Targeting Social Safety Nets Programs

Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized SSN Core Course, April 27, 2016 Targeting Social Safety Nets Programs 1 d

CLICKER QUESTION Currently working on a targeted system or program(s)? Your answers: (a) (b) yes no 2

Currently working on a targeted system or program(s)? A. True B. False 22% 78% 3 True False

CLICKER QUESTION Why targeting? Your answers: (a) Maximize coverage (focus resources) for those in need (b) Re-balance investment towards excluded "groups (c) Reduce dispersion (d) Increase opportunities for those in need (e) All of above 4

Why targeting? A. Maximize coverage (focus resources) for those in need 77% B. Re-balance investment towards excluded "groups C. Reduce dispersion D. Increase opportunities for those in need E. All of above 8% 4% 8% 4% 5 Maximize coverage (focus... Re-balance investment... Reduce dispersion Increase opportunities fo... All of above

CLICKER QUESTION Target group Your answers: (a) (b) (c) Vulnerable groups: single women, widows, elderly, orphan, children Malnourished children or food insecure Unemployed (d) Subsistence farmer (e) Poor 6

Target group A. Vulnerable groups: single women, widows, elderly, orphan, children 43% 45% B. Malnourished children or food insecure C. Unemployed D. Subsistence farmer E. Poor 7% 2% 3% 7 Vulnerable groups: singl... Malnourished children or... Unemployed Subsistence farmer Poor

CLICKER QUESTION Targeting measures: how do we assess targeting? Your answers: (a) (b) (c) Higher coverage of the target group Lower inclusion of non-target group An acceptable exclusion of few that should be in the target group and an acceptable inclusion of the few that should be in the non-target group. 8

Targeting measures: how do we assess targeting? (a) (b) (c) Higher coverage of the target group Lower inclusion of non-target group An acceptable exclusion of few that should be in the target group and an acceptable inclusion of the few that should be in the non-target group. 31% 11% 58% 9 Higher coverage of the t... Lower inclusion of non-t... An acceptable exclusion o...

CLICKER QUESTION What is the best targeting method? Your answers: (a) (b) (c) Geographic Categorical Self-selection (d) Community based (e) (f) (Proxy) Means tested Mixed 10

What is the best targeting method? (a) (b) (c) Geographic Categorical Self-selection (d) Community based (e) (f) (Proxy) Means tested Mixed 69% 16% 0% 8% 2% 6% 11 Geographic Categorical Self-selection Community based (Proxy) Means tested Mixed

CLICKER QUESTION How do we improve targeting? Your answers: (a) (b) (c) Use Mixed methods Change/updated targeting criteria ( formula, target group..) Improve administration and implementation (d) Develop an information system (e) All of the above 12

How do we improve targeting? (a) (b) (c) Use Mixed methods Change/updated targeting criteria ( formula, target group..) Improve administration and implementation (d) Develop an information system (e) All of the above 0% 0% 0% 0% 0% 13 Use Mixed methods Change/updated targetin... Improve administration a.. Develop an information... All of the above

Poverty is multidimensional 14

15 1. Why target the poor?

Why consider targeting? Maximize coverage of the poor with limited resources Exclusion Higher gaps in education, nutrition and health among the poor Focus resources where they are most needed Limited financing means universal is not viable Maximize impact within a given budget Minimize cost to reach a given impact Historically public spending go to higher income groups (e.g., formal sector, where the poor are few) Without active outreach to the poor, even «universal» programs tend to miss them Concentrate resources may yield more than dispersing them by activating synergies

Poverty may be linked to your objective Malnutrition Poor education Poverty Unemployment, underemployment Vulnerability Targeting on your objective may undermine it The malnourished children of Bolsa Alimentação The orphans in Kenya Sometimes other categories may work Widows in rural Africa Families with no able-bodied workers 17

The benefits of targeting Equity and efficiency Fraction of the Social Assistance Budget Captured by Each Quintile, Armenia 1998 and 1999 18

19 2. A balancing act

Targeting is NEVER perfect Never 100% accurate What do these errors cost? Efficiency Social and political capital Inclusion: Media attention Exclusion: disenfranchisement What does it take to address them? A fine balance between the costs of accuracy and errors and the goals of targeting.costs 20

Inclusion and Exclusion Errors Income or Consumption, per capita or adult equivalent Overall Population Non-Poor population Eligibility Threshold Errors of Inclusion Of Non-Poor PROGRAM Beneficiaries of social Assistance Program Errors of Exclusion Poor Population 21

Coverage and accuracy (poorest 20%) CCT Gh: 9% Mx: 37% Ind: 31% Br: 47% 22

The treatment of Bolsa Familia in the media Source: Lindert and Vincensini, 2010 The press paid more attention to inclusion errors in electoral periods 23

Targeting has costs Intake Registry Lots of set-up costs, as programs scale-up Difficult to measure b/c of shared staff and functions Documents (IDs, proof of status) Need to go to an office, spend time, work requirement in workfare Stigma (public list) Work effort: benefit levels, sliding withdrawals, periodicity Crowding out private transfers or complementing them Fertility effects: quantity and quality of children Is a program for the poor a poor program? 24

25 3. How to target? Methods

Targeting methods Categorical Geographical (Proxy) Means Test Combination Self-selection Communitybased

Geographical targeting When location is an important determinant of poverty Macro regions Micro-area poverty maps: based on census and household surveys Can be important when administrative capacity is low Often used as a first step: Panama s Red de Protección Social (CCT) Program 27

Self-targeting Open to everyone but only the poor will be interested Food subsidies of staples consumed by the poor: are they really consuming less? Midly progressive at best. Little exclusion and stigmatization but high inclusion errors. Example: Food subsidies in MENA Labor intensive public works with wages set very low: works for targeting. Stignatization can be high, exclusion errors can be high. Example: Trabajar in Argentina Some elements of self-targeting in a lot of programs: long waiting lines, compliance with conditionalities Categorical targeting 28

Self targeting for consumption subsidies PROS Administratively simple Few errors of exclusion Universal benefit may be politically very popular CONS Hard to find really inferior goods May be hard to transfer large amounts Hard to reform Technical Requirements An inferior good with a suitable marketing chain A service supplied by public and private sector where amenities can differ Appropriate Circumstances Low administrative capacity 29

Self-targeting for workfare PROS Administratively simple Keeps work incentives Eliminates concerns about shirkers Automatic exit criteria CONS Organizing public works is not administratively simple Not applicable for many programs or target groups Foregone earnings reduce net benefit Technical Requirements Wage set below going wage for hard, physical labor A works program that does high value-added projects Appropriate Circumstances Unemployment; Crisis and chronic poverty settings 30

Categorical (demographic) targeting Characteristics that are linked to poverty or vulnerability Age: pre-school children and old-age Marital status: single parent Ethnicity: scheduled castes in India, native American PROS Administratively simple Low cost CONS Weak correlation with poverty Technical Requirements Good civil registry Appropriate Circumstances When targeting specific vulnerabilities (malnutrition) 31

Community-based targeting Uses a group of community members or leaders (whose functions are not related to the program) They must identify those most in need according to program criteria (often OVC, elderly, hh w/o able-bodied adult) Good results Community meeting SCT Zambia 32

Household targeting Community-based targeting, PMT & Means-Tests 33

Community-based targeting PROS Good information Low(on the books) administrative cost Local monitoring may reduce disincentives Technical Requirements Intensive outreach to decision-makers Cohesive, well-defined communities Appropriate Circumstances Low administrative capacity 34 CONS Unknown effects on roles of local actors Costly for the community May reinforce existing power structures or patterns of exclusion May generate conflict and divisiveness Local definitions may vary Strong community structures, political economy Low benefit that must be finely targeted Cost to communities Scalability

Proxy-means testing Multi-dimensional notion of poverty (politically palatable) Eligibility based on weighted index of observable characteristics (score), not easily manipulated and associated with poverty: Variables and weights can be determined using regression (predictors) or principal components analysis Variables typically include: location, housing quality, assets/durables, education, occupation and income, and a variety of others (disability, health, etc.) Appropriate in situations with high degree of informality, seasonality, or in-kind earnings; where chronic poor are the target group; where benefits will be granted for long periods of time Fairly good results 35

36 Means Testing (MT) Eligibility determined based on income and asset tests or self-declaration Verification of information, sometimes extensive Documentation provided by applicant (payroll statements, benefit letters, banking statements, vehicle documentation, etc.) Third party documentation, usually automated (tax records, social security registry, unemployment listings, immigration, banking information) Appropriate conditions: Incomes, expenditures, wealth are formal, monetized and welldocumented; Where benefits are high Used in OECD, Central/Eastern Europe, South Africa Can generate strong targeting outcomes but low take-up

No single method is best Targeting performance by targeting method % of benefits / % of population 2.5 2.0 1.5 1.0 0.5 - Any method Any Means tested Proxy-means tested Community assessment Any Geographical Age:Elderly Age:Young Other categorical Any Public works Consumption Community bidding Huge variation within method according to implementation Individual assessment Categorical Any selection method 75th perc. 25th perc. Median Handa et al., CBT 2010 Coady, Grosh and Hoddinott, 2004 37

Combining methods may improve accuracy Often a first step is geographical targeting Then collect some information at the household-level Triangulate from several sources: Respondent Community Administrative records at local and central level Grievance and redress mechanisms No matter which combination, implementation is key. 38

39 3. How to target? Implementation issues

Five key decisions How to register? Survey, application, community Who takes the eligibility and other decisions? Technology can not substitute for institutional design Local intake Central database and rules How to deal with errors and fraud? Internal and external checks and balances Supply and demand-side accountability How to deal with changes? 40 How to build the required information system architecture?

Challenge 1: Targeting when everybody needs? Focus on children: not losing the next generation, politically acceptable (even if they do not vote) AIDS and its stigma Giving transfers to children? When poverty (crisis) is very deep: Should you target the poor who have a chance? Should you give a chance to those who would sink? Households with «able-bodied» workers or not (who defines?) We know the PMT does not function very well Source: Kenya CT-OVC Who takes the decision? Make the criteria as extensive as possible to minimize the arbitrariness at the local level but politically difficult How to support communities, build appeals and grievance and genuine participation? 41

Challenge 2: Targeting a program or a system? The registry may be used for different programs with different cut-offs interventions: applicant beneficiary Use different sets of the information (multi-dimensions of poverty) => a planning tool The idea is to focus programs on the needs of poor households and communities Cadastro Unico (Brazil) and popular housing, training and literacy, micro-credit Ethiopia: efforts to merge different databases Respect confidentiality/privacy among different systems. 42

A good targeting system should ensure: Transparency and consistency 43 Clear and consistent application of centralized criteria Low political interference and manipulation by frontline officials and beneficiaries Maximum inclusion of the poor with on-going access to the registry People who think they are eligible should be able to apply Issues: budget and outreach Minimum leakage to the non-poor As technically possible, to near poor, errors rather than fraud Cost-efficiency

Implementation Despite the method, implementation matters a LOT for optimizing targeting outcomes Moving from population to beneficiary is not simple. General population Budget implications, coordination, administration and transparency Target population Budget, develop a Monitoring and Information system, determine a targeting method; design an information and outreach campaing, ensure low cost for potential beneficiaries, set payment level 44

Implementation: key points to remember 45

46 3. How to? Proxy-Means Testing

Targeting instrument: PMT What is it? PMT (or scoring formula) is a method to estimate household welfare without requiring detailed information about household welfare. PMT is very useful when large share of household welfare is derived from hard-to-verify sources such as: Informal sector Own production Agricultural production Entrepreneurial activities 47

Targeting instrument: PMT How does it work? Rather than measure total welfare of the household perfectly, we collect some information about the household that are first all correlated with poverty, also easier to measure and to verify such as: Family composition Employment Housing characteristics Ownership of durable goods Geographical location 48

Targeting instrument: PMT Proxy-means testing Multi-dimensional notion of poverty (politically palatable) Eligibility based on weighted index of observable characteristics (score), not easily manipulated and associated with poverty: Variables and weights can be determined using regression (predictors) or principal components analysis Variables typically include: location, housing quality, assets/durables, education, occupation and income, and a variety of others (disability, health, etc.) Appropriate in situations with high degree of informality, seasonality, or in-kind earnings; where chronic poor are the target group; where benefits will be granted for long periods of time Fairly good results 49

MT, PMT or both? Overlap in approaches is common. Bulgaria, Romania, Kyrgyzstan MT systems impute the income potential of land and livestock, thus using them as proxies Brazil uses PMT-models to check unverified declared means Chile, Armenia PMT have some income questions on their form 50

Targeting instrument: PMT Mathematically, we can represent the model as ln y i size i Y i X where X ij are the j characteristics of the household i, and are the PMT weights that will be generated, is the model error for each household i, y i is the household welfare (income or consumption) and size i is the number of members of household i. ij j i 51

PMT score PMTscore m Yˆ ˆ m Z mj ˆ j PMTscore m exp( Yˆ ) exp( ˆ m Z mj ˆ ) Therefore, once the PMT weights are estimated in the household survey and applied on the program database, we can estimate the welfare of the household by the PMTscore. j 52

What is the cut-off point? Cut-off point 4 Lowest PMT Cut-off point 1 Cut-off point 2 Cut-off point 3 Highest PMT A B C D Potential Beneficiaries Not eligible 53 5/4/2016

70 60 50 40 30 20 10 0 20.6 16.7 14.6 17.6 37.5 51.3 53.1 54 Inclusion errors increasing over time: how to deal with 12.9 14.4 13.0 14.7 49.3 EE EI EE EI Pob_ingreso Colombia IPM 61.9 63.7 66.4 Type of household- SisbénVs ECV 78.8 69.8 Sisbén III 2011 Sisbén III 2013 ECV 2011 ECV 2013 95 95.6 Casa o apartamento 20.7 29.6 Cuarto 4.4 4.3 2008 2010 2011 2012 Type of sewage SisbénVs ECV 73.2 64.9 Sisbén III 2011 Sisbén III 2013 ECV 2011 ECV 2013 94.6 91.4 17.4 25.5 5.4 8.6 Source: DNP De uso exclusivo del hogar Compartido con otros hogares

Sisbén New SISBEN Information system designed to identify potential households beneficiaries for social programs, and be used by local authorities and implementers of social policy on the national agenda. Optimizing its operability Update PMT Increase internal validation and checks Improve IT platform Offer additional services to improve targeting Characterizing the population Use spatial information Use local variables Work with local authorities Strengthening interinstitutional relations Set the norms and rules Define Interoperability Have a better information flow

Visualizing Targeting Outcomes in Georgia s PMT The family has five members (three children). The pensioner s household has Single family. monthly income of GEL 20 Receives a pension The household has(gel two Ranking score - 39 550 28) and members. social assistance (GEL 22) Thefamily household has The has three Ranking scoreof- 47 950 monthly income GEL members. 80 a disabled The family has Ranking 64 300 child, whoscore has a-pension The household has four (GEL 28) and social members. The household assistance 22)of has monthly (GEL income GEL Ranking1,050 score - 155 470 Ranking score - 665 960 DATA BASE 5 4 1 3 2 56

Visualizing Targeting Outcomes in Georgia s PMT DATABASE 5 Electricity subsidies 4 Health subsidies 3 Monetary benefits 1 2 57

http://documents.worldbank.org/curated/en/2014/06/22671265/effective -targeting-poor-vulnerable

59 4. How to? Means Testing

Means Testing (MT) Eligibility determined based on income and asset tests Verification of information, sometimes extensive Documentation provided by applicant (payroll statements, benefit letters, banking statements, vehicle documentation, etc.) Third party documentation, usually automated (tax records, social security registry, unemployment listings, immigration, banking information) Benefit levels often tailored according to household size & characteristics, sometimes to income Appropriate conditions: Where incomes, expenditures, wealth are formal, monetized and welldocumented; Where benefit high Used in OECD, Central/Eastern Europe, South Africa Can generate strong targeting outcomes 60

For your information Verifying Identity in US Crucial to avoid duplications in payments, fraud or other errors in processing Have to be able to identify and link individuals and households Several tools used: Single identification number: social security number (SSN) in US Case workers assist applicants to get SSN if don t have it Documentation: proof of address, identity, household members Within-system computer checks of applicant characteristics: Name, age, birth date, sex, race, SSN, address, etc. Based on these characteristics, assign meaningful soundex number Computer runs checks for matches and near-matches for these characteristics Case workers must reconcile any near match or match 62

Verifying Incomes, Assets in US First Tool: Documentation Remember: works well in formal economies with monetized and computer tracked earnings Documentation for Incomes: Generally covers past two months Salary statements Employer wage statements, letters Benefit letters from other programs Documentation for Assets: Two months banking statements (savings, checking) Value of stocks or bonds, life insurance if any Vehicle documentation Documentation on Expenses: Shelter costs, property tax bills Utility bills (gas, electricity, water) Written statement of child care costs, medical care receipts For your information 63

For your information Verifying Incomes, Assets, in US Cont d Second Tool: Automated Computer Matches Computer systems for social assistance are linked to many other systems US: Average number of cross-system checks increasing: In 1991on average ran cross-checks with 7.5 other systems By 2002: cross-checks with 14 other systems Examples: Department of Labor New Hire Registry (employment) Income Verification System Department of Motor Vehicles (for vehicle asset test) Banking System (matching bank records with those in treasury system) Lottery System, etc. Technology greatly improving for cross-system checks: 38% are all now done on-line Common interfaces, single queries for multiple matches 64

Means-Testing in Countries with Moderate Informal Sectors (ECA Countries) 28 of the 30 countries in the ECA region operate last resort income support (LRIS) programs In most cases the programs have operated and evolved since shortly after transition 25 countries use means-test (MT) to assess eligibility, while 3 countries use proxy-means-test (PMT); in the large majority of cases the (proxy) means test is verified 15 countries have Guaranteed Minimum Income (GMI) benefit structure 65

66 Amid Significant Informality

67 Benefit Incidence is Largely Highly Progressive, but Coverage among the poorest decile is low

First Puzzle: How can means testing be successful in economies with significant informal sectors? Most ECA countries have succeeded to put in place flexible, scalable, and well targeted LRIS programs amid high informality, and with low administrative costs

Most ECA LRIS Programs Use Verified Means Testing to Identify Beneficiaries Eligibility determined based on a number of tests Net income tests: Net income Less a income disregards Normalized per adult equivalent or per capita Compared to threshold Asset tests: Asset value compared to threshold (e.g. financial savings) Yes/No filters (e.g. second house, vehicles) Extensive verification of information Documentation provided by applicant payroll statements, benefit letters, banking statements, house ownership and vehicle documentation, etc. Third party documentation, usually automated tax records, social security registry, unemployment registry, banking information Benefit calculations (GMI formula) Benefits level = maximum benefit minus administrative income Taking into account household size Results in graduated benefits 69

Targeting in Practice: Some Incomes are Hard to Verify Easy to verify Hard to verify 70

Empirics on Hard and Easy to Verify Income Bulgaria Kyrgyz Republic 71

72

Household Under-Report Informal Incomes, and even Formal Incomes when Unverified 73

Documentation and Verification of Information Reduces Under-Reporting 74

Imputations Often Used to Address the Under-Reporting of Hard-to-Verify Income 75

To Improve Targeting LRIS Programs Use Asset Filters, but they tend to generate High Errors of Exclusion 76

DO's and DON Ts of Means Tested Programs Programs with good targeting accuracy: DO include formal incomes to test eligibility; and verify this information estimate informal income based on asset ownership (e.g. land, livestock) or presumed income (based on type of occupation); and verify the asset information verify the composition of assistance units use asset filters that do not exclude low income households DON T... ask household to report income sources that could not be verified (vicious circle) use asset filters without calibrating them (they lead to high exclusion error in many programs, explaining some of the low coverage) use on demand application use different mechanisms to address the inherent work disincentives 77

Second Puzzle: Can the administrative costs of such complex programs be kept reasonable?

Good Targeting Requires Administration Frontline units close to beneficiaries: On demand registration (self-selection) The composition of assistance units, formal incomes, and some assets are verified including through home visits Frequent recertification and mandatory updates of documents (quarterly or annually) Sometimes additional conditions (community works) 79

Infrastructure to Support LRIS (and other SA) Programs Subnational tiers involved in program administration Number of Country administrative-territorial tiers, and total population Regional level Local level Albania 2 tiers, 3.6 million 12 Regional Service Administrations 385 offices; Armenia 2 tiers, 3.2 million 11 Departments 55 Centers Bulgaria 2 tiers, 7.2 million 28 Regional Directorates 272 Directorates Kyrgyz Republic 3 tiers, 5.2 million 7 oblast Departments Lithuania 2 tiers, 3.5 million No role Romania 2 tiers, 21.5 million 42 Directorates of Social Assistance Uzbekistan 3 tiers, 25 million 12 Oblast Departments 40 rayon Departments; 477 rural local governments 60 Departments; 550 wards 3,176 local governments 382 rayon Departments; 12,000 mahalla committees 80

81 Despite the programs complexity, administrative costs of LRIS are not high

In most cases the cost of eligibility determination and recertification has the highest share 82 Title of Presentation

The investment in administration results in more progressive transfers The marginal cost of targeting (e.g. eligibility determination and recertification) represents 50 60% of total administrative cost but investment in targeting seems to yield improved targeting accuracy, and thus lower program cost 83

Key Messages on MT programs in countries with moderate formal sectors For ECA Region 1. MT programs are effective 2. But in many countries are too small, there are sound reasons for them to play a larger role in social policy 3. Some countries still lag behind regional champions For the Rest of the World 1. Means testing is feasible in economies with sizable informal sector and reasonable administrative capacity 2. Investing in administrative systems could help deploying LRIS programs that are flexible, respond better to shocks, with improved benefit incidence 84

MT, PMT or both? Overlap in approaches is common. Bulgaria, Romania, Kyrgyzstan MT systems impute the income potential of land and livestock, thus using them as proxies Brazil uses PMT-models to check unverified declared means Chile, Armenia PMT have some income questions on their form Implementation arrangements have much in common: Verification strategies home visit versus computerized cross-checks of databases Outreach, re-certification, quality control, system design, staffing, etc. 85

Conclusion 87 Targeting is complex A single method does not dominate another Combination can work but attention is needed on the implementation arrangements Implementation arrangements have much in common: Verification strategies home visit versus computerized cross-checks of databases Outreach, re-certification, quality control, system design, staffing, etc.

Conclusion 88 Combining methods may improve accuracy Often a first step is geographical targeting Then collect some information at the householdlevel Triangulate from several sources: Respondent Community Administrative records at local and central level Grievance and redress mechanisms No matter which combination, implementation is key.

Conclusion Implementation matters Lowering barriers to participation Effective dissemination of information about the program Minimize visits and waiting for application Minimize documentation required, free-of-charge provision of documents attesting eligibility Introduction of one-stop or one-window system; Single application for multiple benefits Lowering errors Use multiple targeting methods combined Cross-check the information provided by applicants against other public databases; Perform home-visits to assess the means of the households and Frequent recertification Improving program administration MIS, Staff training, Coordination,... 89

More information www.worldbank.org/safetynets 90 Enrollment in the Safety Net, How-to Note Grosh, del Ninno, Tesliuc & Ouerghi, From Protection to Promotion: The Design and Implementation of Effective Safety Nets, Chapter 4 Tesliuc, Pop, Grosh & Yemtsov, Income Support for the Poorest: A review of experience in Eastern Europe and Central Asia Governance and service delivery, in SSN working papers series

Intake Storing and archiving Thank you! Database Training The database 91 Source: Bolsa Familia municipal manager manual

Currently working on a targeted system or program(s)? A. True B. False 0% 0% 92 True False

Currently working on a targeted system or program(s)?

Why targeting? A. Maximize coverage (focus resources) for those in need B. Re-balance investment towards excluded "groups C. Reduce dispersion D. Increase opportunities for those in need E. All of above 0% 0% 0% 0% 0% 94 Maximize coverage (focus... Re-balance investment... Reduce dispersion Increase opportunities fo... All of above

Why targeting?

Target group A. Vulnerable groups: single women, widows, elderly, orphan, children B. Malnourished children or food insecure C. Unemployed D. Subsistence farmer E. Poor 0% 0% 0% 0% 0% 96 Vulnerable groups: sing.. Malnourished children or... Unemployed Subsistence farmer Poor

Target group

Targeting measures: how do we assess targeting? (a) (b) (c) Higher coverage of the target group Lower inclusion of non-target group An acceptable exclusion of few that should be in the target group and an acceptable inclusion of the few that should be in the non-target group. 0% 0% 0% 98 Higher coverage of the t... Lower inclusion of non-t... An acceptable exclusion o...

Targeting measures: how do we assess targeting?

What is the best targeting method? (a) (b) (c) Geographic Categorical Self-selection (d) Community based (e) (f) (Proxy) Means tested Mixed 0% 0% 0% 0% 0% 0% 100 Geographic Categorical Self-selection Community based (Proxy) Means tested Mixed

What is the best targeting method?

How do we improve targeting? (a) (b) (c) Use Mixed methods Change/updated targeting criteria ( formula, target group..) Improve administration and implementation (d) Develop an information system (e) All of the above 16% 79% 2% 2% 2% 102 Use Mixed methods Change/updated targetin... Improve administration a.. Develop an information... All of the above

How do we improve targeting?