Somchai Jitsuchon Thailand Development Research Institute 5 April 2006 Vientiane, LAO PDR

1. Poverty Policy Formulation, Monitoring and Reporting Results:Thailand’s Experience Somchai JitsuchonThailand Development Research Institute5 April 2006Vientiane, LAO PDR

2. 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

4. Poverty Trend Thailand’s Poverty Declined Rapidly over the Past 40-50 Years If using old definition (before 2004), head-count ratio would be only around 5%

5. But Income Inequality Remains High..One of the World’ Highest

6. Income Share by Income Quintile These ratios are frequently quoted in public debates on poverty/inequality

7. Consequences on Target Groups • Destitute poor (absolute poverty) has been dwindling in number, 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 measures’ 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 to convergence of economic activities.

8. Poverty Policy Formulation

9. Changes in Poverty Policy Architects In the past • national poverty policy either did not exist, or was an unsubstantial part of ‘National Plan’. Poverty declined mainly through growth process. • Technocrats were thus key (and sole) architects of poverty policy at national level. • Politicians mostly influenced sectoral policies, or minor area-specific policies.

10. Changes in Poverty Policy Architects Present • Poverty policy was nationalized by the TRT party around the year 2000-1, along with global interest in poverty reduction. Political success of TRT party was partly due this shift. • ‘National Plan’ now plays very little role, along with its technocrat architects. Poverty policy was basically transferred to politicians’ hands. • Consequently, most poverty policies are now more targeting, more sectoral. One exception is the universal health care scheme.

11. National vs. Area-based • Most of the time (past or present), all major poverty policies are centrally conceptualized and implemented by central government’s bureaucratic arms. • However, there has been attempt to decentralized implementations to ‘local governments’. • For example, provinces are granted more power (financial and bureaucratic). More room for local initiatives. But most of local efforts is still devoted to carry national poverty policies designed by national politicians.

12. Consequences • The current policy quickly favors the relative poor, rather than the absolute poor (except the universal health care). • There is urgent need for reliable poverty data at disaggregated areas level (at least at provincial level). • Also urgent need for high frequency poverty data (at least annually), to support the ‘Poverty Eradication within 3 years’ agenda by TRT party leader.

13. Poverty Data

14. Poverty Data • Household Surveys on Consumption/Income • Census (pop census, agricultural census, industrial census) • Administration Records • Participatory Reports • Hybrids

15. Thailand’s Poverty Data A. Use household surveys (SESs) alone. • OK at national/regional level • but inadequate for true area-based policy implementations (e.g. SESs produce 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 party initiative) • completely self-report

16. 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.

17. Nrd2C Variables Rural Villages that ‘fail’ more than 5 criteria are ‘targeted villages’

18. Poverty Registration • Individual level data (not household), nation-wide. • Completely self-reporting method • potential use as ‘poverty map’ • Strengths • Allow ‘poor’ people to report their specific problems. Finding solutions to poverty problem is thus straightforward • Weaknesses • Over-report of problem • potential severe targeting problem (registration by non-poor, and non-registration by poor) • Used more as political propaganda

19. Mis-targeting Problem of Poverty Registration If not complimented by other data sources,71.6% of poor people will be neglected.

20. An Additional Tool:Small Area Estimation Poverty Map Potentials and Performance

21. 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.

22. SAE Poverty Maps in Thailand • First Map in 2000 (Joint project NESDB/NSO/WB/TDRI) • Use household survey 2000, Census 2000, and village survey 1999 (provides location variables for rural map) • Second Map in 2002 (Join project NSO/NESDB/WB/TDRI) • household survey 2002, Census 2000, and village survey 2002 • Third Map in 2004 (on-going effort)

23. Comparing 2000 SAE Map with 1999 Nrd2C ‘Map’ • The two maps are significantly different. Either (or both) may have the problem of including the wrong villages as well as excluding the right villages. Which one?.

24. Field Validation • 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 • In Nakhon Sri Thammarat province (south) • Second Field Validation • To verify SAE 2002 Map • In 3 provinces: Pitsanulok (north), Nonbualumpoo (northeast), Ratchaburi (central)

25. First Field Validation (Map 2000) • Findings: • Both SAE and Nrd2C maps did well in some villages/tambons, but not in others. • For Nrd2C maps, problems arise from • outdated data • ‘target villages’ were targeted from ‘development dimensions’ not relevant to poverty level. • Doubtful reporting (less often than commonly thought), possibly to manipulate government budget allocation. • For SAE map, most problems are wrong predictions of poor village (arise possibly from failure to define appropriately ‘location variables’ important to general income level, e.g. how widespread the rubber-tree growing was) • WB maps tend to do well in predicting ‘non-poor’ localities. • Both can be used together, with improved data quality/models.

26. Second Field Validation (2002 Map) • Focus on accuracy of ‘poverty ranking’ at sub-district level (not poverty rate) • Method 1. 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) Interviews with people gave the most reliable information

27. Poverty Map for Pitsanulok (disaggregated at district level) • Head-count Ratio • Municipal (urban) • Non-municipal (rural)

28. Poverty Map for Pitsanulok (Gini coefficient at district level) Verification Point: Wang Tong district had high inequality Wang Tong

29. Central District Pitsanulok (head-count at sub-district level) • Poverty rates varied considerably • Some sub-districts were clearly better-off (Pai Khodon, Baan Grang).

30. Central District: Validation Points • With BMN ranking: (B) and (C) sub-districts will get more budget • With SAE map rannking: Both should get less budget than (A)

31. Baan Krong (A): Interview with a farmer

32. Baan Grang (B): Group Interview (farmers) (A) was clearly a better-off sub-district, supporting SAE results

33. Poverty Map for Nongbualumpoo (head-count at district level) • 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? Noan Sung

34. Noan Sung: A Farm Field with Double Cropping All other districts could not do double cropping. Also found additional occupation (fishery)

35. Preliminary Evaluation of SAE method • SAE Poverty Map is fairly accurate in predicting poverty ranking by area. • 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.