect. Some of these costs are incurred primarily at the central level, others in frontline units, and others by third-party agencies (for example, payments). To get a comprehensive estimate of a program’s administrative costs, the program administration or cost expert should collect all these elements from all the cost centers. Often, some of the program resources—such as staff or other operational systems—are shared across multiple programs; in these cases, the costs must be assigned to or shared

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among the specific programs using different allocation keys. Moreover, depending on the maturity of the program, the level of administrative costs may decrease over time, as the fixed costs of design, investments in information systems, and monitoring and evaluation are spread over a larger caseload and years in service.23 All these factors make the careful estimation of administrative costs a complex exercise, which is infrequently done for a subset of programs or even social registries (which usually support multiple programs). Therefore, this subsection relies on partial information that must be interpreted carefully.

Information on the composition of these administrative costs, including the marginal costs associated with narrower targeting, is rarer still. All programs, whether welfare targeted or not, incur expenditures to identify beneficiaries or transfer payments. For example, a child allowance for all children requires registering them in the information system, including information on the responsible adult with identity information, contact information, payment information, and so forth. For a welfare-targeted program, the marginal cost of targeting would be related to the information needed to measure, estimate, or rank the welfare of households (in community-based targeting, proxy means test, hybrid means test or means-tested programs) and update that periodically if needed. Thus, administrative costs per client may be higher for narrowly targeted programs, but overall costs may not. Figure 2.14 shows how the costs of a poverty-targeted child allowance might look versus a universal child allowance.

Three statistics are often used to report on the level of administrative costs, including the subset of costs associated with narrower targeting, across programs and countries: the cost per beneficiary served, the share of administrative costs in total program costs, and the cost-transfer ratio. The cost-transfer ratio measures the cost of making a one-unit transfer to a beneficiary. However, interpreting these statistics is not without problems. The cost per beneficiary needs to be converted from local currency into US dollars or another internationally used currency and will depend on the type of exchange rate used (official or based on purchasing power parity and for some countries, unofficial). The share of administrative costs in total program costs (cost of transfers plus administrative costs) and the cost-transfer ratio (a linear transformation of the former) are probably the simplest ways to look at these costs across programs. However, they are influenced by various program design parameters, such as the size (coverage) of the program, its maturity (pilot versus atscale), the size of the transfer, the type of targeting method or methods used, the frequency of recertification, the feasibility and use of program data interoperability, the type of payment mechanism, and so forth. A program with a more generous benefit would score a smaller cost-transfer

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Figure 2.14 Costs of Targeted versus Universal Child Allowance

Targeting costs

Other administrative costs D

C

B E

F

G I

J

Benefits

Poor children

All children

Source: Tesliuc et al. 2014

A H K

ratio or share of administrative costs indicator, all else remaining equal. (See Caldes, Coady, and Maluccio [2006] or Tesliuc et al. [2014] for more on these points.)

Empirical studies have found that the administrative costs associated with targeted programs represent a small share of total program costs. The few empirical studies on administrative costs suggest that most well-run social assistance programs operate with a modest share of administrative costs in the total program budget. Grosh et al. (2008) report a share of administrative costs averaging 5 to 10 percent for public works and cash transfer programs (conditional or not) and 22 percent for in-kind programs (across 55 social assistance programs). Tesliuc et al. (2014) report a range from 2 to 10 percent for a last-resort cash transfer program in the Europe and Central Asia region.24 Schnitzer and Stoeffler (2020) similarly report a low share of administrative costs in total program costs of 0.4 to 5.5 percent for programs in Burkina Faso, Chad, and Niger, depending on the approach used by the administrators.25 Rosas, Zaldivar, and Pinzon-Caicedo (2016) report a cost of 7.7 percent during the first phase of implementation of the Tanzania Productive Safety Net Program. Jamaica’s Advancement Through Health and Education program registered a slightly higher share of administrative costs of about 11 percent for 2018, which includes, in addition to the delivery of conditional cash transfers, case management services and the cost of associated social workers (World Bank 2019).

The costs of social registries, which are used by multiple programs per country to determine eligibility, are also small compared with total program costs. A significant number of developing countries have established social registries to collect information, in office or in the field, to establish eligibility for social programs. Their costs become the new pertinent way to

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measure the administrative costs of targeting in many settings. A literature review of the costs of large-scale social registries in middle-income countries, which support multiple targeted programs, found that these costs range between US$1 and US$3 per household in most countries, or less than 2 percent of the value of benefits channeled through the targeting system. More specifically, the cost per registered household was US$1.4 dollars in Pakistan; around US$2.5 in Bangladesh, Indonesia, and the Philippines (Packard et al. 2019); US$1.3 in Turkey; US$1.27 in Colombia for System for the Selection of Beneficiaries for Social Programs (SISBEN) IV; US$2.25–US$2.50 in Colombia for SISBEN I, II, and III (Departamento Nacional de Planeación database; Leite et al. 2017); and US$2.06 in Brazil for the Cadastro Único 7 until 2013 (Leite et al. 2017). Castaneda and Lindert (2005) report different statistics for the share of the program budgets that were targeted through the social registry: Brazil, 1.4 percent; Chile, 1.3 percent; Colombia, 0.9 percent, Costa Rica, 0.5 percent; and Mexico, 0.7 percent. Hanna and Olken (2018) cite values of 0.8 and 1.7 percent for total transfer costs going to the costs of the social registries in Indonesia and Peru, respectively. Lindert et al. (2018) show that for Malawi’s National Social Support Programme Phase 2, the cost was US$1.74 per household. A recent review of the costs of 10 social registries26 confirms that the administrative costs associated with finer targeting are low, within 1 to 3 percent of the value of the annual transfers (figure 2.15 reports the cost-transfer ratios for the social registries). These costs are in the same range as those reported in other reviews, based on overlapping country coverage (see Devereux et al. 2017; Kidd, Athias, and Mohamud 2021).

Not surprisingly, unit costs are higher for social registries in low-income countries that are in an incipient or partial rollout phase,27 but they continue to remain small compared with the value of the transfers. For example, the cost-transfer ratios of the incipient social registries established in the Republic of Congo and Mali,28 at 7 and 8 percent (figure 2.15), are higher than the cost-transfer ratios for social registries that have achieved national scale. The Republic of Congo and Mali have established registries in an environment of paucity of other administrative data sources (which could have reduced the cost of data collection and verification) and are only in the initial phase of their expansion (not yet benefiting from the economies of scale of a social registry with larger coverage) (see also annex 2D).

Increasingly, programs or social registries collect less information directly from the beneficiaries, while using more information from other administrative databases through interoperability and cross-matching with other databases held by the government, such as income tax, social security contributions, registration of land or automobiles, passports and payments to government-operated utilities, and so forth. In such cases, the costs of

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Figure 2.15 Ratio of the Unit Cost of a Social Registry versus the Annual Benefit of the Largest Program Served

10%

9%

8%

7%

6%

5%

4%

3%

2%

1%

0% at scale

Brazil, 2020 Chile, 2017 Colombia, 2017–20 Jordan, 2020 Malawi, 2018 Pakistan, 2016–21 Philippines, 2019–21 Senegal, 2019–23

Source: Original compilation for this publication based on Annex 2D.

Tunisia, 2016–20 incipient

Congo, Rep., 2017–19 Mali, 2017–20

running those other databases, whose main functions are in their home ministries, are not considered part of the administrative costs of the social assistance program. However, it may take some investment on the part of the social registry to be able to use such data, and it may increase the frequency of updates so that when the overall costs associated with interoperability are included in the social registry costs, there is an increase in both administrative cost and the efficiency or productivity of the system.

For example, in Turkey, the estimated development cost of the Integrated Social Assistance System (ISAS) was US$13.1 million and it was built between 2010 and 2015, reaching about 40 percent of the population in 2015.29 Over 2010–15, ISAS served 43 million people with a unit cost over five years of US$0.3. The investment in ISAS allowed the rationalization of social assistance benefits, by identifying duplications of about 10 percent. Making processes electronic also saved costs by reducing paper and staff time; the government now processes approximately 2.3 million fewer documents per month. In addition to this, processing time has been significantly reduced. For example, the time from application to decision for

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regular social assistance programs has been reduced by approximately 20 percent, and the time from application to disbursement to beneficiaries of the disability and old-age pension programs provided under Law No. 2022 dropped from 1.5 years to one month.30

In Brazil, since 2016, Cadastro Único communicates with 10 other information systems to verify inconsistencies between the declared income and the individual information available in the other information systems. As a result, Brazil can regularly update its caseload of beneficiaries and save millions of dollars in fraud. For example, in 2019,31 it was estimated that the Brazilian government had removed about 1.3 million people from the Bolsa Familia program, generating savings of about R$1.4 billion (US$350 million in 2019) due to the interoperability and cross-verification process. The increase in complexity and functionalities has pushed the average cost per household to US$6.7, compared with US$2.0 during 2010–13; however, in relative terms, the cost of Cadastro Único represents only about 1 percent of the annual transfer cost of the Bolsa Familia program (and is used for eligibility determination in a score of other programs).

Over the next three to four years, Colombia is expected to invest significantly in improving the interoperability and dynamism of SISBEN, increasing the unit cost of application from US$2.25–US$2.50 to about US$6, matching the unit costs in Brazil and Chile after their investment in interoperability was completed.

Administrative costs can be viewed as the investment needed to produce good outcomes (for example, to improve delivery systems; see chapter 4), and there is evidence that a somewhat higher share of “marginal targeting costs” in expenditures can improve targeting accuracy. Tesliuc et al. (2014) generate one of the more thorough cross-country comparisons of administrative costs in total and by their various functions. They find a strong correlation between the cost-transfer ratio of last resort income support programs in Europe and Central Asia and the share of benefits reaching the poorest quintile (figure 2.16). There is a range of optimal investment in program administration: lower spending would result in large errors and hence diminished cost-efficiency and effectiveness, and after a certain point, higher administrative costs indicate waste. Programs should finance enough of these costs, especially when they are the critical factor determining the effectiveness/efficiency of the cash or in-kind transfers.

The administrative effort and political will put into developing povertytargeting and/or social registry systems has been substantial, but the choices made and scale have kept the unit costs low relative to the benefits channeled. In general, social protection delivery systems in developing countries could benefit from more investment in administrative functions. The experience has been that offices are few and often far from beneficiaries, with underdeveloped information systems or too few staff, and with

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Figure 2.16 Share of Program Benefits Reaching the Poorest Quintile and the Cost-Transfer Ratio

90

Share of benefits reaching the poorest quintile

85

80

75

70

65 Lithuania, 2006

60

55 Armenia, 2006

50 Romania, 2005 Bulgaria, 2004

45 0.00 Kyrgyz Republic, 2006 Albania, 2005

0.01 0.02 0.03 0.04 0.05

Cost transfer ratio (CTR) Targeting performance Linear (targeting performance)

Source: Tesliuc et al. 2014

0.06

inadequate abilities to do outreach to the intended population or address grievances. Similarly, their “virtual portal” systems may be underdeveloped and suboptimally user-friendly (see chapter 4; Lindert et al. 2020). Scrimping on administration of social protection delivery systems may just shift costs to clients, raising their transaction costs and contributing to stigma, and increase the level of errors in the program. Given that transfer costs often account for 90 to 95 percent of total program costs, it would seem that programs should err on the side of further investment in delivery systems instead of scrimping to lower administrative costs. Both transaction costs and stigma are issues that can be reduced with good human-centered design, keeping an eye on client experience, investing in administrative systems that facilitate easy access, and so forth. It is likely that technology can help keep administrative costs manageable, as new ways of identifying and paying beneficiaries are developed and operational systems become less fragmented and are shared across different programs.

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Transaction Costs

Transaction costs of various forms can reduce the value of participating in programs and sometimes exclude people altogether. Finding out about a program, filling out forms, supplying proof of identity and other required documents, being interviewed, and following up can all take time, may require bus fares or fees for obtaining documents, and so forth. The problem is intuitive to understand, and a few studies show that for at least some members of the target population, the barriers can be significant. Daigneault, Jacob, and Tereraho (2012) find that basic information and the characteristics of the claiming process are the two most commonly cited factors in their study of take-up of benefits in a few Organisation for Economic Co-operation and Development (OECD) countries. Delaney and Jehoma (2016) find that about 18 percent of income-eligible children do not receive the South African Child Support Grant for such reasons, although the problem is not restricted to targeted programs. ILO (2014) shows that participation in Namibia’s “universal” (age- but not poverty-targeted) social pension is about 92 percent of those over age 60 years. Thinkthrough (2021) documents that the transaction costs for Nepal’s universal child allowance are a barrier to participation, especially for households in remote areas who must travel to reach pertinent administrative services, compounded by the incomplete coverage of birth registration, the program’s relatively complex administrative procedures, and the relatively low value of the transfer.

Although there is still far to go, there is a great deal of know-how and many examples of its utilization to show that social assistance programs could effectively tackle issues of transaction costs, which are discussed in more depth in chapter 4. An increasing number of countries are working to ensure that residents or citizens have identity documents, which is a common stumbling block, with almost every country in Africa and Asia having introduced an electronic identification (eID) or intending to do so in the near future. Social registries to serve multiple programs are being built in many countries (Leite et al. 2017). The increasing use of digital payment systems, especially those that allow multiple options of service providers, is reducing the transaction costs of collecting benefits, which is important, as it is a recurrent rather than one-off transaction. In addition to developing these basic systems, many countries have initiatives for “active outreach” as part of their social protection activities. In Brazil, for example, an active outreach strategy for the social registry was initiated in 2011 with the tagline “Conhecer para Incluir” (to know so as to include). The outreach effort was intense until 2014 and included media outreach and door-to-door efforts in target areas from slums to jungles. About 1.5 million new families were added to the national social registry, which is

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used for 30 poverty-targeted programs, principal among them the Bolsa Familia conditional cash transfer program. Of the families added, over a million were traditional groups (indigenous, quilombolas [residents of Afro-Brazilian communities], or riverine populations) that are highly vulnerable and often underserved.

Social Costs

Programs that differentiate eligibility by welfare may lead to jealousies or ill-will in a community between recipients and nonrecipients. The qualitative research that it takes to detect such effects is not as common as the more quantitative impact evaluations. Qualitative studies are often tied to the early phases of program implementation when the idea of the program is new in the researched communities and the implementation bugs have not yet been ironed out. For example, Della Guardia, Lake, and Schnitzer (forthcoming) investigated the effects of Chad’s pilot cash program, which was initiated in 2016, geographically targeted to the poorest rural areas, with caseloads allocated so that about 40 percent of the people in each included village would benefit, and a proxy means test to select them. The program increased the participants’ consumption and investment (Kandpal, Schnitzer, and Daye 2020). There were positive local spillover effects— some recipients shared their transfers directly with family or neighbors, some helped create community infrastructure, and there was a positive effect on local small businesses and the market for day labor as the beneficiaries spent their transfers and invested in their household enterprises. But there were jealousies as well, and recipients reported that nonrecipients were sometimes rude, jealous, or angry, and sometimes they took actions that were economically punitive, for example, charging higher prices in local commerce, refusing to give full change in transactions, or refusing to repay credit. This level of backlash is more marked than in some other reports, which include some friction, gossip, and repercussions for community labor that is not directly associated with the program but not economic retaliation per se.

Jones, Vargas, and Villar (2007) conducted field work in the early days of Peru’s Juntos conditional cash transfer program, which geographically targets rural villages with beneficiaries selected through a proxy means test and a final community validation phase. The program has a record of positive impact evaluations along the usual dimensions for quantitative impact evaluations of conditional cash transfer programs, such as increased consumption; increased school enrollment, attendance, and grade progression; increased use of health care; and mildly better nutrition outcomes (Jaramillo and Sánchez 2011; Perova and Vakis 2009; Perova and Vakis 2012). But in their qualitative field work, Jones, Vargas, and Villar (2007) found some

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issues of jealousies, including nonrecipient families who were jealous that children in recipient families had better school uniforms and shoes; that nonrecipient youth were more reluctant to contribute to school chores, saying the recipient youth should do them; and that some mothers felt cohesion in community activities had lessened.

There are similar accounts from the outset of Lesotho’s Child Grant Programme (OPM 2014) and Mexico’s PROGRESA program (Adato 2000). The resentments in all cases were in village settings where people knew each other; these feelings may not carry through so much to more urban settings (where an increasing share of the world lives and the new wave of social assistance programs in Africa are located). But they are tied up in the issues inherent in targeting; that is, the rationing of spots in a program in which people want to participate and the difficulty of drawing clear distinctions among the more and less needy in fairly homogeneous poor places.

Stigma is somewhat the inverse of jealousy, and it can be thought of as the psychic version of transaction costs and may be tied up in some of the same processes. Program recipients may have to identify themselves publicly or semipublicly as in need of help. This may entail queuing at social service assistance centers or payment collection points; having their name on a list of aid recipients posted as part of transparency initiatives; or being cross-questioned on income and expenditures, work, school attendance, or other behaviors. These experiences can feel demeaning and all the more so if the public who might witness, or particularly the staff involved in program administration, convey through word or gesture negative judgments about the program claimants. These may be putative behaviors (they are lazy, dirty, cheat, and so forth) or group identities they may hold (educational background, ethnicity, religion, native language, or migration status). Full-scale research in this area is relatively rare, although the problem seems to be common. Baumberg (2016) gives an overview for the UK, Yang et al. (2019) provide a literature review around child benefits, and Gubrium and Pellissery (2016) review a cross-section of programs. In OECD countries, Daigneault, Jacob, and Tereraho (2012) find that stigma is the sixth most common reason for non-take-up of benefits, cited in 22 percent of the studies reviewed. Wright et al. (2015) find that in 26 of 30 focus groups in their research on the dignity of claimants of South Africa’s Child Grant, claimants found issues in which the application process affected their dignity, including long queues, having to negotiate the application process, and being treated disrespectfully by government officials.

The issues of stigma and shame are intertwined, but they are not identical. Shame can come from poverty itself and the way it can constrain selfesteem or the ability to engage in social roles. Some people report that the

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recognition of their needs in the social assistance program is in itself an affirmation and alleviates rather than induces shame (see Gubrium and Pellissery 2016; Roelen 2017; Yang et al. 2019). Granlund and Hochfeld (2020) show that South Africa’s Child Grant has largely positive effects on the dignity and autonomy of the caregiver recipients. A growing body of impact evaluations shows how receipt of social assistance can improve psychosocial well-being, including through allowing participants to become more engaged in social networks (for example, Attah et al. [2016] provides a review of cash transfers in five African countries). The additional resources from the transfer benefits may reduce shame, although the process of claiming the benefits may be more or less stigmatizing, depending on administrative processes, program design, and context (see Roelen [2020] for a review of the interaction).

The connotations and framing of a program can seemingly influence how people feel about it. In the United States, for example, Pell Grants are means-tested federal aid for the costs of college. They are generally not viewed as stigmatizing, presumably because the very act of going to college is a triumph and a step on a journey that is likely to lead to a good job. The thresholds for Pell Grants are set high, so they are better thought of as affluence tested than poverty targeted. Many countries try to associate their programs with positive messages through their names. For example, Mexico’s cash transfer program was first called PROGRESA, an acronym for Progressing through Education and Health, then Oportunidades (opportunities), and then Prospera (prosper). Indonesia’s conditional cash transfer program is called PKH (the Family Hope Program), Peru’s is Juntos (Together), and Jamaica’s PATH stands for Program of Advancement Through Health and Education. Mali’s program is called Jigisemejiri (Tree of Hope), and the Philippines’ 4Ps is the Bridging Program for the Filipino Family.

The issues of exclusion caused by transaction costs and stigma are partly the result of delivery systems that are insufficiently developed and/or inattentive to clients’ needs. As shown in chapter 4, there is much that can be done to ameliorate these problems if there is political will and sufficient funding for administrative costs. In addition to all the good that can be done through making transactions in social assistance service centers convenient and nontraumatizing, the move to digital may also help to reduce stigma. The more transactions are private, the fewer will be the occasions in which people will be treated badly, especially in front of their community. For example, the move to payment via debit cards has been welcomed by beneficiaries of programs such as the US food stamp program and Brazil’s Bolsa Familia cash transfer, because their cards made them look like betteroff consumers with a regular bank debit or credit card (Oliveira et al. 2018).