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BUILDING A BETTER NATIONAL TARGETING 
SYSTEM FOR IMPROVING SOCIAL SAFETY NET 
PROGRAMS: 
INDONESIAN 
EXPERIENCE 
IN 
SHIFT...
BACKGROUND
Despite a declining trend in poverty rates, this has slowed in recent years 
28.28 million people live below the poverty l...
Poor and vulnerable 
communities make up 40% of the population 
14.15% 
Below the 
Monthly Consumption per Capita (IDR) 
P...
GROWTH IN CONSUMPTION 2008-2012 
Poor 
29 million 
Near-poor 
70 million 
Middle income 
100 million 
High income 
50 mill...
FUEL 
PRICES 
IN 
VARIOUS 
ASIAN 
COUNTRIES 
(USD/LITER) 
MAY 
2013 
RON 
> 
90 
RON 
< 
90 
Not 
Specified 
0.63 
0.99 
1...
FUEL 
SUBSIDY 
DISTRIBUTION 
20% 
Highest 
20% 
Second 
Highest 
20% 
Middle 
20% 
Second 
Lowest 
Source: 
10.07 
6.14 
N...
PRESSURE 
FROM 
INTERNATIONAL 
CRUDE 
OIL 
PRICE 
INCREASES 
Fuel 
and 
Electricity 
Subsidies 
take 
Funding 
Away 
from ...
TARGETING 
MECHANISMS
BASIC IDEA 
SHIFT FROM COMMODITY SUBSIDIES 
TO HOUSEHOLD SUBSIDIES 
Commodity 
subsidies 
are 
simple 
but 
unfair. 
They ...
SHIFTING 
TO 
MORE 
TARGETED 
PROGRAMS 
World 
Crude 
Oil 
Price 
Increased 
Since 
the 
Last 
15 
Years 
Fuel 
Subsidy 
R...
TARGETING OPTIONS 
Means 
tesTng: 
this 
requires 
high-­‐quality 
data 
that 
is 
not 
available 
in 
many 
countries 
an...
EXAMPLES OF SPECIFIC 
VULNERABLE GROUPS 
1. Most 
Poor 
(Fakir 
Miskin) 
2. Orphans, 
Street 
Children 
3. Homeless 
witho...
SELF TARGETING: 
KEROSENE CONVERSIONS TO LPG 
Government 
provides 
free 
small 
bokles 
(3 
Kg) 
of 
LPG 
to 
poor 
house...
BUILDING 
A 
UNIFIED 
DATABASE 
SYSTEM
30% Only 
of poor people 
received 
Household Consumption (Decile) 
Receiving Assistance (%)
REVISED 
DATA 
COLLECTION 
METHODOLOGY 
Goal: To reduce inclusion and 
exclusion errors 
Construction of Initial Lists of ...
PROCESS 
OF 
DEVELOPING 
THE 
UNIFIED 
DATABASE 
Data 
collec;on 
(PPLS 
2011) 
BPS* 
Data 
analysis 
& 
development 
of 
...
DATA COLLECTION 
Involved 120,000 enumerators 
Using initial lists, enumerators surveyed every 
individual household and c...
PERCENT OF THE POPULATION WITH 
SIMILAR SOCIO-ECONOMIC 
CHARACTERISTICS 
Exclusion 
Error 
Includes 
24.7 
million 
househ...
WHICH OF THESE HOUSEHOLDS WILL RECEIVE 
SOCIAL ASSISTANCE? 
… 
due 
to 
the 
number 
of 
household 
members, 
the 
number ...
MANAGING UNIFIED DATABASE 
Program 
Services 
(Opera;on) 
Research 
Informa;on 
System 
• Ensure 
that 
programs 
use 
the...
NATIONAL TARGETING SYSTEMS 
USING THE UNIFIED DATABASE 
Eligibility criteria 
social assistance program 
Unified 
Database...
Started 2013 
25% of households with the lowest socio-economic status 
or 15.5 million poor and near-poor households. 
For...
Data Update by Combining 
Top Down and Bottom Up 
PT. Pos 
Households Village Level 
Deliberation 
Recapitalisation 
TNP2K...
Online Complaints Service (LAPOR!) with 
UKP4 
Number of Complaints as of July 2014 
Complaints 
received 
Followed 
up 
F...
UNCONDITIONAL 
CASH 
TRANSFERS 
(UCT)
UNCONDITIONAL CASH TRANSFER 
Program 
descripTon 
and 
size: 
Each 
beneficiary 
family 
received 
IDR 
100,000 
per 
mont...
Reasons 
for 
Providing 
Cash 
Transfer 
as 
Compensa;on 
for 
Rising 
Fuel 
Prices 
Recipients 
of 
cash 
transfers 
can ...
Fuel 
Price 
Increases 
and 
Necessary 
Compensa;on 
for 
the 
Poor 
Premium 
Fuel 
Price 
Increases 
• If 
(IDR) 
Fuel 
P...
PT. POS INDONESIA 
NO. 
DESCRIPTION 
NUMBER 
1. 
Post 
Office 
Branches 
3,892 
2. 
Mobile 
Services 
3,062 
3. 
Cars 
and...
Website BLSM www.kompensasi.info
SMS INFO 
UNCONDITIONAL CASH TRANSFERS 
SMS: INFO<spasi>BLSM 
Send to ….
E 
V 
A 
L 
U 
A 
T 
I 
O 
N
POTENTIAL FOR INJURY: 
Long queuing times, particularly for the elderly 
Queuing 
Time 
Wai;ng 
Times 
for 
UCT 
Beneficia...
POTENTIAL FOR INJURY: 
Long distances to the nearest post office 
Distance 
from 
collecTon 
point 
(PT. 
Pos) 
Time to Co...
0 
20 
40 
60 
80 
100 
Rice 
Kerosene 
Repay 
debt 
Health 
EducaTon 
Others 
Capital 
Gasoline 
2nd 
payment 
UCT 
WAS 
...
UCT 
DID 
NOT 
REDUCE 
TOTAL 
WORKING 
HOURS 
Near-Poor and Below 
2005 2007 Diff 
Household (HH) Head 
UCT 39.2 37.7 1.5*...
Cash Assistance for Poor 
Students in Elementary, 
Middle and High School 
(BSM)
Years in education 
The dropout rate both among the poor between 
grades and stages of education is very high. “ “ 
Percen...
Less 
than 
10% receive BSM 
of poor people 
Household Expenditure (Consumption) per Decile 
Percent of 6-18-year-olds tha...
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 + 
add...
Increasing the use of KPS for BSM 
Stage I 
June 
Stage II 
September
Using KPS to Improve 
Targeting Accuracy for BSM 
School-based 
Households-based (March 2014) 
Source: Susenas 2009, SPS T...
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)...
Growth in Consumption and the Poverty Line 
2010-2014 
Percent (%) Decile 1 Decile 2 Decile 10 
Average Growth in Consumpt...
Growth in Consumption and the Poverty Line 
2013-2014 
Percent (%) Decile 1 Decile 2 Decile 10 
Average Growth in Consumpt...
ANNUAL 
INFLATION: 
FOOD 
AND 
NON-­‐FOOD 
Annual Inflation – Food (%) 
Annual Inflation – Non-Food (%) 
Food inflation is...
THANK YOU 
NATIONAL 
TEAM 
FOR 
THE 
ACCELERATION 
OF 
POVERTY 
REDUCTION
Building a Better National Targeting System for Improving Social Safety Net Programs: Indonesian Experience in Shifting fr...
Building a Better National Targeting System for Improving Social Safety Net Programs: Indonesian Experience in Shifting fr...
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Building a Better National Targeting System for Improving Social Safety Net Programs: Indonesian Experience in Shifting from Commodity Subsidies to Targeted Subsidies (EN)

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Dr. Bambang Widianto
Executive Secretary to the National Team for the Acceleration of Poverty Reduction
Office of the Vice President
Republic of Indonesia

Published in: Economy & Finance
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Building a Better National Targeting System for Improving Social Safety Net Programs: Indonesian Experience in Shifting from Commodity Subsidies to Targeted Subsidies (EN)

  1. 1. 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) September 9, 2014 OFFICE OF THE VICE PRESIDENT THE REPUBLIC OF INDONESIA
  2. 2. BACKGROUND
  3. 3. Despite a declining trend in poverty rates, this has slowed in recent years 28.28 million people live below the poverty line (March 2014)
  4. 4. Poor and vulnerable communities make up 40% of the population 14.15% Below the Monthly Consumption per Capita (IDR) Population Source: Susenas (2010) Poverty Line 200,000 400,000 600,000 800,000 1,000,000
  5. 5. GROWTH IN CONSUMPTION 2008-2012 Poor 29 million Near-poor 70 million Middle income 100 million High income 50 million Average Annual increase (%) ± ± IDR 250,00 0/p/month IDR 370,000/p/month ± IDR 750,000/p/month 12% ± IDR 370,000/p/month 40% ± IDR 750,000/p/month 80%
  6. 6. FUEL PRICES IN VARIOUS ASIAN COUNTRIES (USD/LITER) MAY 2013 RON > 90 RON < 90 Not Specified 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
  7. 7. FUEL SUBSIDY DISTRIBUTION 20% Highest 20% Second Highest 20% Middle 20% Second Lowest Source: 10.07 6.14 NaTonal StaTsTc Office (BPS), March 2014 7 2.74 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 Amount (Triliun ID IDRR) ) (Trillion DistribuTon (%)
  8. 8. PRESSURE FROM INTERNATIONAL CRUDE OIL PRICE INCREASES Fuel and Electricity Subsidies take Funding Away from Pro-­‐poor Development Sectors [in IDR trillion] 23.3 186.2 76.3 Energy Subsidy [in IDR trillion] 36.0 38.8 49.9 50.6 201.6 259.2 300.5 326.1 344.7 86.0 114.2 145.4 184.3 2009 2010 2011 2012 2013 2014 26.5 Fuel 45.0 82.4 165.2 211.9 210.0 246.5 Electricity 49.5 57.6 90.4 94.6 100.0 103.8 206.6 50.1 57.8 44.9 50.6 63.6 82.1 94.5 140.0 255.6 306.5 310.0 350.3 2009 2010 2011 2012 2013 2014 Health EducaTon Infrastructure Sosial Assistance Energy Subsidy
  9. 9. TARGETING MECHANISMS
  10. 10. 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.
  11. 11. SHIFTING TO MORE TARGETED PROGRAMS 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
  12. 12. 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.
  13. 13. 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
  14. 14. 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. 70 60 50 Billion Litres 59.7 1.5 39.3 36.8 40 30 20 10 0 2005 2008 2009 Fuel Consump;on Conversion from Kerosene to LPG (Estimation)
  15. 15. BUILDING A UNIFIED DATABASE SYSTEM
  16. 16. 30% Only of poor people received Household Consumption (Decile) Receiving Assistance (%)
  17. 17. REVISED DATA COLLECTION METHODOLOGY Goal: To reduce inclusion and exclusion errors Construction of Initial Lists of Targeted Households Individual data from other programs Consulta;ons with poor households Popula;on Cencus 2010 Poor Not Poor Beneficiaries Non-­‐Beneficiaries Ini;al list of targeted households
  18. 18. 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
  19. 19. 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.
  20. 20. PERCENT OF THE POPULATION WITH SIMILAR SOCIO-ECONOMIC CHARACTERISTICS Exclusion Error Includes 24.7 million households, or around 96.4 million individuals Includes 15.5 million households or 65.6 million individuals Inclusion Error Includes 5.7 million households or 28.6 million individuals Near Poor/ Vulner-­‐ able Poor 60 % 40 % 25 % 11,66%
  21. 21. 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 …
  22. 22. MANAGING UNIFIED DATABASE Program Services (Opera;on) Research 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: Œ  Ž • IT-­‐based management • Provide informaTon extracted from the Unified Database through IT, media.
  23. 23. NATIONAL TARGETING SYSTEMS USING THE UNIFIED DATABASE Eligibility criteria social assistance program Unified Database for social assistance Beneficiary list for Beneficiary List of Beneficiary List of social assistance programs Beneficiary List of Social ProtecTon Program Social ProtecTon Program Social ProtecTon Program 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.
  24. 24. Started 2013 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
  25. 25. Data Update by Combining Top Down and Bottom Up PT. Pos Households Village Level Deliberation Recapitalisation TNP2K’s Unified Database
  26. 26. Online Complaints Service (LAPOR!) with UKP4 Number of Complaints as of July 2014 Complaints received Followed up Finished/ complete
  27. 27. UNCONDITIONAL CASH TRANSFERS (UCT)
  28. 28. 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
  29. 29. 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.
  30. 30. Fuel Price Increases and Necessary Compensa;on for the Poor Premium Fuel Price Increases • If (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 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.
  31. 31. 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
  32. 32. Website BLSM www.kompensasi.info
  33. 33. SMS INFO UNCONDITIONAL CASH TRANSFERS SMS: INFO<spasi>BLSM Send to ….
  34. 34. E V A L U A T I O N
  35. 35. POTENTIAL FOR INJURY: Long queuing times, particularly for the elderly Queuing Time Wai;ng Times for UCT Beneficiaries, 60+
  36. 36. POTENTIAL FOR INJURY: Long distances to the nearest post office Distance from collecTon point (PT. Pos) Time to Collection Point (Phase 1) 79.72% 2.21% 1.20% 16.87% Less than 1 hr 1 - 2 hrs 3 - 5 hrs more than 5 hrs
  37. 37. 0 20 40 60 80 100 Rice Kerosene Repay debt Health EducaTon Others Capital Gasoline 2nd payment UCT WAS USED FOR BASIC NECESSITIES
  38. 38. UCT DID NOT REDUCE TOTAL WORKING HOURS 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%
  39. 39. Cash Assistance for Poor Students in Elementary, Middle and High School (BSM)
  40. 40. Years in education The dropout rate both among the poor between grades and stages of education is very high. “ “ Percent
  41. 41. Less than 10% receive BSM of poor people Household Expenditure (Consumption) per Decile Percent of 6-18-year-olds that receive BSM
  42. 42. Before 2013 School-based Household-based • Using KPS • 16.6 million students
  43. 43. IMPROVING BSM TARGETING ACCURACY USING KPS UNIFIED DATABASE Children/parents bring their KPS + Family Card + additional proof to their school/ madrasah MINISTRY OF EDUCATION & CULTURE / MINISTRY OF PROVINCIAL DISTRICTS / CITIES Schools/madrasah collect card summaries and information on students for sending to the district/city levels RELIGION
  44. 44. Increasing the use of KPS for BSM Stage I June Stage II September
  45. 45. Using KPS to Improve Targeting Accuracy for BSM School-based Households-based (March 2014) Source: Susenas 2009, SPS TW IV 2013 and TW I 2014 School-based Households-based (March 2014) Coverage of Beneficiaries (%) Coverage of Beneficiaries (%) Elementary School Middle School
  46. 46. IMPACT ON BETTER TARGETING
  47. 47. 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 (%) 0.37 0.41 2009 2012 From 2009 to 2012 inequality continues to rise
  48. 48. Growth in Consumption and the Poverty Line 2010-2014 Percent (%) Decile 1 Decile 2 Decile 10 Average Growth in Consumption 2010-2014 Changes in the Poverty Line
  49. 49. Growth in Consumption and the Poverty Line 2013-2014 Percent (%) Decile 1 Decile 2 Decile 10 Average Growth in Consumption 2013-2014 Changes in the Poverty Line
  50. 50. 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
  51. 51. THANK YOU NATIONAL TEAM FOR THE ACCELERATION OF POVERTY REDUCTION

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