1. REGIONAL POPULATION AGEING IN THAILAND The 11 th IFA Global Conference on Ageing 28 May – 1 June 2012. Prague, the Czech Republic International Federation on Ageing (IFA) Thuttai KEERATIPONGPAIBOON Department of Economics School of Oriental and African Studies (SOAS), University of London A part of the CSEAS Project

2. Structure 12345 2 2 1 1 3 3 Introduction Situation of Regional Population Ageing in Thailand Living Arrangements by Region 4 4 Changes in Economic Behaviour by Region 5 5 Conclusions 2

3. Introduction 12345 Thailand is now an ageing society; the share of elderly population reached 10% in the 2000s. However, many parts of Thailand have not been ageing yet! Changes in demographic structure have lead to changes in household composition, living arrangements and economic behaviour, which the situations are different in each area. The society should concern both national and regional levels. This research reveals the situations of population ageing in five regions of Thailand. Significances of the Research Methodology Data The Socio-Economic Survey (SES), Thailand, 1988-2007 (NSO) The Survey of Older Persons in Thailand (SOP), 2007 (NSO) The Population Projections for Thailand, 2000-2030 (NESDB) Secondary sources Methodology Descriptive Analysis Econometric Analysis: Linear Regression Analysis and Probit Model 3 share NSO: National Statistical Office (Thailand) NESDB: National Economic and Social Development Board (Thailand)

4. Structure 12345 4 2 2 1 1 3 3 Introduction Situation of Regional Population Ageing in Thailand Living Arrangements by Region 4 4 Changes in Economic Behaviour by Region 5 5 Conclusions

5. Situation of Regional Population Ageing Source: Author’s own calculation from the Population Projections (NESDB, 2007) 200020102025 Highest Share of the Elderly North Bangkok 11.09%13.43%26.97% Highest Old-age Dependency Ratio North Bangkok 17.02%19.65%42.50% 12345 The main reasons for different situations of population ageing in five regions are different rates of fertility and net migration. Presently, the North has the highest share of the elderly and old-age dependency ratio; the North experienced demographic changed before others. In the next decade, Bangkok is projected to be the oldest region in Thailand due to (1) new trend of out- migration and (2) higher longevity of Bangkokians. 5 Fertility Rate

6. Situation of Provincial Population Ageing 2000: Most provinces have an old-age dependency ratio below 16 percent, especially those in Northeast and South. 12345 2000 Estimates Elderly Share & Old-age Dep. Ratio 200020102020 HighestSing Buri LowestSamut Prakan 6 Source: Author’s own calculation from the Population Projections (NESDB, 2007)

7. Situation of Provincial Population Ageing Projections 2000: Most provinces have an old-age dependency ratio below 16 percent, especially those in Northeast and South. 2000-2010: Increasing shares of the elderly and higher old- age dependency ratios (baby-boomers are retiring). 2000-2010: Sing Buri is the oldest province. 2000-2010: Samut Prakarn is the youngest province; young people have migrated into for employment opportunities (the new airport has been operating since 2006). 12345 7 Elderly Share & Old-age Dep. Ratio 200020102020 HighestSing Buri LowestSamut Prakan 2010 Source: Author’s own calculation from the Population Projections (NESDB, 2007)

8. Status Share of the Elderly(60+) Year 200020102020 # of Provinces76 Normal Society<10%46150 Ageing Society10% – 20%306160 Aged Society> 20%0016 12345 Elderly Share & Old-age Dep. Ratio 200020102020 HighestSing Buri LowestSamut Prakan Nara- thiwat Situation of Provincial Population Ageing 2020: Thailand will be a completely ageing society. None of provinces will have the elderly share below 10%. 2020: 16 provinces is projected be an aged society. 2020: Sing Buri will (still) be the oldest province; meanwhile, Narathiwat is expected to be the youngest province. This is probably due to (1) conflict/violence in the South or (2) lower fertility rate compared to other provinces. NOTE: new industrial cities and Thai-Muslim provinces are also found to have low old-age dependency ratios. 2020 Projections 8 Source: Author’s own calculation from the Population Projections (NESDB, 2007)

9. Structure 12345 9 2 2 1 1 3 3 Introduction Situation of Regional Population Ageing in Thailand Living Arrangements by Region 4 4 Changes in Economic Behaviour by Region 5 5 Conclusions

10. Living Arrangements by Region 12345 19902007 Thai elderly people still live in multi-generational households. Majority of the elderly in Bangkok live in two-generational households; meanwhile, those in the Northeast and Central regions live in three-generational households. However, more elderly people are found in one-generation HHs (living alone or just with a spouse) in all areas. In the North and Northeast, more elderly persons are found in skipped generation households. Households in all regions are now smaller due to delayed marriage and attitude towards having children. 10 Living Arrangements of Thai elderly people by region, Thailand, 1990 & 2007 Source: Author’s own calculation from the SES data (1990 & 2007)

11. Structure 12345 11 2 2 1 1 3 3 Introduction Situation of Regional Population Ageing in Thailand Living Arrangements by Region 4 4 Changes in Economic Behaviour by Region 5 5 Conclusions

12. Changes in Household Saving Patterns 12345 High Consumption Bubbled Economy Low Household Savings Attitude: Consume now, save later The financial crisis has taught Thais about uncertainty. Thai households tend to save more for their own sakes. Households in Bangkok have the highest rate of savings. following by households in the Central, North, South and Northeast, respectively. 1997 Asian Financial Crisis HH Saving Patterns In all regions, the saving patterns are following the Life Cycle Hypothesis of Savings – people save when they are in the working age and dissave in the old age. One-gen HHs are more likely to confront financial problems when their household heads are older, especially after the age of 70, due to uncertainty in a later part of life. They could have less support from family than those living in other household types. Fluctuation of savings rates is more obvious in the case of skip-gen HHs. Factors determining Household Saving Levels [OLS Estimation] The significant factors are household income, marital status, gender of household head, household size, living arrangements, and numbers of children and elderly persons in household. One-gen HHs are likely to save less than other living arrangements. Evidently, elderly people are still playing an important role in the Thai economy. A number of older persons in Thailand are not absolutely dependents. Many people still earn income after the age of sixty. Some of them help their family businesses or take care of their children’s children. 12

13. Changes in Household Saving Patterns 12345 Age Profiles of Savings (Whole Kingdom), by ages of household heads, 2007 13  Source: Author’s own calculation from the 2007 SES data

14. Changes in Household Saving Patterns Variables Whole Kingdom Region BKKCentralNorthN/ESouth Income 0.69***0.71***0.61***0.59***0.61***0.72*** (0.02)(0.05)(0.02)(0.03)(0.02)(0.05) Income^2 4.86e- 07*** 3.94e-07*** 9.92e- 07*** 1.22e-06***9.18e-07***5.32e-07*** (8.25e-08)(6.58e-08)(1.02e-07)(9.61e-08)(9.50e-08)(8.95e-08) Secondary education (Yes= 1) -715.1***-1071.9***-625.0***-386.9***-364.5***-655.0*** (93.71)(292.82)(89.23)(116.06)(129.73)(185.06) Bachelor’s degree (Yes = 1) -2014.**-2880***-1600***-1289***-1088***-1492*** (202.51)(505.38)(170.07)(261.14)(271.48)(304.60) Master’s or higher (Yes = 1) -4992***-5940***-4268***-1754**-3667*-6545*** (996.56)(2227.51)(924.68)(826.66)(2201.71)(2500.34) Central (Yes = 1) 456.2*** (100.98) North (Yes = 1) 1064.4*** (123.20) Northeast (Yes = 1) 1024.9*** (119.40) South (Yes = 1) 433.24*** (117.09) Rural (Yes = 1) 401.63***222.50***466.43***422.59***438.39*** (62.90)(72.66)(97.62)(113.83)(157.10) Male (Yes = 1) 129.95***470.87**108.56*236.82***-12.00110.20 (45.95)(237.25)(59.51)(72.80)(73.46)(117.74) Working (Yes= 1) 467.65***1850.01***386.21***258.64***238.60**-87.74 (91.83)(579.68)(82.15)(79.83)(99.60)(147.00) 14 Variables Whole Kingdom Region BKKCentralNorthN/ESouth Three-or- more-gen HH (Yes = 1) 74.84463.19131.68-88.1060.85192.26 (70.41)(421.91)(104.32)(117.71)(113.56)(199.29) Two-Gen HH (Yes = 1) 334.94***692.65**260.22***81.70374.04***625.2*** (60.65)(309.57)(82.92)(91.07)(101.03)(193.40) Skip-gen HH (Yes = 1) 365.0***1645.8***446.6***-139.1260.3***729.48*** (69.35)(557.03)(109.02)(98.03)(95.32)(199.07) HH Size 235.39***448.59***201.93***96.17**190.50***260.55*** (21.10)(91.16)(28.20)(37.70)(35.50)(44.59) Age of HH head -41.24***-82.19-52.66***18.8923.09*-13.16 (10.06)(55.59)(11.38)(17.06)(13.92)(22.49) Age of HH head^2 0.41***0.490.49***-0.03-0.110.17 (0.09)(0.67)(0.11)(0.15)(0.12)(0.20) # of children in HH 137.80***-13.43126.89***229.72***61.68244.29*** (35.32)(231.21)(44.05)(49.58)(37.65)(73.51) # of elderly persons in HH 220.34***473.45*221.99***132.5***172.07***262.52*** (37.71)(266.62)(50.89)(51.61)(41.04)(98.05) Constant -3802***-4131***-2216***-3637***-3887***-4329*** (216.22)(1006.40)(282.97)(390.87)(445.47)(543.28) Adjusted R-Squared 0.89700.94480.87150.9270.66030.8600 # Obs (n) 43,0552,45112,42110,73411,3656,084  Source: Author’s own calculation from the 2007 SES data 12345

15. Thais tend to stay longer in the workforce. The share of elderly persons (60+) in the workforce increased from 3.6% in 1986 to 7.0% in 2006 In 2007, 35.56 percent of Thai elderly people were economically active. More than forty percent of the elderly in the South were working; the highest figure compared to other regions (N/E, North, Central and BKK, respectively.) The main reasons for being active are that (1) they have responsibility for their own family, and (2) they are still healthy. Most elderly persons in Bangkok work because sixty years of age is too early to stop working; while the elderly in other regions work for their survival. On the other hand, health problems are main reasons for the elderly to leave the labour force. The elderly living in one-/skip-generational HHs are more likely to work than those living in two-/three- generational HHs. Family relationship is an important factor determining employment status of elderly persons. Employment Behaviour of the Elderly 12345 Pr(work) = a + bX + ε Positive factors (+) Male, marriage, poverty, agricultural household Negative factors (-) Age, pension eligibility, educational attainment, household size 15 Source: Author’s own calculation from the 2007 SES data and the 2007 SOP data

16. Employment Behaviour of the Elderly Variable Whole Kingdom Region BKKCentralNorthN/ESouth I. Demographic Factors Age -0.02***-0.01***-0.02***-0.03*** (-22.15)(-5.13)(-12.58)(-12.07)(-11.82)(-9.29) Secondary education (Yes=1) -0.037-0.042*-0.042-0.0230.0060.132 (-1.21)(-1.77)(-1.05)(-0.31)(0.10)(1.13) Bachelor’s degree (Yes=1) -0.12***-0.05**-0.09*-0.24***-0.080.10 (-2.64)(-2.00)(-1.84)(-3.26)(-0.65)(0.60) Master’s or Higher (Yes=1) -0.204**-0.062*-0.005-0.300**-0.318* (-2.45)(-1.70)(-0.04)(-2.36)(-1.94) Male (Yes=1) 0.165**0.081***0.150***0.179***0.161***0.146*** (8.83)(3.70)(5.61)(4.43)(3.76)(3.00) Household head (Yes=1) 0.228***0.053**0.144***0.252***0.314*** (12.23)(2.48)(5.84)(6.26)(6.91)(6.27) Married (Yes=1) 0.156***0.0060.122***0.145***0.263***0.156*** (8.42)(0.29)(4.32)(3.83)(6.13)(2.97) Healthy (Yes=1) 0.269***0.079**0.227***0.268***0.330***0.364*** (10.98)(2.44)(5.99)(6.12)(5.50)(4.71) Access to medical services (Yes=1) 0.004-0.003-0.013-0.0410.0610.104 (0.11)(-0.13)(-0.20)(-0.35)(0.68)(0.90) II. Economic Factors Pension (Yes=1) -0.114***-0.017-0.107**-0.102-0.173*-0.171 (-3.09)(-0.55)(-2.24)(-1.49)(-1.90)(-1.22) Poverty (Yes=1) 0.0240.351***0.197***0.005-0.0590.188** (0.90)(2.61)(3.17)(0.12)(-1.20)(2.51) Living in HH with savings (Yes=1) -0.012-0.046-0.029-0.026-0.0160.060 (-0.73)(-1.53)(-1.06)(-0.72)(-0.43)(1.30) 16 Variable Whole Kingdom Region BKKCentralNorthN/ESouth III. Household Characteristics Central (Yes=1) 0.126*** (3.78) North (Yes=1) 0.122*** (3.53) Northeast (Yes=1) 0.112*** (3.25) South (Yes=1) 0.187*** (4.91) Rural (Yes=1) -0.035**-0.000-0.051*-0.048*-0.020 (-2.46)(-0.04)(-1.95)(-1.59)(-0.45) Three-or-more-gen HH (Yes=1) -0.056*0.026-0.059-0.093-0.094-0.077 (-1.84)(0.75)(--1.37)(-1.21)(-1.38)(-0.90) Two-gen HH (Yes=1) -0.198***-0.064***-0.173***-0.222***-0.202***-0.278*** (-9.35)(-2.67)(-6.09)(-4.71)(-3.38)(-4.40) Skip-gen HH (Yes=1) 0.295***0.0620.148***0.381***0.311***0.243*** (10.00)(0.82)(3.33)(6.10)(5.58)(3.15) Household Size -0.256***-0.105***-0.227***-0.304***-0.249***-0.272*** (-22.38)(-7.72)(-14.21)(12.12)(-10.19)(-9.41) Agricultural HH (Yes=1) 0.386***0.253**0.362***0.316***0.444*** (20.59)(2.31)(12.46)(8.47)(11.56)(9.60) # of income recipients in HH 0.494***0.178***0.434***0.593***0.516***0.542*** (34.02)(8.74)(23.25)(18.79)(17.02)(14.41) # Obs (n) 20,1208785,6475,5115,5702,514 Probability > Chi-Squared 0.0000*** Pseudo R-Squared 0.62400.42770.59590.63930.67410.6135 Log Pseudo-Likelihood -5144.71-255.12-1507.28-1352.98-1254.42-673.45 12345 Alternative Old-Age Dependency Ratios Source: Author’s own calculation from the 2007 SES data

17. Structure 12345 17 2 2 1 1 3 3 Introduction Situation of Regional Population Ageing in Thailand Living Arrangements by Region 4 4 Changes in Economic Behaviour by Region 5 5 Conclusions

18. 12345 Policy Implications Strengthening family relationship. Improving the social safety nets and welfares. Focusing more on the elderly poor. Thailand will be an absolutely ageing society in the next decade. Changes in demographic structure have affected both social and economic aspects. Household composition and living arrangements of Thai households as well as household economic behaviour have changed remarkably in these few decades. Evidently, Thai people in every region are still living in multi-generational households. However, more people tend to live alone or just with their spouse. There are an increasing number of elderly persons in the Northeast and North found in skipped generation households. This should be a serious concern since these people are more likely to live in financial hardship compared to the elderly in other living arrangements. The government itself cannot afford in taking care every elderly person in the country. Therefore, family should play a crucial role in looking after their ageing members. 18

19. Thank You 19 Thuttai Keeratipongpaiboon Department of Economics SOAS, University of London Email: 231827@soas.ac.uk

20. Supporting Documents 20

21. Factors affecting Family Relationship 12345 Source Mason (1992), Figure 1 21 Main factors are Industrialisation, Urbanisation and Mgigration Industrialisation Urbanisation Migration Family Productive Enterprise Wage Employment of Individuals Cost of Home- produced Goods Demand for Female Labour Universal Primary and Secondary Schooling Per Capita Income Fertility Child Survival Filial Piety Parental Power Female Labour Force Participations Joint/Stem Family Ability to Purchase Privacy/Care Availability of Caregivers Housing Availability Separation of the Generations Care of the Elderly + + + - + + + + + - - + + + - + + + - + - + + + + - - - - - Remarks: - Straight and single-headed arrows show casual relationships that run from the cause to the effect; meanwhile, curved and double-headed arrows represent correlated factors, - A sign shown next to the arrow demonstrates a relation between factors. The net impact of factors can be calculated by multiplying the signs. For example, if there is a negative sign between factor A and B, and also a negative sign between factor B and C, the relationship of factors A and C is positive.

22. Situation: Regional Population Ageing 12345 Region Share of the Elderly (%)Old-age Dependency Ratio (%) 2000 e 2010 p 2020 p 2025 p 2000 e 2010 p 2020 p 2025 p Whole Kingdom9.4311.9017.5121.2214.3017.6126.5833.28 Bangkok7.8811.2820.4026.9710.6116.0630.6842.50 Central (excl BKK)9.8411.6316.9820.8014.5416.8725.1831.83 North11.0913.4320.1624.2117.0219.6531.0239.08 Northeast8.7111.9316.9520.1213.6217.9925.9231.67 South9.4110.7614.6117.4515.0616.4222.4527.28 22 Shares of the Elderly and Old-age Dependency Ratios by Region, Thailand, 2000-2025  Source: Author’s own calculation from the Population Projections (NESDB, 2007)

23. Old-age Employment 12345 23 Shares of the elderly, by living arrangement and employment status, Thailand, 2007  Source: Author’s own calculation from the 2007 SOP data

24. Old-age Employment 12345 24 Shares of active elderly persons, by age group and living arrangement, Thailand, 2007  Source: Author’s own calculation from the 2007 SOP data

25. Poverty is defined when household income per capita is below a poverty line. Elderly poverty is commonly found in the Northeast and North. Low-income HHs have less ability to save compared to rich HHs. Elderly Poverty 12345 25 Region Total Elderly People Poor Elderly People (%) 19901994199820032007 Whole Kingdom100.00 25.6120.9618.1413.5512.82 Bangkok100.00 7.142.341.79 1.55 Central (excl.BKK)100.00 21.9310.9713.257.955.26 North100.00 26.8519.7715.9719.7714.18 Northeast100.00 30.6132.1827.1017.6520.40 South100.00 31.2918.6315.3610.369.55 Shares of the elderly poor, by region, Thailand, 1990-2007 Saving Patterns of Thai HHs, by Age of HH Head and Income Deciles, 2007 Percentage of the Elderly Poor, by Region, 1990-2007  Source: Author’s own calculation from the 2007 SES data

26. Fertility Rates by Region 12345 Remarks: 1 Bangkok was included in the Central region during 1960-1969; 2 1970 Census with Own Children Estimate, National Statistic Office; 3 1980 Census with Own Children Estimate, National Statistic Office; 4 1990 Census with Own Children Estimate, National Statistic Office; 5 2000 Census with Indirect Method Estimate, National Statistic Office; 6 The United Nations (2009a), World Population Prospects: The 2008 Revision; 7 Survey of Population Change, National Statistical Office. Source: adapted from Table 1 in Prachuabmoh and Mithranon (2003). 26 

27. Alternative Old-Age Dependency Ratios 12345 27 

28. Alternative Old-Age Dependency Ratios 12345 Source: Author’s calculation, using the data of the International Labour Organization, http://laborsta.ilo.org/, accessed on March 1, 2010.http://laborsta.ilo.org/ 28 Standard and Alternative Old-age Dependency Ratios, the World, 1980-2020 EstimatesProjections 

29. Alternative Old-Age Dependency Ratios 12345 29 Standard and Alternative Old-age Dependency Ratios, Thailand, 1980-2020 Estimates Projections  Source: Author’s calculation, using the data of the International Labour Organization, http://laborsta.ilo.org/, accessed on March 1, 2010.http://laborsta.ilo.org/

30. Reasons for Labour-Force Participation 12345 30 Elderly People in Thailand answered in the 2007 Survey of Older Persons in Thailand by NSO  Source: Author’s own calculation from the 2007 SOP data

31. Reasons for Labour-Force Withdrawal 12345 31 Elderly People in Thailand answered in the 2007 Survey of Older Persons in Thailand by NSO  Source: Author’s own calculation from the 2007 SOP data

32. Natural Increases and Net Migration 12345 Remark: Natural Increase = Births – Deaths Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat, World Population Prospects: The 2008 Revision, http://esa.un.org/unpp, Monday, March 07, 2011; 8:54:01 AM.http://esa.un.org/unpp 32 Estimates (1950-2009) and Projections (2010-2050), Thailand