R EGIONAL P OPULATION A GEING IN T HAILAND

REGIONAL POPULATION AGEING

IN THAILAND

The 11th IFA Global Conference on Ageing

28 May – 1 June 2012. Prague, the Czech Republic

International Federation on Ageing (IFA)

Thuttai KEERATIPONGPAIBOONDepartment of Economics

School of Oriental and African Studies (SOAS), University of London

A part of the CSEAS Project

Structure12 34 5

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IntroductionIntroduction

Situation of Regional Population Ageing in ThailandSituation of Regional Population Ageing in Thailand

Living Arrangements by RegionLiving Arrangements by Region

44 Changes in Economic Behaviour by RegionChanges in Economic Behaviour by Region

55 ConclusionsConclusions

2

Introduction12 34 5

• 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)

Structure12 34 5

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Situation of Regional Population Ageing

Source: Author’s own calculation from the Population Projections (NESDB, 2007)

2000 2010 2025

Highest Share of the Elderly

North NorthBangko

k

11.09%

13.43% 26.97%

Highest Old-age Dependency Ratio

North NorthBangko

k

17.02%

196

5 %4 2 .5

0 %

12 34 5

• 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

Situation of Provincial Population Ageing

• 2000: Most provinces have an old-age dependency ratio below 16 percent, especially those in Northeast and South.

12 34 5

2000

Estimates

Elderly Share & Old-age Dep. Ratio

2000 2010 2020

Highest Sing Buri

Lowest Samut Prakan 6Source: Author’s own calculation from the Population Projections (NESDB, 2007)


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).

12 34 5

7


2000 2010 2020

Highest Sing Buri

Sing Buri

Lowest Samut Prakan

Samut Prakan

2010


StatusShare of

the Elderly(60+)

Year

20002 01

02 02

0

# of Provinces 76 76 76Normal Society

<10% 46 15 0

Ageing Society 10% – 20 % 30 61 60Aged Society > 20% 0 0 16

12 34 5


2000 2010 2020

Highest Sing Buri

Sing Buri Sing Buri

Lowest Samut Prakan

Samut Prakan

Nara-thiwat


• 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

Projections8Source: Author’s own calculation from the Population Projections (NESDB, 2007)

Structure12 34 5

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Living Arrangements by Region12 34 5

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Whole Kingdom

Bangkok Central (excl.BKK)

North Northeast South

One-person HH Head-Spouse HH Skip-gen HH

Two-Gen HH (excl.Skip) Three-gen HH Four-Gen HH

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Whole Kingdom



One-person HH Head-Spouse HH Skip-gen HH

Two-Gen HH (excl.Skip) Three-gen HH Four-Gen HH

1990 2007

• 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)

Structure12 34 5

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Changes in Household Saving Patterns12 34 5

• 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.

1997Asian 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

Changes in Household Saving Patterns12 34 5Age Profiles of Savings (Whole Kingdom), by ages of household heads, 2007

100

exp x

incomecapitaperhousehold

enditurenconsumptiocapitaperhouseholdincomecapitaperhouseholdratiosavinghousehold

13

Source: Author’s own calculation from the 2007 SES data

Changes in Household Saving Patterns

VariablesWhole

Kingdom

Region

BKK Central North N/E South

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*** -12.00 110.20

(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

VariablesWhole

Kingdom

Region


Three-or-more-gen HH (Yes = 1)

74.84 463.19 131.68 -88.10 60.85 192.26

(70.41) (421.91) (104.32) (117.71) (113.56) (199.29)

Two-Gen HH (Yes = 1)

334.94*** 692.65**260.22**

*81.70 374.04*** 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*** -139.1 260.3*** 729.48***

(69.35) (557.03) (109.02) (98.03) (95.32) (199.07)

HH Size235.39***

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*** 18.89 23.09* -13.16

(10.06) (55.59) (11.38) (17.06) (13.92) (22.49)

Age of HH head^2

0.41*** 0.49 0.49*** -0.03 -0.11 0.17

(0.09) (0.67) (0.11) (0.15) (0.12) (0.20)

# of children in HH

137.80*** -13.43126.89**

*229.72*** 61.68 244.29***

(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

0.8970 0.9448 0.8715 0.927 0.6603 0.8600

# Obs (n) 43,055 2,451 12,421 10,734 11,365 6,084


12 34 5

• 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.

64.44

79.11

66.85 63.18 62.7956.30

35.56

20.89

33.15 36.82 37.2143.70

0%

20%

40%

60%

80%

100%

Whole Kingdom



Percentage of Elderly Persons by Employment Status, Thailand, 2007

Not-working Working

Employment Behaviour of the Elderly12 34 5

Pr(work) = a + bX + ε Positive factors (+)

Male, marriage, poverty, agricultural household

Negative factors (-)

Age, pension eligibility, educational attainment, household size 15Source: Author’s own calculation from the 2007 SES data and the 2007 SOP data

Employment Behaviour of the Elderly

VariableWhole

Kingdom

Region


I. Demographic Factors

Age -0.02*** -0.01*** -0.02*** -0.03*** -0.03*** -0.03***

(-22.15) (-5.13) (-12.58) (-12.07) (-11.82) (-9.29)

Secondary education (Yes=1)

-0.037 -0.042* -0.042 -0.023 0.006 0.132

(-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*** -0.08 0.10

(-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*** 0.314***

(12.23) (2.48) (5.84) (6.26) (6.91) (6.27)

Married (Yes=1) 0.156*** 0.006 0.122*** 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 -0.041 0.061 0.104

(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) 0.024 0.351*** 0.197*** 0.005 -0.059 0.188**

(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 -0.016 0.060

(-0.73) (-1.53) (-1.06) (-0.72) (-0.43) (1.30)

16

VariableWhole

Kingdom

Region


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*** 0.062 0.148*** 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*** 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) 20,120 878 5,647 5,511 5,570 2,514

Probability > Chi-Squared

0.0000*** 0.0000*** 0.0000*** 0.0000*** 0.0000*** 0.0000***

Pseudo R-Squared 0.6240 0.4277 0.5959 0.6393 0.6741 0.6135

Log Pseudo-Likelihood -5144.71 -255.12 -1507.28 -1352.98 -1254.42 -673.45

12 34 5

Alternative Old-Age Dependency Ratios Source: Author’s own calculation from the 2007 SES data

Structure12 34 5

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Conclusions12 34 5

Conclusions

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

Thank You

19

Thuttai KeeratipongpaiboonDepartment of EconomicsSOAS, University of London

Email: [email protected]

Supporting Documents

20

Factors affecting Family Relationship12 34 5

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 IncomeFertility

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.

Situation: Regional Population Ageing12 34 5

RegionShare of the Elderly (%)

Old-age Dependency Ratio

(%)

2 000e 2010p 2020p 2025p 2000e 2010p 2020p 2025p

Whole Kingdom 9.43 11.90 17.51 21.22 14.30 17.61 26.58 33.28

Bangkok 7.88 11.28 20.40 26.97 10.61 16.06 30.68 42.50

Central (excl BKK) 9.84 11.63 16.98 20.80 14.54 16.87 25.18 31.83

North 11.09 13.43 20.16 24.21 17.02 19.65 31.02 39.08

Northeast 8.71 11.93 16.95 20.12 13.62 17.99 25.92 31.67

South 9.41 10.76 14.61 17.45 15.06 16.42 22.45 27.28

22

Shares of the Elderly and Old-age Dependency Ratiosby Region, Thailand, 2000-2025


Old-age Employment12 34 5

23

Shares of the elderly, by living arrangement and employment status, Thailand, 2007

Not Work

70.37%

Work29.63%

Not Work

67.04%

Work32.96%

Not Work

57.45%

Work42.55%

Not Work

57.01%

Work42.99%

Three-or-More-Generational Households

37.86%

Two-Generational Households (excl.

Skipped)23.25%

Skipped Generation Households

11.00%

O ne-Generational Households

27.89%

Source: Author’s own calculation from the 2007 SOP data

Old-age Employment12 34 5

24

Shares of active elderly persons, by age group and living arrangement, Thailand, 2007

5.1

13.8

20.7

35.6

47.3

22.4

29.6

6.7

15.1

21.623.4

35.6

52.1

33.0

6.4

14.1

32.4

55.0

34.0

42.6

45.6

13.7

23.3

31.1

45.0

61.7

33.4

43.0

7.6

16.8

25.1

39.5

53.6

35.6

26.8

0

10

20

30

40

50

60

70

Total Elderly (60+) Total Elderly (65+) 60-64 65-69 70-74 75-79 80 and over

Age Groups (Year)

Per

cent

age

of E

ach

Cat

egor

y (%

)

Three-or-More-Generational Households Two-Generational Households (excl. Skipped) Skipped Generation Households

One-Generational Households All Living Arrangements


•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 Poverty12 34 5

25

20.9612.41 15.25 13.17 9.05

24.66

23.75 22.1631.57

24.09

38.7253.34 51.12

43.3856.34

13.2 9.92 10.78 10.76 9.56

0%

20%

40%

60%

80%

100%

1990 1994 1998 2003 2007

Bangkok Central (excl.BKK) North Northeast South

RegionTotal Elderly

People

Poor Elderly People (%)1990 199

4199

82003 200

7Whole Kingdom 100.00

25.6120.9

618.1

4 13.5512.8

2Bangkok 100.00 7.14 2.34 1.79 1.79 1.55Central (excl.BKK)

100.0021.93

10.97

13.25 7.95 5.26

North 100.0026.85

19.77

15.97 19.77

14.18

Northeast 100.0030.61

32.18

27.10 17.65

20.40

South 100.0031.29

18.63

15.36 10.36 9.55

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

100

exp x

incomecapitaperhousehold

enditurenconsumptiocapitaperhouseholdincomecapitaperhouseholdratesavinghousehold

-200

-150

-100

-50

0

50

100

19 24 29 34 39 44 49 54 59 64 69 74 79 84 89 94 99

Age of Household Head

Hou

seho

ld S

avin

g R

ate

(%)

1st Decile 2nd Decile 3rd Decile 4th Decile 5th Decile6th Decile 7th Decile 8th Decile 9th Decile 10th Decile


Source: Author’s own calculation from the 2007 SES data Source: Author’s own calculation from the 2007 SES data

Fertility Rates by Region12 34 5

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

Alternative Old-Age Dependency Ratios12 34 5

27


Source: Author’s calculation, using the data of the International Labour Organization, http://laborsta.ilo.org/, accessed on March 1, 2010. 28

Standard and Alternative Old-age Dependency Ratios, the World, 1980-2020

Estimates Projections


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.

Reasons for Labour-Force Participation12 34 5

30

Elderly People in Thailand answered in the 2007 Survey of Older Persons in Thailand by NSO


Reasons for Labour-Force Withdrawal12 34 5

31

Elderly People in Thailand answered in the 2007 Survey of Older Persons in Thailand by NSO


Natural Increases and Net Migration12 34 5

Remark: Natural Increase = Births – DeathsSource: 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.32

Estimates (1950-2009) and Projections (2010-2050), Thailand