public disclosure authorized safety nets...

1

Targeting

Social

Safety

Nets

Programs

SSN Core Course, April 27, 2016

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Currently working on a targeted

system or program(s)?

Your answers:

(a) yes

(b) no

2

CLICKER QUESTION

Currently working on a targeted system

or program(s)?

A. True

B. False

3

78%

22%

True False

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

CLICKER QUESTION

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

5M

aximize

cove

rage

(focu

s...

Re-bala

nce in

vest

ment .

..

Reduce d

ispers

ion

Incr

ease o

pportuniti

es fo...

All of a

bove

8%4%

77%

4%8%

Target group

Your answers:

(a) Vulnerable groups: single women, widows, elderly,

orphan, children

(b) Malnourished children or food insecure

(c) Unemployed

(d) Subsistence farmer

(e) Poor

6

CLICKER QUESTION

Target group

A. Vulnerable groups: single women,

widows, elderly, orphan, children

B. Malnourished children or food

insecure

C. Unemployed

D. Subsistence farmer

E. Poor

7

Vulnera

ble gro

ups: sin

gl...

Maln

ourished ch

ildre

n or..

.

Unemplo

yed

Subsiste

nce fa

rmer

Poor

43%

7%

45%

3%2%

Targeting measures: how do we assess

targeting?

Your answers:

(a) Higher coverage of the target group

(b) Lower inclusion of non-target group

(c) 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

CLICKER QUESTION


targeting?



(c) 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.

9Hig

her cove

rage o

f the t.

..

Low

er inclu

sion o

f non-t.

..

An acc

eptable

exclusio

n o...

31%

58%

11%

What is the best targeting method?

Your answers:

(a) Geographic

(b) Categorical

(c) Self-selection

(d) Community based

(e) (Proxy) Means tested

(f) Mixed

10

CLICKER QUESTION


(a) Geographic

(b) Categorical

(c) Self-selection

(d) Community based


(f) Mixed

11

Geographic

Categoric

al

Self-se

lect

ion

Comm

unity b

ased

(Pro

xy) M

eans teste

d

Mixe

d

0%

8%

69%

16%

6%2%

How do we improve targeting?

Your answers:

(a) Use Mixed methods

(b) Change/updated targeting criteria (“formula”,

target group..)

(c) Improve administration and implementation

(d) Develop an information system

(e) All of the above

12

CLICKER QUESTION



(b) Change/updated targeting criteria

(“formula”, target group..)

(c) Improve administration and

implementation



13

Use M

ixed meth

ods

Change/update

d targ

etin...

Impro

ve admin

istra

tion a

..

Develop an

info

rmatio

n ...

All of t

he above

0% 0% 0%0%0%

Poverty is multidimensional

14

1. Why target the poor?

15

Why consider targeting?

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

Concentrateresources may yield more than dispersing them by activating synergies

Maximize coverage

of the poor with

limited resources

Higher gaps

in education,

nutrition and

health among

the poorExclusion

Poverty may be linked to your objective

17

Malnutrition Poor education

Unemployment, underemployment

Vulnerability

Poverty

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

The benefits of targeting

18

Equity and efficiency

Fraction of the Social Assistance Budget Captured by Each

Quintile, Armenia 1998 and 1999

2. A balancing act

19

Targeting is NEVER perfect

20

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

21

Inclusion and Exclusion Errors

Eligibility

Threshold

Non-Poor population

Poor PopulationErrors of Exclusion

Errors of Inclusion

Of Non-Poor

Beneficiaries

of social

Assistance

Program

Overall Population

PROGRAM

Income or Consumption,

per capita or adult

equivalent

Coverage and accuracy (poorest 20%)

22

CCT

Mx: 37%

Br: 47%

Ind: 31%

Gh: 9%

The treatment of Bolsa Familia in the media

23

Source: Lindert and Vincensini, 2010

The press paid more attention to inclusion errors in electoral periods

Targeting has costs

24

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?

3. How to target?

Methods

25

Targeting methods

Geographical

Self-selection

Categorical

Community-based

(Proxy) Means Test

Combination

Geographical targeting

27

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

Self-targeting

28

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

29

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

Self-targeting for workfare

30

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


• Wage set below going wage for hard, physical labor

• A works program that does high value-added projects


• Unemployment; Crisis and chronic poverty settings

Categorical (demographic) targeting

31

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


• Good civil registry


• When targeting specific vulnerabilities (malnutrition)

CONS

Weak correlation with

poverty

PROS Administratively simple Low cost

Community-based targeting

32

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

Household targeting

Community-based targeting, PMT & Means-Tests

33

Community-based targeting

34

PROS

Good information

Low(on the books) administrative cost

Local monitoring may reduce disincentives

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 varyTechnical Requirements

•Intensive outreach to decision-makers

•Cohesive, well-defined communities


•Low administrative capacity

•Strong community structures, political economy

•Low benefit that must be finely targeted

Cost to

communities

Scalability

Proxy-means testing

35

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

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 well-

documented;

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

37

Targeting performance by targeting method

-

0.5

1.0

1.5

2.0

2.5

Any m

ethod

Any

Mea

ns

test

ed

Pro

xy-m

eans

test

ed

Com

munity

asse

ssm

ent

Any

Geo

gra

phic

al

Age:

Eld

erly

Age:

Young

Oth

er

cate

gori

cal

Any

Public

work

s

Consu

mption

Com

munity

bid

din

g

Individual assessment Categorical Any selection method

% o

f b

en

efi

ts / %

of

po

pu

lati

on

75th perc. 25th perc. Median

Coady, Grosh and Hoddinott, 2004

Handa et al., CBT 2010

Huge variation within

method according to

implementation

Combining methods may improve accuracy

38

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.

3. How to target?

Implementation issues

39

Five key decisions

40

• Survey, application, community

How to register?

• Local intake

• Central database and rules

Who takes the eligibility and other decisions? Technology can not substitute for institutional design

• Internal and external checks and balances

• Supply and demand-side accountability

How to deal with errors and fraud?

How to deal with changes?

How to build the required information system architecture?

Challenge 1: Targeting when everybody needs?

41

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

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?

Source: Kenya CT-OVC

Challenge 2: Targeting a program or a system?

42

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.

A good targeting system should ensure:

43

Transparency and consistency

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

3. How to?

Proxy-Means Testing

46

Targeting instrument: PMT

47

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


48

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

Proxy-means testing

49

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


MT, PMT or both?

50

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

Mathematically, we can represent the model as


51

where Xij 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, yi is the household welfare

(income or consumption) and sizei is the

number of members of household i.

ijiji

i

i XYsize

y ln

PMT score

52

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.

jmjm ZY ˆˆˆPMTscorem

)ˆˆexp()ˆexp(PMTscorem jmjm ZY

What is the cut-off point?

Lowest PMT Highest PMT

A B

Not eligible

Cut-off point 1

Cut-off point 4

Cut-off point 2 Cut-off point 3

C D

Potential Beneficiaries

5/4/201653

Inclusion errors increasing over time: how to deal with

20.6

37.5

12.9

49.3

16.7

51.3

14.4

61.9

14.6

53.1

13.0

63.7

17.6

54

14.7

66.4

0

10

20

30

40

50

60

70

EE EI EE EI

Pob_ingreso IPM

Colombia

2008 2010 2011 2012

Source: DNP

78.8

20.769.8

29.6

95

4.4

95.6

4.3

Casa o apartamento Cuarto

Type of household- SisbénVs

ECV

Sisbén III 2011 Sisbén III 2013

ECV 2011 ECV 2013

73.2

17.4

64.9

25.5

94.6

5.4

91.4

8.6

De uso exclusivo del hogar Compartido con otros

hogares

Type of sewage SisbénVs

ECV

Sisbén III 2011 Sisbén III 2013

ECV 2011 ECV 2013

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.

Sisbén

Optimizing its

operability

Offer additional services

to improve targetingStrengthening

interinstitutional

relations

Set the norms and

rules

Define

Interoperability

Have a better

information flow

Use spatial

information

Characterizing the

population

Work with local

authorities

Update PMT

Increase internal

validation and

checks

Improve IT platform Use local variables

New SISBEN

56

•DATA BASE

•The family has five

members (three children).

The household has

monthly income of GEL 20

•Ranking score - 39 550

•Single pensioner’s family.

Receives a pension (GEL

28) and social assistance

(GEL 22)


•The household has two

members.

•The household has

monthly income of GEL

80


•The family has three

members.

•The family has a disabled

child, who has a pension

(GEL 28) and social

assistance (GEL 22)

Ranking score - 155 470

The household has four

members. The household

has monthly income of

1,050 GEL


•5

•4

•2•1

Visualizing Targeting Outcomes in Georgia’s PMT

•3

57

DATABASE

•5

•4

•2•1

Monetary

benefits

Health

subsidies

Electricity

subsidies

•3

Visualizing Targeting Outcomes in Georgia’s PMT

http://documents.worldbank.org/curated/en/2014/06/22671265/effective

-targeting-poor-vulnerable

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

4. How to?

Means Testing

59

Means Testing (MT)

60

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 well-documented;

Where benefit high

Used in OECD, Central/Eastern Europe, South Africa

Can generate strong targeting outcomes

62

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

For your

information

63

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

64

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

For your

information

Means-Testing in Countries with Moderate

Informal Sectors (ECA Countries)

65

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

… Amid Significant Informality

66

Benefit Incidence is Largely Highly

Progressive, but Coverage among the

poorest decile is low

67

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

First Puzzle:

69

Most ECA LRIS Programs Use Verified Means Testing to Identify Beneficiaries

Eligibility determined

based on a number of

tests

Extensive verification of

information

Benefit calculations

(GMI formula)

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)

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

Benefits level = maximum benefit minus administrativeincome

Taking into account household size

Results in graduated benefits

Targeting in Practice:

Some Incomes are Hard to Verify

70

Easy to

verify

Hard

to

verify

Empirics on Hard and Easy to Verify Income

71

Bulgaria Kyrgyz Republic

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

77

Programs with good targeting accuracy:

DO DON’T

… include formal incomes to test eligibility; and verify

this information

... ask household to report income sources

that could not be verified (vicious circle)

… 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

… 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

Can the administrative

costs of such complex

programs be kept

reasonable?

Second Puzzle:

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

ECA Uses Complex Administrative

Infrastructure to Support LRIS (and other SA)

Programs

80

Country

Number of

administrative-territorial

tiers, and total population

Subnational tiers involved in program administration

Regional level Local level

Albania 2 tiers, 3.6 million12 Regional Service

Administrations385 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 40 rayon Departments;

477 rural local governments

Lithuania 2 tiers, 3.5 million No role60 Departments;

550 wards

Romania 2 tiers, 21.5 million42 Directorates of Social

Assistance3,176 local governments

Uzbekistan 3 tiers, 25 million 12 Oblast Departments 382 rayon Departments;

12,000 mahalla committees

Despite the programs’ complexity,

administrative costs of LRIS are not high

81

In most cases the cost of eligibility determination

and recertification has the highest share

Title of Presentation82

The investment in administration results in

more progressive transfers

83

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

Key Messages on MT programs in countries

with moderate formal sectors

For ECA Region For the Rest of the World

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

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?

85

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.

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 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.

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 re-

certification

Improving program administration

MIS, Staff training, Coordination,....89

More information

90

www.worldbank.org/safetynets

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

http://www.worldbank.org/safetynets

Thank you!

91

Training

Source: Bolsa Familia

municipal manager manual

The database

Intake Storing and archiving

Database

Currently working on a targeted system

or program(s)?

A. True

B. False

92

0%

0%

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

94M

aximize

cove

rage

(focu

s...

Re-bala

nce in

vest

ment .

..

Reduce d

ispers

ion

Incr

ease o

pportuniti

es fo...

All of a

bove

0% 0% 0%0%0%

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

96

Vulnera

ble gr

oups: sin

g..

Maln

ourished ch

ildre

n or..

.

Unemplo

yed

Subsis

tence

farm

erPoor

0% 0% 0%0%0%

Target group


targeting?



(c) 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.

98Hig

her cove

rage o

f the t.

..

Low

er inclu

sion o

f non-t.

..

An acc

eptable

exclusio

n o...

0% 0%0%

Targeting measures: how do we assess targeting?


(a) Geographic

(b) Categorical

(c) Self-selection

(d) Community based


(f) Mixed

100

Geographic

Categoric

al

Self-se

lect

ion

Comm

unity b

ased

(Pro

xy) M

eans teste

d

Mixe

d

0% 0% 0%0%0%0%



(b) Change/updated targeting criteria

(“formula”, target group..)

(c) Improve administration and

implementation



102

Use M

ixed meth

ods

Change/update

d targ

etin...

Impro

ve admin

istra

tion a

..

Develop an

info

rmatio

n ...

All of t

he above

16%

2%

79%

2%2%