September  9,  2014  OFFICE OF THE VICE PRESIDENT

THE REPUBLIC OF INDONESIA

BUILDING A BETTER NATIONAL TARGETING SYSTEM FOR IMPROVING SOCIAL SAFETY NET PROGRAMS:  INDONESIAN  EXPERIENCE  IN  SHIFTING  FROM  COMMODITY  SUBSIDIES  TO  TARGETED  SUBSIDIES  

Dr.  Bambang  Widianto  Deputy    for  Social  Welfare  and  Poverty  Allevia;on/  Execu;ve  Secretary  of  THE  NATIONAL  TEAM  FOR  THE  ACCELERATION  OF  POVERTY  REDUCTION  (TNP2K)    

BACKGROUND  

Despite a declining trend in poverty rates, this has slowed in recent years

28.28 million people live below the poverty line (March 2014)

Monthly Consumption per Capita (IDR)

Poor and vulnerable communities make up

40% of the population

Popu

latio

n

Source: Susenas (2010)

Poverty Line

14.15% Below the

200,000 400,000 600,000 800,000 1,000,000

Poor 29 million

Near-poor 70 million

Middle income 100 million

High income 50 million

GROWTH IN CONSUMPTION 2008-2012

Average

Ann

ual i

ncre

ase

(%)

± IDR 370,000/p/month ± IDR 750,000/p/month ± IDR 250,000/p/month 12%

± IDR 370,000/p/month 40%

± IDR 750,000/p/month 80%

0.63  

0.99   1.01  

1.21   1.18  

1.53  1.42  

1.30   1.29  

Indonesia  Indonesia  Myanmar   Thailand  Phillipines  Singapore   Vietnam   Laos   Cambodia  

FUEL  PRICES  IN  VARIOUS  ASIAN  COUNTRIES  (USD/LITER)  MAY  2013  

RON  >  90  RON  <  90  Not  Specified  

FUEL  SUBSIDY  DISTRIBUTION    

Source:  NaTonal  StaTsTc  Office  (BPS),  March  2014  

7  

 2.74    

 6.14    

 10.07    

 22.03    

 59.03    

5.7  

12.9  

21.1  

46.3  

124.0  

 -­‐          20.00      40.00      60.00      80.00      100.00      120.00      140.00    

20%  Lowest  

20%  Second  Lowest  

20%  Middle  

20%  Second  Highest  

20%  Highest  

Amount  (Triliun  IDR)   DistribuTon  (%)  (Trillion  IDR)  

PRESSURE  FROM  INTERNATIONAL  CRUDE  OIL  PRICE  INCREASES  

Fuel  and  Electricity  Subsidies  take  Funding  Away  from  Pro-­‐poor  Development  Sectors  [in  IDR  trillion]    

 Energy  Subsidy  [in  IDR  trillion]   2009   2010   2011   2012   2013   2014  Fuel   45.0   82.4   165.2   211.9   210.0   246.5  Electricity   49.5   57.6   90.4   94.6   100.0   103.8  

23.3  

26.5  

36.0  

38.8  

49.9  

50.6  

186.2  

201.6   25

9.2   300.5  

326.1  

344.7  

76.3  

86.0  

114.2  

145.4   184.3  

206.6  

50.1  

57.8  

44.9  

50.6  

63.6  

82.1  

94.5   140.0  

255.6   30

6.5  

310.0  

350.3  

2009   2010   2011   2012   2013   2014  

Health   EducaTon   Infrastructure   Sosial  Assistance   Energy  Subsidy  

TARGETING    MECHANISMS  

BASIC IDEA SHIFT FROM COMMODITY SUBSIDIES TO HOUSEHOLD SUBSIDIES                Commodity  subsidies  are  simple  but  unfair.                  They  are  not  pro-­‐poor.                  Have  a  big  impact  on  government  budgets.                  Aggregate  poverty  data  is  not  adequate.                  Targeted  subsidies  as  the  basis  of  social  assistance:                  UncondiTonal  Cash  Transfers  (UCT),  Health  Care                            (Jamkesmas),  Student  Aid  (BSM),  Rice  for  the  Poor                    (Raskin),  etc.  

World  Crude  Oil  Price  Increased  Since  the  Last  15  Years  

Fuel  Subsidy  ReducTon  CompensaTon  Program   UncondiTonal  Cash  Transfers        CondiTonal  Cash  Transfer      Rice  for  the  poor      EducaTon      Health      Rural  Infrastructure      Community-­‐Based  Development  

 

SHIFTING  TO  MORE  TARGETED  PROGRAMS  

TARGETING OPTIONS Means   tesTng:   this   requires   high-­‐quality   data   that   is   not  available   in  many  countries  and  may  be  expensive  to  put  in  place.  

Geographical   targeTng:   transfers   are   provided   to   those  living  in  areas  with  a  high  incidence  of  poverty.  

Community-­‐based   targeTng:   uses   community   structures  to  idenTfy  the  poorest  members  in  a  community  or  those  eligible,  according  to  agreed  criteria.  

Providing   benefits   to   those   recognized   as   belonging   to   a  specific  vulnerable  category  of  the  populaTon.  

Self-­‐targeTng:  for  example,   in  work  programs  that  offer  a  below-­‐market   wage,   based   on   the   logic   that   individuals  choose  to  opt  into  the  program.  

EXAMPLES OF SPECIFIC VULNERABLE GROUPS

1.  Most  Poor  (Fakir  Miskin)  2.  Orphans,  Street  Children  3.  Homeless  without  Support    4.  Isolated  Tribal  CommuniTes  5.  Mentally  Ill  6.  Displaced  PopulaTons  

SELF TARGETING: KEROSENE CONVERSIONS TO LPG Government  provides  free  small  bokles  (3  Kg)  of  LPG  to  poor  households,  small  restaurants,  food  vendors  and  other  micro  businesses.  

Billion

 Litres  

59.7

39.3 36.8

1.5

0

10

20

30

40

50

60

70

2005 2008 2009

Fuel  Consump;on  

Conversion from Kerosene to LPG

(Estimation)

BUILDING  A  UNIFIED    DATABASE  SYSTEM  

30% Only

of poor people received

Household Consumption (Decile)

Rec

eivi

ng A

ssis

tanc

e (%

)

REVISED  DATA  COLLECTION  METHODOLOGY    

Goal: To reduce inclusion and exclusion errors

Individual  data  from  other  programs  

Consulta;ons  with  poor  households  

Popula;on  Cencus  2010  

Ini;al  list  of  targeted  

households    

Poor   Not  Poor  

 Beneficiaries  

 

Non-­‐Beneficiaries    

Construction of Initial Lists of Targeted Households

PROCESS  OF  DEVELOPING  THE  UNIFIED  DATABASE  

 Data  collec;on    (PPLS  2011)  

BPS*  

Data  analysis  &  development  of  

TNP2K**    PMT  models    

 Unified  database  

 

Improvements  to  the  Methodology:    -­‐   More  households  surveyed  (43%  vs.  29%  in  2008)  -­‐   Use  of  census  data  as  a  starTng  point    -­‐   Community  involvement  -­‐   More  variables  collected  for  beker  poverty  predicTon  -­‐   Improvements  to  Proxy  Mean  TesTng  (PMT)  methods  

Note:  *  BPS:  NaTonal  StaTsTcs  Office                      **  TNP2K:  NaTonal  Team  for  the  AcceleraTon  of  Poverty  ReducTon  

DATA COLLECTION

Involved 120,000 enumerators

Using initial lists, enumerators surveyed every individual household and collected information for variables on their social and economic status.

Initial list contained “the bottom“ 50% of households. Survey results were sent to TNP2K, and then processed to produce the Unified Database. The Unified Database contains information only on the bottom 40% of households.

PERCENT OF THE POPULATION WITH SIMILAR SOCIO-ECONOMIC

CHARACTERISTICS

Includes  5.7  million  households  or    28.6  million  individuals  

Includes  24.7  million  households,  or  around  96.4  million  individuals  

Includes  15.5  million  households  or    65.6  million  individuals      

Exclusion  Error  

Inclusion  Error  

Poor  

Near    Poor/  Vulner-­‐able  

11,66%  

40  %  

60  %  

25  %  

WHICH OF THESE HOUSEHOLDS WILL RECEIVE SOCIAL ASSISTANCE?

…  due  to  the  number  of  household  members,  the  number    of  dependents  and  the  wife’s  employment  status,  the  household  on  the  right  is  

the  real  beneficiary  of  social  assistance.  

At  first  glance,  this  household  would  be  the  beneficiary,  BUT  …  

Research  

Program  Services  (Opera;on)  

Informa;on  System  

•  Ensure  that  programs  use  the  Unified  Database.  

•  Provide  technical  support  to  the  programs.  

•  Ensure  the  validity  of  various  studies  to  improve  targeTng.  

•  Monitor  &  evaluate  the  use  of  the  Unified  Database.  

•  PMT  modeling  and  analysis  of  cost-­‐effecTveness  for  future  data  collecTon  (presumably  next  in  2014).  

TNP2K TARGETING UNIT TASKS: MANAGING UNIFIED DATABASE

�  

�  

�   •  IT-­‐based  management  •  Provide  informaTon  extracted  

from  the  Unified  Database  through  IT,  media.  

Beneficiary  List  of    Social  ProtecTon  Program    

Unified  Database  for  social  assistance  

Eligibility criteria social assistance program

Beneficiary  List  of    Social  ProtecTon  Program    

Beneficiary  List  of    Social  ProtecTon  Program    

Beneficiary  list  for    social  assistance  programs    

NATIONAL TARGETING SYSTEMS USING THE UNIFIED DATABASE

Set  by  each  program.    For  example,  for  PKH,  the  criteria  was  set  by  the  Minister  of  Social  Affairs:    extremely  poor  households  with  elementary  school-­‐aged  children  or  pregnant  mothers.  

Data  by  name  and  address.  Contains  informa;on  on  the  bogom  40%  of  the  popula;on.    

Names  and  addresses  of  eligible  beneficiaries  for  social  assistance  programs.  

25% of households with the lowest socio-economic status or 15.5 million poor and near-poor households.  

For accessing: BLSM, BSM, Raskin and the JKN card

Started 2013

Data Update by Combining Top Down and Bottom Up

PT. Pos

Households Village Level Deliberation

Recapitalisation

TNP2K’s Unified Database

Number of Complaints as of July 2014

Online Complaints Service (LAPOR!) with UKP4

Complaints received

Followed up

Finished/complete

UNCONDITIONAL  CASH  TRANSFERS  (UCT)  

UNCONDITIONAL CASH TRANSFER Program  descripTon  and  size:    

Each  beneficiary  family  received  IDR  100,000  per  month,  paid  quarterly,  from  October  2005  to  December  2006.    2005-­‐2006  program  budget  was  IDR  23  trillion.      2008  program  budget  was  IDR  13  trillion.  

In  2013,  the  Government  of  Indonesia  implemented  the  uncondiTonal  cash  transfers  (UCT)  program  for  15.5  million  poor  and  near-­‐poor  families,  as  compensaTon  for  inflaTonary  effects  linked  to  fuel  price  increases.    Each  family  received  IDR  150,000  per  month  for  four  months    2013  program  budget  was  IDR  12  trillion  

Reasons  for  Providing  Cash  Transfer  as  Compensa;on  for  Rising  Fuel  Prices  

Recipients  of  cash  transfers  can  benefit  immediately.    Cash  is  easier  for  beneficiaries  when  making  adjustments  in  their  consumpTon  needs.  

In  terms  of  programme  implementaTon,  giving  cash  is  more  efficient  and  the  distribuTon  costs  are  cheaper.  

Fuel  Price  Increases  and  Necessary  Compensa;on  for  the  Poor  

•  If  fuel  prices  rise  by  IDR  3,000  to  total  IDR  9,500,  it  would  be  necessary  to  compensate  +/-­‐  IDR  200,000/household/month  for  6  months.    

 •  A  compensaTon  period  of  6  months  is  considered  adequate  because  inflaTon  

tends  to  return  to  normal  levels  by  that  point.  

Premium  Fuel  Price  Increases  

(IDR)  

Fuel  Price  Increases  (%)  

Baseline  +  Addi;onal    Infla;on  

Linked  to  the  Consumer  Price  Index    

(pp)1  

Baseline  +  Addi;onal  Infla;on  

Incurred  by  the  Poor  (pp)  

Compensa;on  for  Poverty  

Line  Increases  (IDR)  

Compensa;on  Amount  per  month  (IDR)  

2,000   30.77   1.8   3.861   695,077   115,846  

3,000   46.15   3.2   6.864   1,235,692   205,949  

4,000   61.54   4.6   9.868   1,776,308   296,051  

PT. POS INDONESIA NO.   DESCRIPTION    NUMBER  

1.   Post  Office  Branches   3,892  2.   Mobile  Services   3,062  3.   Cars  and  Motorcycles   10,523  4.   Employees   28,900  5.   Online  Post  Offices   3,500  6.   Delivery  People   9,867  

34  

Website BLSM www.kompensasi.info

SMS: INFO<spasi>BLSM Send to ….

SMS INFO UNCONDITIONAL CASH TRANSFERS

E  V  A  L  U  A  T  I  O  N  

Queuing  Time  

POTENTIAL FOR INJURY: Long queuing times, particularly for the elderly

Wai;ng  Times  for  UCT  Beneficiaries,  60+  

Distance  from  collecTon  point  (PT.  Pos)  

79.72%

16.87%

2.21% 1.20%

Time to Collection Point (Phase 1)

Less than 1 hr 1 - 2 hrs 3 - 5 hrs more than 5 hrs

POTENTIAL FOR INJURY: Long distances to the nearest post office

0   20   40   60   80   100  

Gasoline  

Capital  

Others  

EducaTon  

Health  

Repay  debt  

Kerosene  

Rice  

2nd  payment  

UCT  WAS  USED  FOR  BASIC  NECESSITIES  

Near-Poor and Below 2005 2007 Diff

Household (HH) Head UCT 39.2 37.7 1.5** Non-UCT 41.0 39.8 1.2** Difference -1.8 -2.1 0.3

Spouse UCT 30.1 31.6 -1.5** Non-UCT 33.2 33.4 -0.3 Difference -3.0 -1.8 -1.2

Other HH Member UCT 37.8 35.6 2.2** Non-UCT 39.1 37.5 1.6** Difference -1.3 -1.9 0.6

** Sign. at 5%

UCT  DID  NOT  REDUCE  TOTAL  WORKING  HOURS  

Cash Assistance for Poor Students in Elementary, Middle and High School

(BSM)

The dropout rate both among the poor between grades and stages of education is very high.

“ “ Years in education

Perc

ent

Less than

of poor people receive BSM 10%

Household Expenditure (Consumption) per Decile

Percent of 6-18-year-olds that receive BSM

Before 2013

School-based Household-based

•  Using KPS •  16.6 million students

IMPROVING  BSM  TARGETING  ACCURACY  USING  KPS  

UNIFIED DATABASE

Children/parents bring their KPS +

Family Card + additional proof to their school/

madrasah

Schools/madrasah collect card summaries and information on students for sending to the district/city

levels

DISTRICTS / CITIES

PROVINCIAL

MINISTRY OF EDUCATION & CULTURE / MINISTRY OF

RELIGION

Increasing the use of KPS for BSM

Stage I June

Stage II September

Using KPS to Improve Targeting Accuracy for BSM

Source: Susenas 2009, SPS TW IV 2013 and TW I 2014

School-based Households-based (March 2014)

School-based Households-based (March 2014)

Cov

erag

e of

Ben

efic

iarie

s (%

)

Cov

erag

e of

Ben

efic

iarie

s (%

)

Elementary School Middle School

IMPACT ON BETTER TARGETING

The number of poor decreased

4.25 million in 5 years

32.53

28.28

14.15%

11.25%

2009 2014 Number of poor (million)

Poverty rate (%)

From 2009 to 2012 inequality continues to rise

0.37 0.41

2009 2012

Growth in Consumption and the Poverty Line 2010-2014

Average Growth in Consumption 2010-2014 Changes in the Poverty Line

Perc

ent (

%)

Decile 1 Decile 2 Decile 10

Growth in Consumption and the Poverty Line 2013-2014

Average Growth in Consumption 2013-2014 Changes in the Poverty Line

Perc

ent (

%)

Decile 1 Decile 2 Decile 10

ANNUAL  INFLATION:  FOOD  AND  NON-­‐FOOD  

Annual Inflation – Food (%)

Annual Inflation – Non-Food (%)

Food inflation is always higher compared with non-food inflation. As such, the burden on the poor is heavier.

Annual Inflation

THANK YOU

 NATIONAL  TEAM    FOR  THE  ACCELERATION  OF  POVERTY  REDUCTION