Revisiting Targeting in Social Assistance

Page 99

Targeting within Universal Social Protection | 63

Social protection is not the only sector with high-priority needs. Gaspar et al. (2019) calculate that to cover the costs of the Sustainable Development Goals related to health, education, electricity, roads, water, and sanitation (but not including social protection) would take on average about 4 percentage points of GDP in emerging markets, but 15 percentage points of GDP in low-income countries. They consider that increasing the tax-toGDP ratio by 5 percentage points of GDP in the next decade is an ambitious but reasonable target in many developing countries, leaving a large gap between plausible resources and high-priority needs. This suggests that there will be fierce competition for resources among high-priority expenditures and thus highlights the importance of the political economy that shapes those decisions. The battle for fiscal space is not easy. It is rarely easy to raise taxes, and there are pressing needs for many good purposes. Thus, the question of whether to target to conserve resources or to raise more revenue to allow broader social protection programs is perennial.

Essay 9: Does Universality Increase Budgets and Thus Reduce the Need for Prioritizing the Needy? In the discourse on the political economy of budgets, taxes, and targeting, “more for the poor is less for the poor” has become something of a mantra. An important source of support for the idea is the median voter theory, which postulates that voters will vote for programs that benefit them directly. Thus, a program for a minority such as “the poor” will garner little political support, while one that extends benefits to the middle class or universally will garner enough votes to have much larger budgets. The analytical underpinnings of the argument have been developed by serious scholars (Gelbach and Pritchett 1997; Meltzer and Richard 1981). Several country-specific explorations of some aspects of the theory support it. Jacques and Noel (2018) provide one of the supportive cross-country findings for OECD countries. Taylor-Gooby’s (2005) study is an example of the single-country literature. Looking at public opinion in the United Kingdom, he finds that there is broader support for the universal National Health System than for targeted social schemes. The argument has gained currency among institutions that advocate for social protection, such as the International Labour Organization, the United Nations Children’s Fund, HelpAge International, the Global Coalition for Social Protection Floors, and Development Pathways. The idea seems to be so widely accepted that this chapter does not include a full literature review of support (see UNICEF–ODI 2020).


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7.5 Performance Triangle for Two Programs

6min
pages 527-529

7.9 Relative Efficiency of Programs

1min
page 517

Concluding Remarks

1min
page 530

7.13 Exclusion and Inclusion Errors

1min
page 525

the Poverty Line

1min
page 516

7.12 Impacts on Poverty and Inequality

2min
page 524

7.3 Inclusion and Exclusion Errors in a 10-Person Economy

4min
pages 510-511

7.4 Targeting Differential

2min
page 512

What to Look for When Conducting Method Assessments

1min
page 509

7.1 Social Program Coverage in Brazil

1min
page 507

Illustrative Case Study on How to Avoid Spurious Interpretations

2min
page 504

Introduction

1min
page 503

References

18min
pages 492-502

Notes

21min
pages 483-491

B6.11.2 Household Consumption, Assets, and Land Access in PSNP Woredas, by PSNP Beneficiary Status, 2008

21min
pages 471-480

Conclusion

4min
pages 481-482

B6.11.1 Criteria for Selecting Beneficiary Households

1min
page 470

Community-Based Targeting

2min
page 469

Key Elements for Community-Based Targeting

4min
pages 467-468

6.10 Machine Learning, Big Data, and Human Rights

6min
pages 464-466

PMT, Machine Learning, and Big Data: What Do We Know?

4min
pages 447-448

Poor Households in Togo

5min
pages 458-460

Formulae

8min
pages 440-443

Its Drivers

1min
page 457

B6.6.1 Distribution of Winners and Losers, by Demographic Group

11min
pages 435-439

6.8 Machine Learning Models That Are Commonly Used

15min
pages 449-455

B6.6.1 Timeline of Key Developments in Georgia’s Targeted Social Assistance Program

1min
page 434

Causal Effect One

25min
pages 418-428

Updating the PMT Formula: The 2013–15 Reform of the Georgia Targeted Social Assistance Program

2min
page 433

6.3 Illustration of PMT Weights for Selected Variables

8min
pages 429-432

Key Elements for PMT Methods: Traditional Models, Processes, and Machine Learning

4min
pages 416-417

B6.4.1 Summary of the Availability and Quality of Administrative Data in Tunisia, 2019

1min
page 415

Hybrid Means Testing Targeting System: The Case of Tunisia

1min
page 414

6.2 Romania: Asset-to-Income Conversion Coefficients

5min
pages 409-411

and Proxy Means Testing Models in Algeria

4min
pages 412-413

6.1 Albania: Imputation of Farm Income

2min
page 408

Key Elements for Hybrid Means Testing

1min
page 403

6.2 Income Test under the Hybrid Means Testing Approach

5min
pages 405-407

6.2 Treatment of Assets in Means-Tested Programs

20min
pages 394-402

Key Elements for Means Tests

6min
pages 391-393

Geographic Targeting: Big Data Are Revolutionizing Poverty Mapping

2min
page 385

6.1 Example of Classification of Developed Area

9min
pages 386-390

6.1 Examples of Big Data

13min
pages 379-384

Some Starting Considerations about Data—Traditional and Big

2min
page 378

Summary

1min
page 358

Notes

7min
pages 363-365

References

19min
pages 366-377

Targeting Methods

9min
pages 359-362

Different Eligibility Approaches

2min
page 348

Addition of Quantitative Information to the Decision-Making Process

4min
pages 346-347

5.8 Illustrative Lessons from the Simulations Literature

8min
pages 354-357

Country

13min
pages 340-345

5.6 Profiling Job Seekers to Differentiate Support

2min
page 336

Methods That Rank People According to Welfare

6min
pages 337-339

a Fragile State

18min
pages 311-319

from Mongolia, Bolivia, and Nepal

5min
pages 331-333

Considerations in Choosing among Welfare Targeting Methods

2min
page 310

Category in Determining Eligibility or Benefits

4min
pages 334-335

B5.3.2 Woreda Selection Does Not Add Much to the PSNP’s Targeting Performance

7min
pages 322-325

5.1 Humanitarian–Social Protection Alignment

6min
pages 307-309

Reflections on Patterns of Use of Targeting Methods

14min
pages 301-306

Patterns in Using and Combining Targeting Methods

4min
pages 299-300

5.1 Common Targeting Methods

2min
page 298

Notes

4min
pages 286-287

Introduction

4min
pages 295-297

Conclusion

1min
page 285

References

10min
pages 288-294

4.7 Examples of How Countries Are Providing Data Security

1min
page 284

Data Protection?

3min
pages 282-283

from Chile and Moldova

7min
pages 278-281

Planning and Adapting Delivery Systems for Crisis Response

14min
pages 263-269

Program Access That Lead to Errors of Exclusion

4min
pages 273-274

Data Systems and Their Role in Supporting Eligibility Determination and Recertification

6min
pages 275-277

Client Interface: The Interaction between People and Institutions

6min
pages 270-272

Jigisemejiri Program

3min
pages 261-262

4.2 How Big Should a Social Registry Be?

17min
pages 253-260

Support Program

17min
pages 245-252

Fortifying Weak Links in the Delivery Chain to Reduce Errors of Exclusion and Inclusion

4min
pages 243-244

Introduction

6min
pages 239-242

References

13min
pages 230-238

3.3 Morocco’s Progress toward Universal Social Protection

6min
pages 221-223

3.2 Food Security and Money-Metric Welfare

14min
pages 194-200

Notes

14min
pages 224-229

“Vulnerability”

4min
pages 192-193

Part I: Even in Times of Stability, Welfare Measurement for Eligibility Determination Is Complex

13min
pages 186-191

References

11min
pages 178-185

Summary

4min
pages 160-161

Recent ASPIRE Survey–Based Evidence of Targeting Outcomes

4min
pages 123-124

Evidence Base for the Costs of Poverty Targeting

27min
pages 147-159

Notes

4min
pages 176-177

Measurement and Interpretation

11min
pages 118-122

References

19min
pages 107-117

Notes

4min
pages 105-106

Conclusion

2min
page 104

Essay 9: Does Universality Increase Budgets and Thus Reduce the Need for Prioritizing the Needy?

9min
pages 99-102

Essay 10: How Do Human Rights Frameworks View Targeting?

2min
page 103

Essay 8: Can Budgets Be Raised over Time to Reduce the Need for Targeting?

4min
pages 95-96

Essay 7: What Does the Distribution of Taxes Imply about the Distribution of Transfers?

4min
pages 91-92

Essay 6: Why Is Redistribution Important?

2min
page 90

1.1 Potential Sources of Revenue

3min
pages 97-98

Essay 5: Is Targeting the Poor Important for Outcomes Other Than Poverty?

4min
pages 88-89

1.1 Contrasting Policy and Budget Scenarios: Base Case

3min
pages 84-85

Essay 3: What Is the Rationale for Targeting by Welfare or Other Metrics?

4min
pages 82-83

Essay 1: Where Does Targeting Fit Conceptually within Universal Social Protection?

4min
pages 75-76

Essay 2: Where Does Targeting Fit Practically within Universal Social Protection?

8min
pages 78-81

References

3min
pages 71-74

Notes

2min
page 70

O.1 Common Targeting Methods

2min
page 58

O.6 Factors to Consider in Choosing a Targeting Method

23min
pages 59-69

Protection Measured?

2min
page 77

O.5 Social Protection Delivery Chain

5min
pages 55-57
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