Assessing the Targeting Performance of Social Programs: Cape Verde

MPRAMunich Personal RePEc Archive

Assessing the Targeting Performance ofSocial Programs Cape Verde

Diego Angel-Urdinola and Quentin Wodon

World Bank

January 2008

Online at httpmpraubuni-muenchende11072MPRA Paper No 11072 posted 14 October 2008 0505 UTC

Budget constraints faced by governments in developing countries implythat effectively targeting performance of public subsidies and social pro-grams (whether the subsidies are provided in cash or in kind) is impor-tant in reducing povertyThere are three main advantages to effective tar-geting First for programs not intended to offer universal coverage bettertargeting helps reduce program outlay because there are fewer benefici-aries Second for any given level of outlay better targeting suggests thatthe share of public expenditure that accrues to poor people typically willbe higher and so will enable the programs to have a larger impact onpovertyThird targeting may help reduce the potential negative incentiveeffects or distortions in economic behavior associated with transfers iffewer households are affected by the programs For example if fewerhouseholds benefit from subsidized water or electricity service there willbe less incentive to consume more than would be consumed normally ifthe full cost of the service were paid by the household Too much target-ing however can produce negative incentive effects In some industrialcountries transfers may lead to poverty traps whereby the incentives forsome households to emerge from poverty are lessened by high implicittaxation rates associated with increased income and decreased transfers

C H A P T E R 1 3

Assessing the Targeting Performance

of Social Programs

Cape Verde


417

(c) The International Bank for Reconstruction and Development The World Bank

In this chapter our objective is not to discuss the incentive effects asso-ciated with social programs rather we intend to document the incidenceor distributional properties of the programs under way in Cape Verde agroup of islands off the West African coast in the North Atlantic Oceanand to analyze whether some systems of targeting could help improvetargeting performance1

According to the Cape Verde poverty report prepared by the WorldBank (2005) public transfers in Cape Verde represent on average be-tween 5 percent and 13 percent of household income depending on theconsumption quintile to which a household belongs Most social publicspending is invested for education health care and pensions As a resultschool enrollment rates are high and the country has been successful ineradicating most communicable diseases and in achieving the best per-formance levels for basic indicators among sub-Saharan African countries2

Cape Verde however needs to improve the efficiency of its spendingbecause of budget constraintsThe demands for education and health carehave increased with nearly universal access to primary education trans-lating into a higher demand for secondary and tertiary education Unitcosts per student in primary school increased from $60 in 1993 to $128in 2000The increase at the secondary level was even larger from $125 in1993 to $334 in 2000 (World Bank 2005) Estimates suggest that the an-nual unit cost for a student in tertiary education circa 2004ndash05 could beas high as $2000 (because of investment in new university facilities andstudy-abroad programs promoted by the government)

Because overall life expectancy is high the health care system faces thechallenge of providing subsidized and affordable medical care to a grow-ing and aging population in need of expensive and complicated treat-ments Government expenditures on pensions also are substantial and thefinancial situation of the contributory pension system is not sustainablein the long run (see World Bank 2007)

Beyond an analysis of the incidence of public spending in Cape Verdewe also provide a framework for analyzing the factors that determine thetargeting performance of social programs and transfers Whereas most in-dicators of benefit incidence are silent as to why subsidies are targeted theway they are (that is the indicators give only an idea of subsidiesrsquo targetingperformance)3 we develop a simple decomposition that enables an analy-sis of both ldquoaccessrdquo and ldquosubsidy designrdquo factors that affect subsidiesrsquo over-all targeting performance Finally we explore the potential for more effec-

418 Public Finance for Poverty Reduction


tive targeting of social programs in Cape Verde by comparing the target-ing performance that could be achieved either under a proxy means-test-ing system or under a geographic targeting system based on a poverty maprecently completed

To sum up to increase efficiency and limit costs efforts must be madeto allocate resources to those segments of the population that most needthem In this chapter we analyze how public transfers are targeted usingdata from a 2001ndash02 national household survey and study the incidenceand coverage of public transfers Because incidence analysis does not ex-plain the rationale behind resource allocation we look at the determi-nants of the systemrsquos targeting performance following a framework devel-oped by Angel-Urdinola and Wodon (2007) We also discuss alternativetargeting mechanisms to improve performance

Incidence of Public Transfers and Targeting Performance

This section provides an analysis of the incidence and coverage of publictransfers in Cape Verde using data from the Inequeacuterito agraves Despensas e Re-ceitas Familiares household survey conducted by Cape Verdersquos Ministryof Finance and the National Institute for Statistics during the lasttrimester of 2001 and the first trimester of 2002 The survey collectedgeneral information on households and individuals (including data on de-mographics education assets and health) and comprehensive informa-tion on income and expenditures The stratified sample included 4584households (44 percent from rural areas) and was representative of thetotal population (approximately 95257 households)

Our analysis covers all public transfers that could be identified in thehousehold survey Public spending for primary secondary and tertiary edu-cation is considered as are outlays for public pensions (that is reform pen-sions which are traditional pensions and minimum pensions which targetpoor people)4 The survey also included information on school stipends(bolsas de estudo) other public subsidies (abonoes e subsiacutedios diversos) andsocial assistance (prestaccedilotildees de assistecircncia social pelas administraccedilotildees publicasem geacutenero)

Many assumptions have been made in using the survey data One as-sumption is that the unit cost of providing basic in-kind public servicesmdashsay in education and healthmdashis similar across geographic areas or house-hold categories that use these services As noted by Wodon and Ye (2006)

Assessing the Targeting Performance of Social Programs Cape Verde 419


in the case of Sierra Leone when this assumption is not verified it typi-cally is because poor people benefit more than nonpoor people fromlower-cost (and lower-quality) services This means that the estimates ofin-kind benefits accruing to the poor from the use of publicly providedservices as presented here are probably overstated

To present and visualize our results on the incidence of public transferswe first rely on a diagram that provides three sources of information atonce (figure 131)The three indicators are the percentage of the poor pop-ulation that benefits from any given income source the percentage of thetotal income from a source that is received by the poor and the size of theincome source (that is the total income from the source obtained by thepopulation as a whole) Here are the key results portrayed in the figure

bull Sizes of various transfers Primary secondary and tertiary educationhealth care and reform pensions all represent large public transfers tohouseholds (pensions are not purely public transfers however they arepartly private contributions because workers have contributed to thepension scheme) Outlays for minimum pensions school stipends so-cial assistance and other public subsidies are much smaller


Figure 131 Incidence and Coverage of RemittancesPrivate Transfers 2001ndash2002

Source Authorsrsquo estimates

10

07

04

01

ndash02

rea

ch a

mo

ng

th

e p

oo

r (

of

the

po

or

wh

o b

en

efi

t fr

om

th

e s

ou

rce

)

0 025 050 075 100

targeting to the poor ( of total transfer from the sourcereceived by the poor)

perfect transferprimary education

secondaryeducation

health carereform

pensionspublic study fund

minimum pension

public subsidiestertiary education

social assistance


bull Coverage For primary and secondary education and for health servic-es coverage levels are fairly high For other transfers coverage levelsare in the 10ndash15 percent range or even lower For example coverage oftertiary education among the poor is virtually zero

bull Targeting Given that poor people represent 367 percent of the coun-tryrsquos population5 a lower share than 367 percent would mean thatrelative to their population size poor people benefit less from trans-fers than does the population as a wholeAs expected the targeting in-dicators are more favorable for primary education than for secondaryeducation and health with virtually none of the spending on tertiaryeducation benefiting the poor The share of reform pension outlaysthat reaches the poor also is minimal About a third of the outlays forthe minimum pension schemes do reach the poor but poor people stillreceive a lower share of these outlays relative to their proportion of thetotal population That suggests weaknesses in the targeting system forthese pensions About 40 percent of social assistance outlays reach thepoor but the targeting indicator is lower for other public subsidies andschooling stipends

bull Eradication of poverty The large bubble on the upper right corner on Fig-ure 131 represents the size of a perfectly targeted transfer that wouldbe sufficient to eradicate poverty (the coverage among the poor wouldbe 100 percent as would be the targeting among the poor since thetransfer would provide to each poor household exactly what is neededto lift the household to the poverty line) Pooling the resources from var-ious types of cash transfers could go a long way in reducing poverty if allthese resources were better targeted to the poor Aiming for perfectlytargeted transfers is obviously difficult in most cases (such as reformpensions which are meant to replace income lost by retirement) and wedo not recommend it because many of the transfers are meant to covera larger population than the poor Still overall only a small portion ofthe transfers typically reach poor people so the effect of those transferson the reduction of poverty is relatively limited

Following Angel-Urdinola and Wodon (2007) another way to look atbenefit incidence is to define a simple indicator of targeting performanceΩ which is the share of the subsidy benefits received by the poor (SP SH where SP denotes the value of all subsidies accruing to the poor andSH denotes the total value of the benefits received by the population as a



whole) divided by the proportion of the population in poverty (P Hwhere P denotes the number of poor households or individuals and H de-notes the number of households in the overall population In mathemati-cal notation we have

Ω = Sp Sh (131)P

H

A value of 100 for Ω implies that the subsidy distribution is neutralwith the share of benefits going to the poor proportional to their popu-lation share A value above (below) 100 for Ω implies that the subsidydistribution is progressive (regressive) the poor receive a larger (small-er) share of the benefits than their population share The smaller thenumber the more regressive it ismdashand vice versa

In our analysis we also provide data on the public transfer allocationsrsquoerrors of exclusion An error of exclusion occurs when a poor householddoes not benefit from a subsidy Denoting by Bp the proportion of house-holds who get the public transfer (that is the beneficiary incidence orcoverage level among the poor mentioned in the discussion of figure131) the share of poor households excluded from the subsidy is

Error of exclusion = 1 ndash Bp (132)

Figure 132 displays the value of the targeting performance indicator Ωas well as the errors of exclusion for the public transfers described aboveand for subsidies for the consumption of water and electricity (these val-ues are obtained from Angel-Urdinola and Wodon 2007) As before theresults suggest that public transfers related to primary education socialassistance minimum pensions and health care are the most pro-poor(that is the value of Ω is greater than 1) With the exception of primaryeducation and to some extent health care however program coverage isvery limited because the errors of exclusion are often high Other publictransfers (secondary education the public study fund that provides grantsfor schooling electricity and water subsidies reform pensions and terti-ary education) display values of Ω lower than 1 suggesting that resourcesare allocated more heavily to nonpoor households than to poor house-holds Most of the programs with low values for Ω also have very limitedcoverage as suggested by their high errors of exclusion



Factors That Determine Targeting Performance

The data presented above suggest that many poor households in CapeVerde do not receive a range of public transfers and that the values of thetargeting performance indicators Ω are often lower than 1 As Angel-Urdinola and Wodon (2007) described in detail for the case of water andelectricity subsidies there may be both ldquoaccessrdquo and ldquosubsidy designrdquo fac-tors that contribute to low targeting performance and poor coverage

Access factors can de divided into physical access (A) and usage or ldquotakeuprdquo of subsidies or services (U) Let AH represent the share of all house-holds having physical access to (or being eligible for) a transfer or serviceFor example access to primary education is available only in communitiesor geographic areas where there are schools Given access let UH|A be theshare of households who have physical access to a public transfer or serviceand choose to use it or are eligible for it (this could not occur for instanceif parents do not send their children to school because they canrsquot afford thefees or if eligible households do not receive a cash transfer to which theyare entitled because they lack information about the program)


Figure 132 Indicators of Targeting Performance

Source Authorsrsquo calculations

omega (share of benefits for the poorshare of the poor inpopulation) and error of exclusion ()

0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund

Electricity subsidies

Reform pensions

Tertiary education

Water subsidies

error of exclusion omega


Subsidy design factors are those that determine the final distributionalincidence of the transfer once we know who could benefit from the sub-sidy or transfer because the household has access to it and is using theserviceA first subsidy design factor is the targeting mechanism used TH|Uis defined as the share of households among those using a service that ac-tually get the public transfer (that is the beneficiary population amongthe population that potentially can benefit from the transfer because ithas access and is using the service)

A second subsidy design factor is the rate of subsidization R Denotethe average unit cost of the service by C (such as the average annual unitcost per student in primary school) C is assumed to be constant acrossall households The total cost of serving a customer is a function of C andof the quantity consumed (or the number of beneficiaries using the serv-ice) denoted by Q If the average quantity consumed by subsidy recipi-ents is QH|T and the average private expenditure on the good (such asco-payments for health care or education) is denoted by EH|T then theaverage rate of subsidization is RH|T = 1 ndash EH|T (QH|T C) As shown inAngel-Urdinola and Wodon (2007) the parameter Ω can be described asa product of five ratios as follows (denoting by P the poor)

Ω =AP

UP|A TP|U

RP|T QP|T (133)

AH UH|A TH|U RH|T QH|T

The first two ratios represent the service access rate among the poor di-vided by the access rate among the population as a whole followed by theusage rate for a service (given access) for the poor compared with the ratefor the population as a whole Typically one would expect that the ratioof access rates (A) would be lower than 1 because the poor tend to live inareas with lower access to public transfers and services than the popula-tion as a whole Similarly one would expect that the ratio of the usagerates for transfers and services (U) would be lower than 1 because a lackof information and perhaps a lack of funds makes poor people less likelyto use public services than is the population as a whole where there is ac-cess This ldquoaccess-factors handicaprdquo can be expected to work against thetargeting of public transfers to the poor Subsidy design factors will needto overcome the access handicap if the distribution of transfers is to beprogressive so that the value of Ω is larger than 1This result could be ob-served among others if targeting is good (among those using the servicethe poor are more likely to receive the public transfer than is the popula-



tion as a whole) if the unit reduction in price versus full cost received bythe poor is larger than for the nonpoor or if the poor are likely to con-sume more of the good than is the population as a whole when they havebeen found eligible for the transfer (for example the poor may have morechildren enrolled in public schools than does the total population)

Table 131 provides the results of the above Ω decomposition to ex-plain in more detail the key determinants of targeting performance forthe various public transfers observed in Cape Verdersquos household surveyFor primary education and health care which present values of Ω greaterthan 1 access generally is high among the poor (that is AP is close to 1 inboth cases) and usage rates are larger among the poor (that is UP|A gtUH|A) The latter finding probably arises because richer households canafford to choose to use private services for either education or health careWe find for instance that usage rates for primary education are 10 per-centage points higher than average among poor households and rates forhealth care are 3 percentage points higher As expected overall usagerates for education are higher than for health care (78ndash87 percent versus35ndash38 percent) because households are more likely to have children inthe education system than to have a member (presumably sick) activelyusing health services In terms of quantity consumed we find that the Qratios for primary education and health care are close to 1 For educationthe Q ratio is slightly above 1 for education because on average poorhouseholds are larger and thus more likely to have more children usingeducation services on a yearly basis (thus QP|T = 203 gt QH|T = 175) Forhealth care the ratio is slightly below 1 which is not surprising becausericher households usually have a higher average of effective health con-sultations per household each year (QP|T = 336 lt QH|T = 3422 these val-ues are high because the number of recent visits is annualized) For sec-ondary education the value of Ω is also slightly lower than 1 mainlystemming from a high Q ratio (QH|T = 16 gt QP|T = 15) which resultsfrom nonpoor households tending to have more children in secondaryschool Users of minimum pensions and social assistance programs whichalso display a value for Ω greater than 1 generally are poor householdsand thus AP UP gt AH UH Q ratios for these two programs on the con-trary are usually lower than 1 which suggests that on average richerhouseholds receive larger nominal benefits than do poor households

Other programs (public subsidies public study funds and social assis-tance programs) display Ω values below 1 For example it is striking tosee that social assistance programs are not well targeted and it would be



426

Ta

ble

13

1

De

com

po

siti

on

of

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term

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nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

nav

erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

ser

vice

(A)

who

use

ser

vice

(U|A

)su

bsid

y (T

|U)

(R|T

)co

nsum

ed (Q

|T)

(C)

Wa

ter

sub

sid

ies

Po

or

ho

use

ho

lds

05

20

20

10

00

40

33

63

50

All

ho

use

ho

lds

06

50

41

10

00

33

63

73

50

Rat

io0

79

04

91

00

11

90

53

35

0

Elec

tric

ity

sub

sid

ies

Po

or

ho

use

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07

20

34

10

00

11

56

83

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All

ho

use

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08

20

54

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06

11

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22

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31

00

17

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51

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Pri

ma

ry e

du

cati

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use

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10

00

08

77

10

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10

00

20

32

31

37

0

All

ho

use

ho

lds

10

00

07

80

10

00

10

00

17

51

31

37

0

Rat

io1

00

01

12

41

00

01

00

01

16

03

13

70

Sec

on

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cati

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Po

or

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lds

09

84

03

99

10

00

10

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15

14

27

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2

All

ho

use

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09

93

04

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15

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10

97

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00

01

00

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95

82

75

52

Tert

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Po

or

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use

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01

63

00

34

10

00

10

00

14

32

41

23

86

All

ho

use

ho

lds

02

72

00

91

10

00

10

00

11

06

41

23

86

Rat

io0

59

90

37

41

00

01

00

01

29

54

12

38

6


427

Hea

lth

ca

re

Po

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use

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lds

09

93

03

88

10

00

10

00

33

64

01

74

3

All

ho

use

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lds

09

94

03

58

10

00

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21

51

74

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Rat

io0

99

91

08

51

00

01

00

00

98

31

74

3

Prog

ram

(A x

U)

(T|U

)(R

|T)

(QC

|T)

Ref

orm

pen

sio

ns

Po

or

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use

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lds

00

97

10

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65

26

96

4

All

ho

use

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01

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30

Rat

io0

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41

00

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37

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Sub

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00

49

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28

89

20

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All

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use

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lds

00

71

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29

41

55

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Rat

io0

69

01

00

01

00

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98

2

Pu

blic

stu

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fun

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Po

or

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use

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00

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55

97

60

All

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use

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lds

00

10

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63

27

50

Rat

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81

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01

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91

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So

cia

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Po

or

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use

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lds

00

13

10

00

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24

54

59

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All

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use

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00

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32

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Rat

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75

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Min

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lds

00

70

10

00

10

00

31

73

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All

ho

use

ho

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00

47

10

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38

88

84

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Rat

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Sour

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ns


useful to learn why this is true by examining the various subprograms inthis category6 In any case contrary to what we observed for minimumpensions users of these various programs and transfers are more likely tobe nonpoor households and thereby AP UP lt AH UH) FurthermoreQ ratios for these programs are lower than 1 which suggests that richerhouseholds receive greater benefits on average As for utility services lowΩ values for electricity and water subsidies result from a combination ofdifferent subsidy rates and quantities consumed by poor and nonpoorhouseholds Although the rate of subsidization is greater for poor house-holds than for all households (RP|T = 011 versus RH|T = 006) the aver-age quantity (in kilowatt hours) consumed per month by poor house-holds connected to the network is less than half the quantity consumedin the population as a whole (QP|T = 4931 versus QH|T = 11172) Indeedbecause the system provides greater subsidies to households that con-sume less (the country implemented an inverted block tariffs scheme)this difference in consumption levels explains why the energy bills ofpoor households are more discounted than bills of other householdsHowever nonpoor households still receive a larger subsidy each monththan do the poor households because they consume more electricity andalmost all of their consumption is subsidized to some degree the productof RP|T RN|T QP|T QN|T is 0817

Improving Targeting Performance

Targeting is a relevant subsidy factor for improving the allocation of re-sources so that they become more beneficial for poor people There areseveral targeting mechanisms that policy makers can design to define cri-teria for public transfer eligibility Some of the more widely used mecha-nisms are geographic targeting (whereby benefits are allocated in locali-ties with high concentrations of poverty) quantity targeting (throughwhich benefits are allocated to users who consume smaller quantities ofservice) and proxy means testing (whereby benefit allocations are basedon the prediction of a householdrsquos poverty level reflected by certain visi-ble characteristics) Targeting mechanisms are well designed to the extentthey provide more accurate predictions of which households are poorer(and therefore in greater need of public transfers) In this section we an-alyze the predictive power of means-testing and geographic mechanisms



Proxy Means Testing to Predict Household Poverty

Proxy means-testing mechanisms rely on a method of predicting house-hold welfare based on visible characteristics Like the other targetingmethods proxy means testing may be used in combination with quantitytargeting or may be the sole basis for identifying subsidy beneficiaries

To design a proxy means-testing mechanism we relied on linear regres-sions to predict household welfare In particular we used the natural logof per capita expenditure as the dependent variable and we controlled forhousehold characteristics that may predict per capita consumption andthat are easily verifiable by a social worker These household-level vari-ables include the log of the household size (to allow for nonlinearity)whether the household head is female the age of the head and the agesquared the literacy and education levels of the head (the excluded cate-gory is a household head who has no education) and other infrastructurevariables (for example household access to electricity piped water and atoilet and a household dwellingrsquos type of walls floor and ceiling) We alsoincluded a vector of geographic variables (a set of geographic dummies forevery island) and dummies reflecting whether households possess a seriesof assets (television radio telephone oven refrigerator washing machinebicycle motorcycle and other motor vehicles)To maximize the predictivepower of our regression we relied on stepwise estimationThis method en-sures that the set of available variables included in our model provides thehighest possible fit as measured by the R2When the model was estimatedwe generated a predictor of the dependent variable Additionally we creat-ed a dummy variable (poor) that takes the value of 1 if the ldquoobservedrdquo valueof household per capita consumption is below the official poverty line(equivalent to CVEsc 432498 per capita annually) and a second dummy(predicted poor) that equals 1 if the ldquopredictedrdquo value of the householdrsquos percapita consumption fulfills the same condition

Regression results are available on request In general when makingstatistical predictions based on linear regressions two errors arise (Type Iand Type II errors) In our case the Type I error (error of exclusion) wouldconsist of excluding from a targeted program households that are poorbut are predicted to be nonpoor on the basis of the proxy means-testingmechanism and the Type II error (error of inclusion) would consist of al-locating program benefits to households that are nonpoor Findings ofhow well our model predicts poverty (and the size of the Type I and TypeII errors) are presented in table 132



In Cape Verde 281 percent of all households are poor As shown intable 132 our model rightly predicted as ldquopoorrdquo 175 percent of the ac-tual 281 percent and it wrongly predicted the remaining 106 percent(therefore the Type I error is equivalent to approximately 38 percent asa share of the predicted poor) Table 132 presents similar results for ur-ban and rural areas The Type I error is 46 percent in urban areas and 30percent in rural areas Although the share of incorrectly predicted poorhouseholds is somewhat high more information should be collected be-fore making a judgment of the model In particular the model still couldbe considered a good one to the extent that most of the households mis-predicted as poor are borderline nonpoor households (that is they are onlymarginally above the poverty line) Furthermore by changing the povertyline the magnitude of the errors also change We will conduct more de-tailed analyses of this issue below The Type II error of the model meas-ured by the poor households predicted to be nonpoor is approximately 10percent nationwide (4 percent in urban and 22 percent in rural areas)

We provide a more detailed analysis of the errors of inclusion and ex-clusion by using a prediction matrix based on population decile (ratherthan on household decile) of per capita consumption (table 133) CapeVerdersquos 281 percent poor households are equivalent to 367 percent ofthe population (25 percent urban and 51 percent rural) For simplicityrsquossake in identifying the poor population we used the third fourth andfifth deciles of per capita consumption (weighted by the populationweights) as our new poverty lines at the urban national and rural levelsrespectively According to the matrix errors of exclusion are 100 per-


Table 132 Errors of Exclusion and Inclusion in a Proxy Means-Testing Model

All households

Targeting indicator National Urban Rural

Poor predicted poor 0175 0095 0295

Poor predicted nonpoor 0106 0080 0125

Error of exclusion 0377 0459 0298

Nonpoor predicted nonpoor 0651 0793 0451

Nonpoor predicted poor 0069 0032 0129

Error of inclusion 0095 0039 0222

Sample size (number of households) 4583 2463 2120

Weighted sample size 95237 54283 40954



431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

17

90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on


cent 85 percent and 135 percent at the national urban and rural lev-els respectively Almost half of the individuals excluded (poor but pre-dicted nonpoor) are borderline poor The magnitude of the errors of in-clusion is similar to that of the errors of exclusion Most of the nonpoorhouseholds ldquowronglyrdquo predicted are also borderline nonpoor (that is theyare only a little above the poverty line)

Now we turn to exploring how sensitive the prediction model is to thechoice of poverty line To do so we ranked our welfare predictor from thelowest to the highest Using household weights and size (and conserving theranking) we calculated the share of the total population represented byeach household in the surveyWe defined as ldquopredicted poorrdquo all householdsbelow our choice of poverty line (we used 20 30 40 and 50 percent of thecumulative population distribution of the predictor respectively) The realldquopoorrdquo (approximately 37 percent) are those households with observed percapita incomes below the official poverty linemdashthat is below CVEsc432498 per capita annually Our results are summarized in table 134


Table 134 Means-testing Performance under Different Poverty Lines

All households

Poor Poor Nonpoor NonpoorSample considered predicted predicted predicted predictedpoor () poor () nonpoor () poor () nonpoor ()

National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599



As suggested in table 134 using a cutoff point of 40 percent of thepredicted poor (the benchmark case because the actual poverty rate is 37 percent) the model gives a good prediction of poor households espe-cially in urban areas Urban poverty predictions are more accurate mainlybecause urban households show a larger dispersion in terms of consump-tion as well as asset levels than do rural households which increases thepower of the proxy means-testing mechanism Using higher (lower) cut-off points results in a higher (lower) share of the actual ldquopoorrdquo being pre-dicted poor especially in urban areas Of course a higher (lower) cut-offpoint increases (decreases) the probability that the model fails to excludenonpoor households from the targeted program That may contribute toan overinvestment (underinvestment) of social funds because the percent-age of nonpoor households predicted to be poor becomes larger (smaller)

Geographic Targeting to Predict Household Poverty

Using census data and the Cape Verde poverty map (which predicts percapita expenditure for all households included in the census) we rankedall districts in the country from the one with the highest average povertyrate to the one with the lowest rate We then calculated the overall popu-lation share in every district Keeping the rank constant we calculated thecumulative population distribution All households belonging to theprovinces below 20 30 40 and 50 percent of the population distributionwere predicted as ldquogeographically poorrdquo

As suggested by table 135 geographic targeting like proxy means test-ing has a better predictive power in urban than in rural areas By imple-menting this method and assuming poverty rates of 20 30 40 and 50percent of the population respectively we could predict correctly only28 percent of the poor households in rural areas (versus 47 percent in ur-ban areas) 40 percent (versus 61 percent) 51 percent (versus 72 per-cent) and 62 percent (versus 82 percent) This result is not surprising be-cause the urban poor population usually is concentrated in slum districtswhereas poor households are more widely dispersed in rural districts

As table 136 suggests proxy means testing offers a better targetingmechanism than does geographical targeting at the national urban andrural levels when all households in the survey and census are included inthe analysis This is true because both the errors of inclusion and the er-rors of exclusion are smaller using proxy means-testing mechanisms thanusing geographic targeting methods in all scenarios This is to be expected



because the proxy means-testing model controls not only for locality fac-tors but also for other variables that predict welfare such as type of hous-ing characteristics and demographics

Conclusion

Cape Verde spends heavily on public transfers especially for health careeducation and pensions Although large government spending in the so-cial sectors has made the country one of the best performers in WestAfrica regarding the delivery of services in those sectors the system needsto improve the efficiency of its spending to ensure its sustainability Thecountryrsquos expenditures on primary education and health care constitute alarge share of overall public transfers in nominal terms and they are quitepro-poor However other components of the social protection network(such as pensions public subsidies public study funding utility subsidiesand higher education) are not reaching the poor adequately


Table 135 Geographic Targeting Using Census Data

All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863


Note The actual ldquopoorrdquoare defined as those households having annual consumption below CVEsc 432498 per

capita (the official poverty line)


The targeting performance of public transfers in Cape Verde has a natu-ral distributional handicap because poor households usually have an accessdisadvantage they are limited in access to infrastructure and informationand they still cannot afford the services To overcome this handicap policymakers must pay attention to the performance of subsidy-design factors(such as targeting mechanisms and rates of subsidization) Results forCape Verde indicate that apart from primary education and health care(services with high rates of access and use among poor people) publictransfers are not being allocated in a pro-poor manner because of a combi-nation of disadvantageous access factors among the poor and poorly per-forming design factors (especially involving targeting mechanisms)

Finally proxy means testing generally has better predictive power thandoes geographic targeting especially in rural areas where poverty is wide-spread In urban areas the predictive advantage of means testing over ge-ographic targeting is lower probably because urban poverty is concentrat-


Table 136 Geographical Targeting Versus Proxy Means Testing

Geographical targeting Proxy means testingusing census using survey

Share of the sample Error of Error of Error of Error ofconsidered poor () inclusion () exclusion () inclusion () exclusion ()

Full sample Full sample

National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815

Source Authorsrsquo estimation

Note The actual ldquopoorrdquounder means testing are defined as those households having per capita consumption

below CVEsc 432498 annually (the official poverty line)


ed in slums This poses a natural trade-off because policy makers con-strained by tight budgets may choose to implement geographic targetingeven when it sacrifices some predictive power8

Notes

1 There is a large body of literature in this area Several studies have been devot-ed to assessing the targeting performance of a wide range of programs in devel-oping and transition economies (for example Grosh 1994 Subbarao et al1997 Braithwaite Grootaert and Milanovic 2000 and Coady Grosh andHoddinott 2004) In the case of utilities such as water and electricity althoughsubsidies are very widespread it is not clear that they are well targeted(Wodon Ajwad and Siaens 2003 Komives et al 2005 Angel-Urdinola Cos-grove-Davies and Wodon 2006 and Angel-Urdinola and Wodon 2007) Thisfinding is problematic given that utility subsidies in developing and transitioneconomies often are more costly than other transfer programs (Alderman2002)

2 Life expectancy at birth is 701 years child mortality is 42 per 1000 live birthsamong boys and 30 per 1000 live births among girls and the maternal mortal-ity ratio was 150 to 100000 live births in 2000 (see World Bank 2005 for moredetails) These figures reflect both the relatively high income per capita inCape Verde and the high share of public spending devoted to health care

3 For a good discussion of standard benefit incidence analysis see Demery (2003)

4 There are two noncontributory social security schemesmdashone for people inthe Food for Work (FAIMO) public works program and one for other elderlyor disabled people FAIMO is a labor-intensive infrastructure works programfinanced with food aid counterpart funds that employs approximately15000 to 20000 people annuallyThe aim of this program is to provide someincome security to the poor especially those people who live in rural areasand women who are heads of household In 1992 a noncontributory pensionscheme was introduced for workers in FAIMO All elderly people who haveworked at least 10 years in campaigns funded by the government are covered(44 percent of the FAIMO workers have at least 10 yearsrsquo tenure) and inva-lidity and old-age pensions are provided All FAIMO pensioners receive afixed annual pension equivalent to $300 The Minimum Social Protection(PSM) scheme is a noncontributory means-tested program set up in 1995 toprovide income for people not covered by the other social protection pro-gram The PSM is fully financed with resources from official development as-sistance Approximately 7000 families receive pensions from the PSM pri-



marily elderly people and families in economic distress who are not coveredunder other pension schemes

5 Following the methodology used by the National Institute of Statistics inCape Verde a household is considered poor if its annual per capita consump-tion falls below the official poverty line (equivalent to CVEsc 432498 percapita a year) With that poverty line 367 percent of the population is poor(equivalent to 280 percent of households)

6 Unfortunately the requisite information for such a study is not included inthe survey data

7 For a more detailed discussion on the targeting performance of utility tariffsin Cape Verde see Wodon et al (2007)

8 The cost of implementing proxy means testing is usually higher because it re-quires the involvement of social workers and the use of data processing

References

Alderman Harold 2002 ldquoSubsidies as a Social Safety Net Effectiveness and Chal-lengesrdquo Social Safety Net Primer Series Discussion Paper 0224 World BankWashington DC

Angel-Urdinola Diego M Cosgrove-Davies and Q Wodon 2006 ldquoRwanda Elec-tricity Tariff Reformrdquo In Poverty and Social Impact Analysis of Reforms Lessonsand Examples from Implementation ed Aline Coudouel A Dani and S Pater-nostro 235ndash56 Washington DC World Bank

Angel-Urdinola Diego and Quentin Wodon 2007 ldquoDo Utility Subsidies Reachthe Poor Framework and Evidence for Cape Verde Sao Tome and RwandardquoEconomics Bulletin 94 (4) 1ndash7

Braithwaite Jeanine C Grootaert and B Milanovic 2000 Poverty and Social Assis-tance in Transition Countries New York Palgrave Macmillan

Coady David M Grosh and J Hoddinott 2004 ldquoTargeting Outcomes ReduxrdquoWorld Bank Research Observer 19 (1) 61ndash85

Demery Lionel 2003 ldquoAnalyzing the Incidence of Public Spendingrdquo In The Impactof Economic Policies on Poverty and Income Distribution Evaluation Techniquesand Tools ed Franccediloise Bourguignon and Luis A Pereira da Silva 41ndash68Wash-ington DC World Bank

Grosh Margaret 1994 Administering Targeted Social Programs in Latin AmericaFrom Platitudes to Practice Washington DC World Bank



Komives Kristin V Foster J Halpern Q Wodon and R Abdullah 2005 WaterElectricity and the Poor Who Benefits from Utility Subsidies Washington DCWorld Bank

Subbarao Kalanidhi A Bonnerjee J Braithwaite S Carvalho K Ezemenari CGraham and A Thompson 1997 Safety Net Programs and Poverty ReductionLessons from Cross-Country Experience Washington DC World Bank

Wodon Quentin M I Ajwad and C Siaens 2003 ldquoLifeline or Means TestingElectric Utility Subsidies in Hondurasrdquo In Infrastructure for the Poor People Pub-lic Policy for Private Provision ed P Brook and T Irwin 277ndash96 WashingtonDC World Bank

Wodon Quentin D Angel-Urdinola D Echevlin M Francisco and P Meier2007 ldquoEnergy Subsidies Electricity Tariffs and the Poor in Cape VerderdquoWorldBank Washington DC

Wodon Quentin and Xiao Ye 2006 ldquoBenefit Incidence Analysis Adjusted forNeeds and Costs Assessing the Equity of Public Education Spending in SierraLeonerdquo World Bank Washington DC

World Bank 2005 ldquoCape Verde Poverty Diagnosticrdquo Report 32826-CV WorldBank Washington DC

mdashmdashmdash 2007 ldquoCape Verde The Challenge of Increasing Fiscal Space to Meet Fu-ture Pressures (Public Expenditure Review)rdquo Report 34523-CV World BankWashington DC



Budget constraints faced by governments in developing countries implythat effectively targeting performance of public subsidies and social pro-grams (whether the subsidies are provided in cash or in kind) is impor-tant in reducing povertyThere are three main advantages to effective tar-geting First for programs not intended to offer universal coverage bettertargeting helps reduce program outlay because there are fewer benefici-aries Second for any given level of outlay better targeting suggests thatthe share of public expenditure that accrues to poor people typically willbe higher and so will enable the programs to have a larger impact onpovertyThird targeting may help reduce the potential negative incentiveeffects or distortions in economic behavior associated with transfers iffewer households are affected by the programs For example if fewerhouseholds benefit from subsidized water or electricity service there willbe less incentive to consume more than would be consumed normally ifthe full cost of the service were paid by the household Too much target-ing however can produce negative incentive effects In some industrialcountries transfers may lead to poverty traps whereby the incentives forsome households to emerge from poverty are lessened by high implicittaxation rates associated with increased income and decreased transfers

C H A P T E R 1 3

Assessing the Targeting Performance

of Social Programs

Cape Verde


417























10

07

04

01

ndash02

rea

ch a

mo

ng

th

e p

oo

r (

of

the

po

or

wh

o b

en

efi

t fr

om

th

e s

ou

rce

)

0 025 050 075 100



secondaryeducation

health carereform


minimum pension


social assistance









Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

Ta

ble

13

1

De

com

po

siti

on

of

De

term

ina

nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

nav

erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

ser

vice

(A)

who

use

ser

vice

(U|A

)su

bsid

y (T

|U)

(R|T

)co

nsum

ed (Q

|T)

(C)

Wa

ter

sub

sid

ies

Po

or

ho

use

ho

lds

05

20

20

10

00

40

33

63

50

All

ho

use

ho

lds

06

50

41

10

00

33

63

73

50

Rat

io0

79

04

91

00

11

90

53

35

0

Elec

tric

ity

sub

sid

ies

Po

or

ho

use

ho

lds

07

20

34

10

00

11

56

83

20

5

All

ho

use

ho

lds

08

20

54

10

00

06

11

17

22

05

Rat

io0

88

06

31

00

17

00

51

20

5

Pri

ma

ry e

du

cati

on

Po

or

ho

use

ho

lds

10

00

08

77

10

00

10

00

20

32

31

37

0

All

ho

use

ho

lds

10

00

07

80

10

00

10

00

17

51

31

37

0

Rat

io1

00

01

12

41

00

01

00

01

16

03

13

70

Sec

on

da

ry e

du

cati

on

Po

or

ho

use

ho

lds

09

84

03

99

10

00

10

00

15

14

27

55

2

All

ho

use

ho

lds

09

93

04

08

10

00

10

00

15

81

27

55

2

Rat

io0

99

10

97

81

00

01

00

00

95

82

75

52

Tert

iary

ed

uca

tio

n

Po

or

ho

use

ho

lds

01

63

00

34

10

00

10

00

14

32

41

23

86

All

ho

use

ho

lds

02

72

00

91

10

00

10

00

11

06

41

23

86

Rat

io0

59

90

37

41

00

01

00

01

29

54

12

38

6


427

Hea

lth

ca

re

Po

or

ho

use

ho

lds

09

93

03

88

10

00

10

00

33

64

01

74

3

All

ho

use

ho

lds

09

94

03

58

10

00

10

00

34

21

51

74

3

Rat

io0

99

91

08

51

00

01

00

00

98

31

74

3

Prog

ram

(A x

U)

(T|U

)(R

|T)

(QC

|T)

Ref

orm

pen

sio

ns

Po

or

ho

use

ho

lds

00

97

10

00

10

00

65

26

96

4

All

ho

use

ho

lds

01

02

10

00

10

00

17

51

55

30

Rat

io0

95

41

00

01

00

00

37

3

Sub

sid

ies

Po

or

ho

use

ho

lds

00

49

10

00

10

00

28

89

20

4

All

ho

use

ho

lds

00

71

10

00

10

00

29

41

55

8

Rat

io0

69

01

00

01

00

00

98

2

Pu

blic

stu

dy

fun

d

Po

or

ho

use

ho

lds

00

06

10

00

10

00

11

55

97

60

All

ho

use

ho

lds

00

10

10

00

10

00

12

63

27

50

Rat

io0

63

81

00

01

00

00

91

5

So

cia

l ass

ista

nce

Po

or

ho

use

ho

lds

00

13

10

00

10

00

24

54

59

8

All

ho

use

ho

lds

00

06

10

00

10

00

32

72

18

4

Rat

io2

03

91

00

01

00

00

75

0

Min

imu

m p

ensi

on

Po

or

ho

use

ho

lds

00

70

10

00

10

00

31

73

49

0

All

ho

use

ho

lds

00

47

10

00

10

00

38

88

84

0

Rat

io1

48

61

00

01

00

00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

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68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

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37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

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00

10

00

00

00

76

22

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28

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29

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74

03

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17

00

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00

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50

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97

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61

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09

20

31

01

00

06

00

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77

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96

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13

12

92

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00

00

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85

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91

19

20

78

01

50

00

70

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10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

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t p

ag

e


432

Ta

ble

13

3c

on

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ued

100

Per c

apita

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ror o

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iture

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ile1

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45

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89

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clus

ion

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80

00

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20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

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09

17

83

52

23

80

00

10

00

00

00

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00

11

02

70

04

04

50

39

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61

00

0

Erro

r o

f e

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sio

n1

23

24

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76

00

00

00

00

00

00

00

00

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00

0

Rura

l are

as

14

20

18

61

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94

03

70

23

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70

02

00

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14

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07

10

58

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00

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31

79

15

11

88

12

40

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67

05

10

14

00

62

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87

13

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85

06

30

55

02

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91

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14

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90

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02

24

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91

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71

28

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00

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09

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53

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12

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05

90

00

80

00

05

60

63

10

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62

07

51

44

14

82

08

13

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00

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00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References








































10

07

04

01

ndash02

rea

ch a

mo

ng

th

e p

oo

r (

of

the

po

or

wh

o b

en

efi

t fr

om

th

e s

ou

rce

)

0 025 050 075 100



secondaryeducation

health carereform


minimum pension


social assistance









Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

Ta

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Ratio

of s

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of s

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s w

ithof

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lds

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of s

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of

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of

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of

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t cos

tco

mm

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cess

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ith a

cces

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ers

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ive

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ogra

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Sour

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All households












431

Ta

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13

3

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lfa

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trix

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ror o

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iona

l

14

48

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13

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60

15

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69

31

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22

21

18

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02

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01

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05

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08

91

26

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93

10

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07

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17

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71

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02

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06

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03

03

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31

03

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09

51

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14

07

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01

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02

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0

Erro

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15

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76

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00

con

tin

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on

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t p

ag

e


432

Ta

ble

13

3c

on

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100

Per c

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ion

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an a

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80

00

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20

16

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00

77

16

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43

28

61

98

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40

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00

00

00

14

02

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43

04

31

09

17

83

52

23

80

00

10

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00

00

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11

02

70

04

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50

39

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61

00

0

Erro

r o

f e

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sio

n1

23

24

94

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00

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Rura

l are

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14

20

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35

08

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02

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31

79

15

11

88

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67

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13

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70

11

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85

06

30

55

02

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00

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50

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12

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00

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00

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63

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62

07

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44

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00

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00

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05

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83

09

01

58

18

82

14

19

00

00

10

00

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00

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40

49

02

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59

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r o

f e

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sio

n0

72

25

82

32

39

83

83

00

00

00

00

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00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References

































10

07

04

01

ndash02

rea

ch a

mo

ng

th

e p

oo

r (

of

the

po

or

wh

o b

en

efi

t fr

om

th

e s

ou

rce

)

0 025 050 075 100



secondaryeducation

health carereform


minimum pension


social assistance









Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

Ta

ble

13

1

De

com

po

siti

on

of

De

term

ina

nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

nav

erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

ser

vice

(A)

who

use

ser

vice

(U|A

)su

bsid

y (T

|U)

(R|T

)co

nsum

ed (Q

|T)

(C)

Wa

ter

sub

sid

ies

Po

or

ho

use

ho

lds

05

20

20

10

00

40

33

63

50

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use

ho

lds

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50

41

10

00

33

63

73

50

Rat

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79

04

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00

11

90

53

35

0

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tric

ity

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ies

Po

or

ho

use

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lds

07

20

34

10

00

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56

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20

5

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use

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08

20

54

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00

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11

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22

05

Rat

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88

06

31

00

17

00

51

20

5

Pri

ma

ry e

du

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on

Po

or

ho

use

ho

lds

10

00

08

77

10

00

10

00

20

32

31

37

0

All

ho

use

ho

lds

10

00

07

80

10

00

10

00

17

51

31

37

0

Rat

io1

00

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12

41

00

01

00

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16

03

13

70

Sec

on

da

ry e

du

cati

on

Po

or

ho

use

ho

lds

09

84

03

99

10

00

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00

15

14

27

55

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93

04

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00

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97

81

00

01

00

00

95

82

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431

Ta

ble

13

3

We

lfa

re P

red

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trix

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apita

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10

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02

00

37

06

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50

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03

03

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31

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09

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96

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14

07

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00

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Erro

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15

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ag

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432

Ta

ble

13

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00

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00

00

00

14

02

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04

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17

83

52

23

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00

10

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00

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04

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f e

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00

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0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

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31

79

15

11

88

12

40

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90

67

05

10

14

00

62

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13

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85

06

30

55

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91

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14

01

31

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90

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02

24

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02

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00

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24

09

50

53

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12

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05

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00

80

00

05

60

63

10

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62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

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00

10

00

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00

01

40

49

02

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59

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0

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r o

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00

00

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00

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0

Sour

ceA

uth

ors

rsquoest

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es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

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l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References

























10

07

04

01

ndash02

rea

ch a

mo

ng

th

e p

oo

r (

of

the

po

or

wh

o b

en

efi

t fr

om

th

e s

ou

rce

)

0 025 050 075 100



secondaryeducation

health carereform


minimum pension


social assistance









Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

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Sour

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All households












431

Ta

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432

Ta

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52

23

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Erro

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e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References


























Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

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13

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ith a

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6

Sour

ceA

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tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

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ile1

23

45

67

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10in

clus

ion

Nat

iona

l

14

48

25

41

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07

00

35

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05

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20

01

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13

61

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60

15

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01

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31

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22

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02

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01

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02

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40

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04

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13

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05

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57

08

91

26

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16

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93

10

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07

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09

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17

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71

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02

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06

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98

17

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22

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68

03

50

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80

03

03

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31

03

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94

09

51

96

21

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14

07

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00

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0

Erro

r o

f e

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n1

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an a

reas

15

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76

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19

20

78

01

50

00

70

10

03

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44

10

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36

16

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01

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50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

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ror o

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pend

iture

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ile1

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clus

ion

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an a

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80

00

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16

04

00

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16

51

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28

61

98

06

40

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90

00

00

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14

02

40

43

04

31

09

17

83

52

23

80

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10

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00

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04

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50

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61

00

0

Erro

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f e

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sio

n1

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24

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0

Rura

l are

as

14

20

18

61

35

08

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94

03

70

23

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02

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22

11

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14

11

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10

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04

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31

79

15

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05

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00

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13

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11

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85

06

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78

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28

14

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51

20

02

10

00

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24

09

50

53

08

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12

41

32

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05

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00

80

00

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63

10

80

62

07

51

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14

82

08

13

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00

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00

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20

11

05

50

83

09

01

58

18

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14

19

00

00

10

00

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00

01

40

49

02

80

59

05

60

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17

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0

Erro

r o

f e

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sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References




















Ω = Sp Sh (131)P

H














0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

Ta

ble

13

1

De

com

po

siti

on

of

De

term

ina

nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

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erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

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vice

(A)

who

use

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vice

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bsid

y (T

|U)

(R|T

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nsum

ed (Q

|T)

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Po

or

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use

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05

20

20

10

00

40

33

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All

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41

10

00

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0

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70

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on

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Po

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Rat

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52

Tert

iary

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All

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Rat

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427

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Prog

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0

Min

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10

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49

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All

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use

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10

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00

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84

0

Rat

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48

61

00

01

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00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

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ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

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432

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ble

13

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100

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0

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r o

f e

xclu

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n0

72

25

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32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References


























0 02 04 06 0 8 10 12 14 16 18

pro

gra

m

Primary education

Social assistance

Minimum pension

Health care

Secondary education

Public subsidies

Public study fund


Reform pensions

Tertiary education

Water subsidies





Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

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431

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432

Ta

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Sour

ceA

uth

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rsquoest

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es

Not

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ells

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l po

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lati

on

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e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

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err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References





















Ω =AP

UP|A TP|U

RP|T QP|T (133)










426

Ta

ble

13

1

De

com

po

siti

on

of

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term

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of

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c T

ran

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Ratio

of s

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of s

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hou

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of s

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of

Ratio

of

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of

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t cos

tco

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unit

y ac

cess

w

ith a

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erag

e qu

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VEsc

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(A)

who

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Po

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(QC

|T)

Ref

orm

pen

sio

ns

Po

or

ho

use

ho

lds

00

97

10

00

10

00

65

26

96

4

All

ho

use

ho

lds

01

02

10

00

10

00

17

51

55

30

Rat

io0

95

41

00

01

00

00

37

3

Sub

sid

ies

Po

or

ho

use

ho

lds

00

49

10

00

10

00

28

89

20

4

All

ho

use

ho

lds

00

71

10

00

10

00

29

41

55

8

Rat

io0

69

01

00

01

00

00

98

2

Pu

blic

stu

dy

fun

d

Po

or

ho

use

ho

lds

00

06

10

00

10

00

11

55

97

60

All

ho

use

ho

lds

00

10

10

00

10

00

12

63

27

50

Rat

io0

63

81

00

01

00

00

91

5

So

cia

l ass

ista

nce

Po

or

ho

use

ho

lds

00

13

10

00

10

00

24

54

59

8

All

ho

use

ho

lds

00

06

10

00

10

00

32

72

18

4

Rat

io2

03

91

00

01

00

00

75

0

Min

imu

m p

ensi

on

Po

or

ho

use

ho

lds

00

70

10

00

10

00

31

73

49

0

All

ho

use

ho

lds

00

47

10

00

10

00

38

88

84

0

Rat

io1

48

61

00

01

00

00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

17

90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References
























426

Ta

ble

13

1

De

com

po

siti

on

of

De

term

ina

nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

nav

erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

ser

vice

(A)

who

use

ser

vice

(U|A

)su

bsid

y (T

|U)

(R|T

)co

nsum

ed (Q

|T)

(C)

Wa

ter

sub

sid

ies

Po

or

ho

use

ho

lds

05

20

20

10

00

40

33

63

50

All

ho

use

ho

lds

06

50

41

10

00

33

63

73

50

Rat

io0

79

04

91

00

11

90

53

35

0

Elec

tric

ity

sub

sid

ies

Po

or

ho

use

ho

lds

07

20

34

10

00

11

56

83

20

5

All

ho

use

ho

lds

08

20

54

10

00

06

11

17

22

05

Rat

io0

88

06

31

00

17

00

51

20

5

Pri

ma

ry e

du

cati

on

Po

or

ho

use

ho

lds

10

00

08

77

10

00

10

00

20

32

31

37

0

All

ho

use

ho

lds

10

00

07

80

10

00

10

00

17

51

31

37

0

Rat

io1

00

01

12

41

00

01

00

01

16

03

13

70

Sec

on

da

ry e

du

cati

on

Po

or

ho

use

ho

lds

09

84

03

99

10

00

10

00

15

14

27

55

2

All

ho

use

ho

lds

09

93

04

08

10

00

10

00

15

81

27

55

2

Rat

io0

99

10

97

81

00

01

00

00

95

82

75

52

Tert

iary

ed

uca

tio

n

Po

or

ho

use

ho

lds

01

63

00

34

10

00

10

00

14

32

41

23

86

All

ho

use

ho

lds

02

72

00

91

10

00

10

00

11

06

41

23

86

Rat

io0

59

90

37

41

00

01

00

01

29

54

12

38

6


427

Hea

lth

ca

re

Po

or

ho

use

ho

lds

09

93

03

88

10

00

10

00

33

64

01

74

3

All

ho

use

ho

lds

09

94

03

58

10

00

10

00

34

21

51

74

3

Rat

io0

99

91

08

51

00

01

00

00

98

31

74

3

Prog

ram

(A x

U)

(T|U

)(R

|T)

(QC

|T)

Ref

orm

pen

sio

ns

Po

or

ho

use

ho

lds

00

97

10

00

10

00

65

26

96

4

All

ho

use

ho

lds

01

02

10

00

10

00

17

51

55

30

Rat

io0

95

41

00

01

00

00

37

3

Sub

sid

ies

Po

or

ho

use

ho

lds

00

49

10

00

10

00

28

89

20

4

All

ho

use

ho

lds

00

71

10

00

10

00

29

41

55

8

Rat

io0

69

01

00

01

00

00

98

2

Pu

blic

stu

dy

fun

d

Po

or

ho

use

ho

lds

00

06

10

00

10

00

11

55

97

60

All

ho

use

ho

lds

00

10

10

00

10

00

12

63

27

50

Rat

io0

63

81

00

01

00

00

91

5

So

cia

l ass

ista

nce

Po

or

ho

use

ho

lds

00

13

10

00

10

00

24

54

59

8

All

ho

use

ho

lds

00

06

10

00

10

00

32

72

18

4

Rat

io2

03

91

00

01

00

00

75

0

Min

imu

m p

ensi

on

Po

or

ho

use

ho

lds

00

70

10

00

10

00

31

73

49

0

All

ho

use

ho

lds

00

47

10

00

10

00

38

88

84

0

Rat

io1

48

61

00

01

00

00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

17

90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References



















426

Ta

ble

13

1

De

com

po

siti

on

of

De

term

ina

nts

of

Pu

bli

c T

ran

sfe

rs P

erf

orm

an

ce

Ratio

of s

hare

Ratio

of s

hare

of h

ouse

hold

s w

ithof

hou

seho

lds

Ratio

of s

hare

of

Ratio

of

Ratio

of

Uni

t cos

tco

mm

unit

y ac

cess

w

ith a

cces

sus

ers

who

rece

ive

subs

idiz

atio

nav

erag

e qu

antit

y(C

VEsc

)Pr

ogra

mto

ser

vice

(A)

who

use

ser

vice

(U|A

)su

bsid

y (T

|U)

(R|T

)co

nsum

ed (Q

|T)

(C)

Wa

ter

sub

sid

ies

Po

or

ho

use

ho

lds

05

20

20

10

00

40

33

63

50

All

ho

use

ho

lds

06

50

41

10

00

33

63

73

50

Rat

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79

04

91

00

11

90

53

35

0

Elec

tric

ity

sub

sid

ies

Po

or

ho

use

ho

lds

07

20

34

10

00

11

56

83

20

5

All

ho

use

ho

lds

08

20

54

10

00

06

11

17

22

05

Rat

io0

88

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31

00

17

00

51

20

5

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ma

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du

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on

Po

or

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lds

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00

08

77

10

00

10

00

20

32

31

37

0

All

ho

use

ho

lds

10

00

07

80

10

00

10

00

17

51

31

37

0

Rat

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00

01

12

41

00

01

00

01

16

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13

70

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on

da

ry e

du

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on

Po

or

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ho

lds

09

84

03

99

10

00

10

00

15

14

27

55

2

All

ho

use

ho

lds

09

93

04

08

10

00

10

00

15

81

27

55

2

Rat

io0

99

10

97

81

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01

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82

75

52

Tert

iary

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n

Po

or

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lds

01

63

00

34

10

00

10

00

14

32

41

23

86

All

ho

use

ho

lds

02

72

00

91

10

00

10

00

11

06

41

23

86

Rat

io0

59

90

37

41

00

01

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01

29

54

12

38

6


427

Hea

lth

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re

Po

or

ho

use

ho

lds

09

93

03

88

10

00

10

00

33

64

01

74

3

All

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use

ho

lds

09

94

03

58

10

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10

00

34

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51

74

3

Rat

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91

08

51

00

01

00

00

98

31

74

3

Prog

ram

(A x

U)

(T|U

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Po

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lds

00

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10

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10

00

65

26

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4

All

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00

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30

Rat

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41

00

01

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37

3

Sub

sid

ies

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ho

lds

00

49

10

00

10

00

28

89

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4

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ho

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lds

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71

10

00

10

00

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41

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8

Rat

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01

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01

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98

2

Pu

blic

stu

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or

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lds

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06

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00

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00

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55

97

60

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ho

use

ho

lds

00

10

10

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10

00

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63

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50

Rat

io0

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81

00

01

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91

5

So

cia

l ass

ista

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use

ho

lds

00

13

10

00

10

00

24

54

59

8

All

ho

use

ho

lds

00

06

10

00

10

00

32

72

18

4

Rat

io2

03

91

00

01

00

00

75

0

Min

imu

m p

ensi

on

Po

or

ho

use

ho

lds

00

70

10

00

10

00

31

73

49

0

All

ho

use

ho

lds

00

47

10

00

10

00

38

88

84

0

Rat

io1

48

61

00

01

00

00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

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90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References



















427

Hea

lth

ca

re

Po

or

ho

use

ho

lds

09

93

03

88

10

00

10

00

33

64

01

74

3

All

ho

use

ho

lds

09

94

03

58

10

00

10

00

34

21

51

74

3

Rat

io0

99

91

08

51

00

01

00

00

98

31

74

3

Prog

ram

(A x

U)

(T|U

)(R

|T)

(QC

|T)

Ref

orm

pen

sio

ns

Po

or

ho

use

ho

lds

00

97

10

00

10

00

65

26

96

4

All

ho

use

ho

lds

01

02

10

00

10

00

17

51

55

30

Rat

io0

95

41

00

01

00

00

37

3

Sub

sid

ies

Po

or

ho

use

ho

lds

00

49

10

00

10

00

28

89

20

4

All

ho

use

ho

lds

00

71

10

00

10

00

29

41

55

8

Rat

io0

69

01

00

01

00

00

98

2

Pu

blic

stu

dy

fun

d

Po

or

ho

use

ho

lds

00

06

10

00

10

00

11

55

97

60

All

ho

use

ho

lds

00

10

10

00

10

00

12

63

27

50

Rat

io0

63

81

00

01

00

00

91

5

So

cia

l ass

ista

nce

Po

or

ho

use

ho

lds

00

13

10

00

10

00

24

54

59

8

All

ho

use

ho

lds

00

06

10

00

10

00

32

72

18

4

Rat

io2

03

91

00

01

00

00

75

0

Min

imu

m p

ensi

on

Po

or

ho

use

ho

lds

00

70

10

00

10

00

31

73

49

0

All

ho

use

ho

lds

00

47

10

00

10

00

38

88

84

0

Rat

io1

48

61

00

01

00

00

81

6

Sour

ceA

uth

ors

rsquocal

cula

tio

ns

















All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

17

90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References


































All households












431

Ta

ble

13

3

We

lfa

re P

red

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on

Ma

trix

100

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apita

Er

ror o

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pend

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dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

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n1

15

22

82

87

37

30

00

00

00

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00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

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35

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96

03

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08

00

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00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

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00

70

10

03

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44

10

11

36

16

12

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50

00

con

tin

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on

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e


432

Ta

ble

13

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100

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ror o

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23

45

67

89

10in

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Urb

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80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

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00

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0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

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12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

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90

85

06

30

55

02

23

54

50

38

11

10

94

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91

56

14

01

31

13

90

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02

24

78

60

48

09

50

91

09

71

28

14

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48

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51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

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00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

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40

49

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59

05

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82

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32

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0

Erro

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72

25

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39

83

83

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00

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0

Sour

ceA

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es

Not

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pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References





























All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

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pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

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n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

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50

21

11

97

23

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59

09

20

31

01

00

06

00

05

34

40

77

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96

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08

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16

09

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13

12

92

03

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31

00

00

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20

01

00

85

12

41

21

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01

91

19

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50

00

70

10

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tin

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e


432

Ta

ble

13

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80

00

01

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00

77

16

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28

61

98

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00

00

00

14

02

40

43

04

31

09

17

83

52

23

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00

10

00

00

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00

00

11

02

70

04

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50

39

21

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61

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0

Erro

r o

f e

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23

24

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00

00

00

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00

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0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

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sio

n0

72

25

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32

39

83

83

00

00

00

00

00

00

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0

Sour

ceA

uth

ors

rsquoest

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es

Not

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es

in c

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icat

e s

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e o

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pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References























All households












431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

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50

21

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97

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59

09

20

31

01

00

06

00

05

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77

09

82

04

17

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96

03

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08

00

00

00

50

16

09

11

13

12

92

03

15

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69

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20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

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50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

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ued

100

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apita

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23

45

67

89

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ion

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reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

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23

24

94

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00

00

00

00

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00

00

00

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0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

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82

17

65

32

00

0

Erro

r o

f e

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sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

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es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

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e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References



















431

Ta

ble

13

3

We

lfa

re P

red

icti

on

Ma

trix

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Nat

iona

l

14

48

25

41

73

07

00

35

01

40

05

00

20

01

00

00

57

22

52

24

31

99

13

61

04

04

60

15

00

40

00

00

01

69

31

46

16

71

90

22

21

18

08

40

42

02

80

01

00

02

73

40

38

10

71

52

19

91

63

15

71

27

04

50

13

00

05

05

50

57

08

91

26

15

31

78

16

90

93

10

30

25

00

30

00

60

42

07

00

67

09

21

67

17

62

15

09

90

71

00

30

00

70

13

02

00

37

06

70

98

17

71

63

22

11

68

03

50

00

80

03

03

70

31

03

80

94

09

51

96

21

82

14

07

30

00

90

00

01

00

16

01

50

31

03

91

15

21

13

41

22

40

00

10

00

00

02

01

00

08

01

40

41

02

90

68

16

66

60

00

0

Erro

r o

f e

xclu

sio

n1

15

22

82

87

37

30

00

00

00

00

00

00

00

00

0

Urb

an a

reas

15

93

25

50

96

04

80

26

00

00

01

00

10

00

00

00

76

22

38

28

42

29

11

30

74

03

10

17

00

00

00

00

02

35

30

50

21

11

97

23

61

59

09

20

31

01

00

06

00

05

34

40

77

09

82

04

17

41

35

17

90

96

03

40

08

00

00

00

50

16

09

11

13

12

92

03

15

31

69

09

20

31

00

00

00

60

20

01

00

85

12

41

21

17

01

91

19

20

78

01

50

00

70

10

03

80

44

10

11

36

16

12

01

16

71

17

01

50

00

con

tin

ued

on

nex

t p

ag

e


432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References



















432

Ta

ble

13

3c

on

tin

ued

100

Per c

apita

Er

ror o

fex

pend

iture

dec

ile1

23

45

67

89

10in

clus

ion

Urb

an a

reas

80

00

01

20

16

04

00

77

16

51

43

28

61

98

06

40

00

90

00

00

00

14

02

40

43

04

31

09

17

83

52

23

80

00

10

00

00

00

00

00

11

02

70

04

04

50

39

21

46

61

00

0

Erro

r o

f e

xclu

sio

n1

23

24

94

76

00

00

00

00

00

00

00

00

00

00

0

Rura

l are

as

14

20

18

61

35

08

70

94

03

70

23

01

70

02

00

40

83

22

11

15

41

88

14

11

32

07

10

58

04

00

00

00

21

71

31

79

15

11

88

12

40

94

12

90

67

05

10

14

00

62

67

40

87

13

41

70

11

51

38

12

90

85

06

30

55

02

23

54

50

38

11

10

94

12

91

56

14

01

31

13

90

46

02

24

78

60

48

09

50

91

09

71

28

14

61

48

10

51

20

02

10

00

70

24

09

50

53

08

90

82

12

41

32

16

61

70

05

90

00

80

00

05

60

63

10

80

62

07

51

44

14

82

08

13

70

00

90

00

01

20

11

05

50

83

09

01

58

18

82

14

19

00

00

10

00

00

00

01

40

49

02

80

59

05

60

82

17

65

32

00

0

Erro

r o

f e

xclu

sio

n0

72

25

82

32

39

83

83

00

00

00

00

00

00

00

0

Sour

ceA

uth

ors

rsquoest

imat

es

Not

eV

alu

es

in c

ells

ind

icat

e s

har

e o

f th

e t

ota

l po

pu

lati

on

Th

e s

had

ed

are

as in

th

e m

atri

x ac

cou

nt

for

the

err

ors

of

incl

usi

on

or

exc

lusi

on






All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References























All households


National

2000 1600 2069 398 5932

3000 2269 1401 729 5601

4000 2839 831 1159 5172

5000 3206 464 1791 4539

Urban

2000 1517 981 481 7020

3000 1944 555 1052 6450

4000 2223 275 1776 5726

5000 2402 096 2596 4906

Rural

2000 1665 3442 331 4562

3000 2448 2659 551 4342

4000 3066 2041 933 3960

5000 3697 1410 1294 3599











Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References



























Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References




















Conclusion




All households


National

2000 1426 2191 572 5811

3000 2001 1616 989 5393

4000 2496 1122 1488 4895

5000 2892 726 2094 4289

Urban areas

2000 888 1010 1100 7003

3000 1154 744 1828 6275

4000 1377 521 2602 5501

5000 1555 342 1555 4684

Rural areas

2000 1547 4055 452 3946

3000 2221 3382 768 3630

4000 2859 2743 1130 3267

5000 3455 2148 1534 2863












National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References


























National

20 2863 2738 1992 2586

30 3308 2306 2432 2001

40 3735 1865 2899 1384

50 4200 1448 3584 927

Urban areas

20 5533 1260 2407 1226

30 6130 1060 3511 792

40 6539 865 4441 458

50 5000 680 5194 192

Rural areas

20 2261 5068 1658 4300

30 2569 4823 1837 3798

40 2833 4564 2333 3401

50 3075 4287 2593 2815






Notes












References




















Notes












References
























References




























Documents

Assessing the Targeting Performance of Social Programs: Cape Verde