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Poverty Policy Formulation, Monitoring and Reporting Results: Thailand ’ s Experience. Somchai Jitsuchon Thailand Development Research Institute 5 April 2006 Vientiane, LAO PDR. Outline. 1. Overview of Thailand’s Poverty 2. Poverty Policy Formulation - PowerPoint PPT Presentation
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1
Somchai Jitsuchon Thailand Development Research Institute
5 April 2 0 0 6 Vientiane, LAO PDR
Poverty Policy F ormulation, Mo nitoring and Reporting Results:
Thailand’s Experience
Outline
1. Overview of Thailand’s Poverty
2. Poverty Policy Formulation Fundamental Changes of Policy Architects National vs. Area-based Policy
3. Monitoring and Reporting Poverty Data Small Area Estimation Poverty Map
3
Thailand’s Poverty Overview
Poverty TrendThailand’s Poverty Declined Rapidly over the Past 40-50 Years
If using old definition (before 2004), head-count ratio would be only around 5%
4542
34
28
1915
1820 21
1915
11
51
45
38
33
25
1719
21 2119
16
11
0
10
20
30
40
50
60
1986 1988 1990 1992 1994 1996 1998 1999 2000 2001 2002 2004
Consumption Poverty Income Poverty
0
0.1
0.2
0.3
0.4
0.5
0.6
Gini C
oeffic
ient
But Income Inequality Remains High..One of the World’ Highest
Income Share by IncomeQuintile
1986 1988 1990 1992 1994 1996 1998 2000 2002 2004Poorest 20% 55.87 54.37 56.97 58.98 57.23 56.53 56.13 57.45 55.91 54.86Quintile 2 20.02 20.62 19.50 18.90 19.68 19.91 19.82 19.83 20.07 20.16Quintile 2 12.09 12.38 11.70 11.11 11.67 11.83 12.00 11.50 12.07 12.41Quintile 2 7.67 8.05 7.54 7.06 7.35 7.55 7.75 7.27 7.72 8.04Richest 20% 4.36 4.58 4.29 3.96 4.07 4.18 4.30 3.95 4.23 4.54Total 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00Richest/Poorest
12.81 11.88 13.28 14.90 14.07 13.52 13.06 14.55 13.23 12.10
These ratios are frequently quoted in public debates on poverty/inequality
Consequences on Tar get Groups
Destitute poor (absolute poverty) has been dwindling in nu
mber, but some pockets of chronic poverty might exist.
Relative poverty increasingly important stubborn to economic growth, if inequality persists.
began to dominate public debates/policies. More ‘poverty measur
es’ are devised for the relative poor, not the poorest.
Problems of vulnerability also increasingly important, but
still largely neglected.
Rural and urban poverty more linked than in the past, due t
o convergence of economic activities.
8
Poverty Po licy Formulation
Changes in Poverty Policy Architects
In the past national poverty policy either did not ex
ist, or was an unsubstantial part of ‘Nati onal Plan’. Poverty declined mainly thr ough growth process.
Technocrats were thus key (and sole) ar chitects of poverty policy at national lev
el. Politicians mostly influenced sectoral po
- licies, or minor area specific policies.
Changes in Poverty Policy Architects
Present Poverty policy was nationalized by the TR
- T party around the year 2 0 0 0 1 , alo ngwithgl obal i nt er est i n pover t y r educt i on . Politicalsuccess of TRT par t y was par t l y due t hisshi f t .
‘ National Plan’ now plays very little role, a long with its technocrat architects. Pover
ty policy was basically transferred to politi cians’ hands.
Consequently, mostpovertypoliciesar e nowmor e t ar get i ng, mor e sect or a l. Oneexcept i on i s t he uni ver sal heal t h ca rescheme.
-National vs. Area based
Mostofthetime(pastor pr esent ), al l maj or pover t y pol i c iesarecent r al l y concept ual i zed and i mpl em entedbycent r al gover nment ’s bur eaucr at i c arms.
However, therehasbeenat t empt t o decent r al i zed i mpl ement ations to ‘local governments’.
Forexample, provincesaregrantedmorepower (fi nanci al and bur eaucr at i c). More room for local initiatives. But most of l ocal eff or t s i s st i l l devot ed t o car rynat i onal pover t y pol i ci es desi gned b ynat i onal pol i t i ci ans.
Consequences The current policy quickly favors the r
elative poor, rather than the absolute poor (except the universal health care
).
There is urgent need for reliable pove rty data at disaggregated areas level (
at least at provincial level).
Also urgent need for high frequency p overty data (at least annually), to sup
port the ‘Poverty Eradication within 3 years’ agenda by TRT party leader.
13
Poverty Data
Poverty Data Household Surveys on Consumption/Income
Census (pop census, agri cultural census, industrial
census) Administration Records Participatory Reports Hybrids
Thailand’s Pov erty Data
A. Use household surveys (SESs) alone. OK at national/regional level - but inadequate for true area based po licy implementations (e.g. SESs produc
e zero poverty in many provinces).
B. Rural Village Data: Nrd2C and BMN(basic minimum need)Ad hoc ‘poverty line’ composite index (monetary & non-monetary), with ad hoc formula
C. Poverty Registration (TRT part y initiative)completely self-report
Nrd2C/BMN
Census-type Rural Survey. Nrd2C every 2 years, BMN every year.
Data collection/reporting by village committees.
There are doubts that some villages do not actually collect data, but report anyway.
Strengths: - Allow non monetary dimensions of poverty Frequent, yet Low cost
Weaknesses: cover only rural areas data quality may suffer from non-standard
data collection method and (more importantly)impartial evaluation.
2Nrd C VariablesVariable NRd2C Development Variables Variable NRd2C Development
Variables1) Infrastructure 4) Water Sources
I1 Land Title and Types i20 Drinking WaterI2 Electricity Accessibility i21 Non-Drinking WaterI3 Transport and Communication i22 Water for AgricultureI4 Right to Use Land 5) Knowledge, Education, and
Culture2) Outputs, Income, and Employment i23 Villagers’ Education Level
I5 Village Business i24 Continuing Education Ratei6 Earning and Employment i25 Knowledge Provided by the
Governmenti7 Wage Rate i26 Places for Educationi8 Outputs from Rice Farming i27 News and Information Service
Placesi9 Outputs from Other Plant-Farming i28 Activities in Religion, Cultural,
and Sporti10 Other Occupation 6) Natural Resources and
Developmenti11 Migration to Work i29 Foresti12 Farmer Grouping and Cooperation i30 Soil Resourcesi13 Off-Season Agriculture Activities i31 Water Resource
3) Healthi14 Protection in Drug Usagei15 Protection from Contagious
Diseasesi16 Mental Healthi17 Environment SanitaryI18 Work SafetyI19 Participation in Health/ Sanitary
Activities
5Rural Villages that ‘fail’ more than criteria are ‘targeted villages’
Individual level data (not househo -ld), nation wide.
- Completely self reporting method potential use as ‘poverty map’ Strengths
Allow ‘poor’ people to report their specif ic problems. Finding solutions to povert
y problem is thus straightforward Weaknesses
- Over report of problem potential severe targeting problem (regi
- -stration by non poor, and non registrati on by poor)
Used more as political propaganda
Poverty Registration
- Mis targeting Proble m of
Poverty RegistrationNon-Poor Poor Total
Non-registered 82.0% 71.6% Registered 18.0% 28.4%Total 100.0% 100.0%Within Registered 89.9% 10.1% 100.0%
If not complimented by other datasources,
7 1 .6 % of poor people will be neeeeeeeee
20
An AdditionalTool: Small Area Est imation Poverty Map
Potentials and Performance
SAE Poverty Map
Simple Idea: Get estimates of household income/consumption on large dataset (usually Census) based on models built on household surveys (SESs).
SESs have both (Y,X) but Census has only X.The models also allow for ‘location effects’
Advantages: •Combine Census’s Large Coverage with SESs’ Reliability.•Esitmated Y’s enable many applications (poverty, inequality, social security).
Limitations: •Only monetary definition of poverty.•Census is every 10 years (may use other dataset---BMN). •Huge data work, complicated econometric procedures.
chchch uy βxln
chcchu
First Map in 2000 (Joint projectNESDB/NSO/WB/TDRI) Use household survey 2000, Census 2000, and
village survey 1999 (provides location variables for rural map)
Second Map in 2002 (Join projectNSO/NESDB/WB/TDRI) household survey 2002, Census 2000, and village
survey 2002
- Third Map in 2004 (on going effort)
SAE Poverty Maps in Thailand
2000Comparing SAE Ma 1 9 9 9 2 ‘
p’Nrd2C Classification
SAE Poverty Map Non-Target ornon-matched
Target Total
Non-Poor 39,781 9,511 49,292
Poor (30% up) 12,296 4,707 17,003
Total 52,077 14,218 66,295
The two maps are significantly differen t. Either (or both) may have the proble m of including the wrong villages as we
ll as excluding the right villages. Whic h one?.
Why Validation?•Survey Sampling Errors • Model Error• Omitted Variable problem• Inconsistency between SAE and Nrd2C
First Field Validation• To verify SAE 2000 Map, and 1999 Nrd2C•ee eeeeee eee eeeeeeeee eeeeeeee eeee
th) Second Field Validation
• 2002To verify SAE Map• 3In provinces: Pitsanulok (north), Nonb
eeeeeee( ), (l)
Field Validation
FFFFF FFFFFFFFFF FF FF (2000
Findings:• 2Both SAE and Nrd C maps did well in som FFF FF FFFFFFF/, .• F FFFF FFFFFFF F FFFFF FFFF2 ,
• outdated data• ‘ target villages’ were targeted from ‘developmen t dimensions’ not relevant to poverty level.• Doubtful reporting (less often than commonly tho ught), possibly to manipulate government budge t allocation.
• For SAE map, most problems are wrong preFFFFFFFF FF FFFF FFFFFFF (arise possibly from fail ure to define appropriately ‘location variables’ impo rtant to general income level, e.g. how widespread t - he rubber tree growing was)
• FFFF FF FF FFFF FF FFFFFFFFFF FFFF-FFFFF FFFF‘’ . Both can be used together, with improved data quality/models.
Focus on accuracy of ‘poverty ranking’ at sub-district level (not poverty rate)
Method1. Compare with related official
documents (e.g. tax record, BMN)
2. Key Informant Interview (District chiefs, local development agencies, provincial statisticians )
3. Area Observation (geographic, soil quality, water sources, business community, house conditions)
4. Interview with People (farmers, shop owners, street walkers)
Second Field Validati on (2002 Map)
Interviews with people gave the most reliable information
- Head count Rati o Municipal (urban) - Non municipal (rur
al)
Poverty Map for Pitsanulok (disa ggregated at district level)
Poverty Map for Pitsanulok (Gini coefficient at district level)
Verification P oint:
Wang Tong district had high inequalit
y WangTong
Poverty rates va ri edconsi derabl
y
- Some sub districts were clearly bette
- r off(Pai Khodon, Baan Grang).
-Central District Pitsanulok (head - count at sub district level)
Central District: Valid ation Points
BMN Database SAE Poverty RankSub-districts
Income Rank Poverty Rank Income ConsumptionBaan Krong (A) 1 12 19 15Baan Grang (B) 15 9 1 2Pai Khodon (C) 13 17 2 1Ta Poh (D) 19 2 4 3
- With BMN ranking: (B) and (C) sub districts will get morebudget
With SAE map rannking: Both should get less budget tha n (A)
(): Interview with a farmer
Baan Grang (B): Group In terview (farmers)
- -(A) wascl ear l y a bet t er off sub di st r ict, suppor t i ng SAE r esul t s
One of the poorest province
According to SAE maps, all districts were poor, except for Noan Sung district
However, one key informant insisted Noan Sung was relative poorer than other district.
Verification Point: Which was true?
Poverty Map for Nongbualumpoo (head-count at district level)
Noan Sung
Noan Sung: A Farm Field with Double
Cropping
All other districts could not do double cropping.
Also found additional occupation (fishery)
Preliminary Evaluation of SAE
method SAE Poverty Map is fairly accurate in
predicting poverty ranking by area.
Poorer (Reality)
Better-Off (Reality)
Poorer (SAE) Predict
Predict few (X)
Better-Off
(SAE)Not
PredictPredict
SAE can benefit from improvement in the accuracy of surveyed income/consumption.
Need to simplify the method (underway), and overcome the theoretical and empirical issues of poverty map updating.