Endowed Professorships Public Lecture Series: I The University of Hong Kong 11 April 2014
Y C Richard Wong Philip Wong Kennedy Wong Professor
in Political Economy
Understanding Inequality and Intergenerational Mobility
–– in Hong Kong
Outline
1 Intuition, Fact and Theory 2 Inequality and Intergenerational Mobility in the US 3 Individual Income Inequality
– Wages, Lifetime Earnings, Productivity and Returns to Schooling – Labor Force Participation and Welfare
4 Household Income Inequality – Marital Sorting, Single Parenthood and HK as Top 10 Divorce Destination
5 Household and Individual Income Inequality Compared 6 Inequality and the Poverty Line 7 Inequality and Intergenerational Mobility in Hong Kong 8 Divorce, Public Rental Housing and Intergenerational Poverty 9 Early Childhood Intervention and Parenting 10 Housing Subsidies should focus on Homeownership
2
Politics and Analysis
• In pre-industrial societies, inequality, poverty and intergenerational mobility were not political issues
• Today they are • The popular press has interpreted them as a product
of unequal power relations between capital and labor, rich and poor, inherent to capitalism, made worse by cronyism, and communism is not immune
• My lecture is to tell another narrative, show why mine is empirically compelling, and reassess the options for a new policy strategy
3
• I will give a long narrative on Hong Kong, but to make it compelling I shall also tell a short one on the United States
• But first a word of caution about narratives, which in social sciences are too often elevated into the exalted status of theories claiming too much dignity
• To be a theory it has to confront facts, explain them, and make correct predictions, until then theories are fiction; entertaining perhaps, but true only by coincidence
4
Theory and Fact
• A fact without a theory • is like a ship without a sail, • is like a boat without a rudder, • is like a kite without a tail, • a fact without a theory is as sad as sad can be, • but there is one thing even more sad,
• it is a theory without a fact
5
Here are some key takeaways
6
Key Takeaways (Slide 1)
• Measured income is unequal for many different reasons, considerable proportion is noise, especially household income
• Individual income inequality has been rising because of underinvestment in education and lack of inflow of quality human capital
• Individual income has not grown very much in the past 20 years except among the top 30%
7
Key Takeaways (Slide 2)
• In the past two decades around 3% of the population have decided not to work for no reason (most likely because of more generous welfare benefits)
• Minimum wages has no effect on reducing household income inequality and have negligible effects on alleviating poverty
• Household income inequality has been rising because of rising single parent households
8
Key Takeaways (Slide 3)
• Divorce rates are 50% higher among tenants than homeowners
• Remarriage rates are much higher for men than women
• Our public rental housing program, their allocation criterion in particular, creates incentives for low-income families to divorce
• Creating additional housing demand and …
9
Key Takeaways (Slide 4)
• Broken families probably worsen intergenerational mobility, especially among low-income single parent families
• Many of these families are concentrated in the public housing estates, and is likely to continue to be the case unless….
• Policy interventions to enhance mobility and alleviate poverty must occur when the children are very young – head start programs
10
Key Takeaways (Slide 5)
• Subsidized housing programs should be anchored on homeownership not rental units
• Public rental housing are operated at a loss that could not even cover development costs
• They require huge public subsidies with serious fiscal consequences for the future
• Public ownership units can cover development costs and generate public revenues because land premium can be partly recovered
11
Inequality and Intergenerational Mobility
• Is inequality and intergenerational upward mobility related?
• We know measured income inequality has risen in the last 30 years in many societies
• We know much less about what has happened to intergenerational mobility
• Many intuitively believe that the two must be related
• What is yours?
12
Little Mobility <=> More Inequality?
• If your parents are rich then you will be rich too then there will be little upward mobility
• This is the same as saying the intergenerational income elasticity is high
• Do you also intuitively think that with little upward mobility then it must increase income inequality?
• So is the intergenerational income elasticity positively correlated with measured income inequality?
13
A Fact Without a Theory
14
Intuition, Facts and Theory
• Is your intuition now confirmed by “facts”? • The positive correlation is sensitive to what
countries are included and to how you measure income elasticity and income inequality
15
16
• The correlation you observed is actually meaningless because you should really be looking at what happens to inequality over time in these countries when intergenerational mobility increases or decreases, and you have to explain why it happens
• Without a theory you really have learned nothing from the “facts” you just saw
• You have claimed what the data couldn’t show
17
Our Narrative Begins in the US
• Let us take a look at the best available study from the US (by Raj Chetty, et al., 2014) to help fix ideas
• Growing public perception that intergenerational mobility has declined and income inequality has risen in the US
• Analyze trends in mobility for 1971-1993 birth cohorts using administrative data on more than 50 million children and their parents
18
Two main empirical results
• Income inequality has increased over time – Consequences of the “birth lottery” for the
parents to whom a child is born are larger today than in the past
• Relationship between parent and child percentile ranks in income is unchanged – Chance of moving from bottom to top fifth of
income distribution no lower for children entering labor market today than in the 1970s
19
Changes in Income Ladder in the US
• The rungs of income ladder have grown further apart (income inequality has increased)
• ….but number of steps children have to climb from lower to higher rungs have not changed
20
0 0.
2 0.
4 0.
6 0.
8 R
ank-
Ran
k S
lope
1971 1974 1977 1980 1983 1986 1989 1992 Child's Birth Cohort
Intergenerational Mobility Estimates for the 1971-1993 Birth Cohorts
Forecast Based on Age 26 Income and College Attendance
Income Rank-Rank (Child Age 30; SOI Sample)
College-Income Gradient (Child Age 19; Pop. Sample)
Income Rank-Rank (Child Age 26; Pop. Sample)
0%
10%
20
%
30%
40
%
1971 1974 1977 1980 1983 1986 Child's Birth Cohort
Parent Quintile
Probability of Reaching Top Quintile by US Birth Cohort
Q1 Q3 Q5
Pro
babi
lity
Chi
ld in
Top
Fift
h of
Inco
me
Dis
tribu
tion
22
Geography of US Intergenerational Mobility
23
• Segregation. Upward mobility is significantly lower in areas with large, heavily segregated African-American populations. The study notes that whites in these areas also have low upward mobility rates.
• Inequality. Factors that erode the middle class hamper intergenerational mobility more than the factors that lead to income growth in the upper tail.
• Quality of education. Areas with higher test scores and lower dropout rates do better.
• Social capital. Strong community social networks and community involvement contributes to the community's upward mobility rates.
• Family structure. The percentage of single parents in a community is the strongest predictor of upward mobility. Children of married parents also have higher upward mobility if they live in communities with fewer single parents.
24
Upward Mobility by Share of Single Mothers in the Community
25
The State of White America, 1960-2010
If the low-income high divorce families are sinking then how can upward mobility still be unchanged in the US? The high-income families are staying together and their children are doing even better: Story of Fishtown and Belmont
What Determines Individual Income Inequality?
• What is individual labor earnings • Earnings = Wage x Hours worked per period • Inequality of wage rates and hours of work affect
inequality of earnings • Wage rate depends on productivity
(education, soft skills, health) • Hours worked per year depends on incentives
(wage rate, other sources of income, taxes, welfare subsidies, health, macroeconomic conditions, ability to work with others)
27
Lifetime Earnings
• Earnings at a point in the life cycle or over a lifetime? • What is a person’s true economic position? Who is rich?
Who is poor? • A cross-section measure of individual income takes a
snapshot at a moment in time • Crucially it fails to control for age and schooling • Can a snapshot be representative of a lifetime’s
earnings? • Households are even more complicated and are at
different stages of their life cycle • Schooling is generally a much better measure of lifetime
earnings of an individual and the household
28
Hong Kong – Mean Earnings by Age, 2011
29
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Mean Earnings (HK$)
Age
Degree or above
Post Secondary
Secondary and Matriculation
Primary or lower
Hong Kong- Mean Earnings by age, 1981
30
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
12,000
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Mean Earnings(HK$)
Age
Degree or above
Post Secondary
Secondary and Matriculation
Primary or lower
Hong Kong - Earnings of degree graduates divided by secondary and matriculation students, 1981 & 2011
31
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
Ratio
Age
2001
1981
Annual Percentage Growth of Real Median Monthly Individual Income by Decile Groups (1981-2011)
5.69
5.04 5.12 4.74 4.72
4.46 4.26
4.62
5.68
7.16
0.25
-0.20
0.37 0.70
1.08 1.34 1.50
1.99 2.10 2.08
-1
0
1
2
3
4
5
6
7
8
1st decile (lowest)
2nd 3rd 4th 5th 6th 7th 8th 9th 10th (highest)
Annual Percentage
Growth
Decile Income Groups
1981-1996
1996-2011
32
Annual Percentage Increase in Population Aged 15+ by Education (1961-2011)
5.1 5.2 4.0
0.3 1.3 1.2
-1.9
2.8
0.4
21.6
4.2
13.6
-2.3
-4.9
15.2
4.3
0.9
4.6
0.8
5.4 6.2
12.5
4.1 4.1 3.1
-8
-6
-4
-2
0
2
4
6
8
10
12
14
16
18
20
22
24
1961-1971 1971-1976 1976-1981 1981-1986 1986-1991 1991-1996 1996-2001 2001-2006 2006-2011
Percentage (%)
Upper Secondary & Matriculation Non-degree post-secondary Degree course
33
Average Years of Schooling in Hong Kong and Singapore (aged 25+)
7.3
5.6 5.0
3.7
8.3
7.3 6.7
5.9
9.2 9.2
8.0 8.1
10.2 10.6
9.2 9.7
0
1
2
3
4
5
6
7
8
9
10
11
12
Hong Kong Singapore Hong Kong Singapore
Men Women
Years of Schooling
1981 1991 2001 2011
34
Total Factor Productivity in Hong Kong and Singapore 1960-2011
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
TFP Level at current PPPs(USA=1)
Hong Kong
Singapore
35
Labor Force Participation Rates in Hong Kong and Singapore 2011 (in %)
14.6
63.2
94.8
97.4
94.8
79.3
30.2
75.6
15.8
64.5
92.1
92.1
89.2
64.9
11.5
67.0
9.8
62.5
83.7
75.8
68.9
47.6
11.6
57.0
15.2
64.6
79.9
69.7
61.8
33.4
3.0
49.6
100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100
15-19
20-24
25-34
35-44
45-54
55-64
65+
Overall
Labor Force Participation Rate%
Age Group
Hong Kong-Women Singapore - Women Hong Kong- Men Singapore - Men
36
Men Women
Percentage of Men not in the Labor Force for No Compelling Reason by Age
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
1976 1981 1986 1991 1996 2001 2006 2011
% of relevant age group Men
Age 20 to 29
Age 30 to 39
Age 40 to 49
Age 50 to 59
37
Percentage of Women not in the Labor Force for No Compelling Reason by Age
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
1976 1981 1986 1991 1996 2001 2006 2011
% of relevent age group Women
Age 20 to 29
Age 30 to 39
Age 40 to 49
Age 50 to 59
38
Social Welfare and Public Expenditures
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
0
10
20
30
40
50
60
70
80
90 natural logarithm
% of total public expenditure Social welfare Expenditure as a % of total public expenditure
log[Social Welfare Expenditure (HK$bn)]
39
Household Income Inequality
• Household earnings is the sum of the earnings of individual members
• Depends on each member’s earnings, i.e., wage rate and hours worked
• Household size matters. Whether members work matters. Who marries who matter. Who divorces matter.
• Why? And how has this changed over time? • All these factors affect household earnings
inequality
40
Do Minimum Wages Reduce Inequality?
• Here is an example of a theory without a fact • Minimum wages are introduced to help poor
families • Will it do so? What is your intuition? • What proportion of the minimum wage
workers are in low-income households?
41
Number of Households and Households with Minimum Wage Workers by Income Deciles 2011
42
8,115
15,412
20,302
17,188 15,917
14,684 14,226
8,094
4,353 2,662
3.1%
6.7%
7.6%
8.2%
6.4%
7.0%
4.9%
3.9%
1.9%
1.2%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
9.0%
0
5,000
10,000
15,000
20,000
25,000
the Lowest Decile
2nd Decile 3rd Decile 4th Decile 5th Decile 6th Decile 7th Decile 8th Decile 9th Decile the Highest Decile
No. of Households Households with Minmum Wage Workers
Households with Minmum Wage Workers as % of households in this decile
Marital Sorting
• Educated men marries educated women • More women became well educated over time and
therefore more working women • Over time households with well educated couples
become a two-income family • M:100+W:50 => HH:100; M:100+W:75 => HH:175 • Households with less well educated couples remain a
one-income family • M:60+W:30 => HH:60; M:60+W:45 => HH:60
43
• 50 years ago most women did not work, even well educated women
• Today more well educated women work, but many of the less well-educated still do not work
• Household earnings inequality therefore increases even if individual earnings inequality do not
44
Single Parenthood
• Divorces have increased rapidly in HK • Higher among low-income families • Consider two households:
– Family R => M=100 W=100 Total=200 – Family P => M=50 W=50 Total=100 – Average household income = 150
• Now Family P divorces – Family R => M=100 W=100 Total=200 – Family P1 => M=50 – Family P2 => W=50 – Average household income = 100 inequality widens
45
Rising Incidence of Divorce 1971-2011
0.79 1.66 2.93 3.98 5.11 6.54 7.83 8.27
9.5 16.7 19.5
29.4 33.8
52.4
74.2
100.7
117.4
6.0%
8.7% 9.2%
8.6%
9.5%
11.5%
13.6%
15.4%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
0
10
20
30
40
50
60
70
80
90
100
110
120
130
1971 1976 1981 1986 1991 1996 2001 2006 2011
per 1000 households
Number of divorces granted per 1000 households
Number of divorced individuals per 1000 households
Percentage of single parents among ever-married households (age≤65 with children≤age18)
46
HK Divorce Rate among Top 10 in the World
• Russia 4.8 Switzerland 2.8 • Belarus 4.1 Ukraine 2.8 • USA 3.6 • Gibraltar 3.2 Hong Kong 2.9 • Moldova 3.1 • Belgium 3.0 China 2.0 • Cuba 2.9 UK 2.0 • Czech Rep 2.9 Singapore 1.5
47
First Marriages, Divorces and Remarriages
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000 19
76
1977
19
78
1979
19
80
1981
19
82
1983
19
84
1985
19
86
1987
19
88
1989
19
90
1991
19
92
1993
19
94
1995
19
96
1997
19
98
1999
20
00
2001
20
02
2003
20
04
2005
20
06
2007
20
08
2009
20
10
2011
20
12
No. First marriage of both parties Divorce decrees granted Remarriage
48
Number of Divorced and Separated Men per 1000 Households by Housing Tenure
0
10
20
30
40
50
60
70
80
90
100
1976 1981 1986 1991 1996 2001 2006 2011
per 1000 households
Divorced Private Housing Renters
Divorced Public Housing Renters
Divorced Private Housing Owners
Divorced Subsidized Sale Flats (HOS/PSPS/TPS etc.)
49
Number of Divorced and Separated Women per 1000 Households by Housing Tenure
0
10
20
30
40
50
60
70
80
90
100
1976 1981 1986 1991 1996 2001 2006 2011
per 1000 households
Divorced Private Housing Renters
Divorced Public Housing Renters
Divorced Private Housing Owners
Divorced Subsidized Sale Flats (HOS/PSPS/TPS etc.)
50
Housing Tenure of Divorced Men and Women (‘000s)
Marital Status and Sex
Year Public Renter
Private Renter
Subsidized Flats
Private Owner
Total
Divorced men 1991 8 5.9 1 5 21
2001 21 15 6 13 56
2011 41 19 11 21 92
Divorced women 1991 9 7 2 11 29
2001 33 24 11 25 92
2011 78 33 23 42 176
4/16/2014 51
Why are there More Divorced Women than Men?
• Cross-border brides • After China’s opening many low income single
men living alone (some in caged homes or sub-divided units) can enjoy family life
• This has increased the demand for public rental housing
• For almost two decades, 40% of marriages involving a HK resident is a cross border one
52
Cross border marriages in China and HK
782 4,380
21,268 15,669
15,028
5,678
27.9%
42.3% 40.7%
0%
10%
20%
30%
40%
50%
60%
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
(No.)
Number of Marriages registered in China(estimated)- Successful Applicants of Certificate of Absence of Marriage Records (CAMR) for the purpose of marrying in the mainland of China Number of Marriages registered in HK - Bridegrooms or brides from the mainland of China
Bridegrooms or brides from the mainland of China (Marriages registered in HK or China as % of total number of Marriages registered in HK and China
53
Are Recent Immigrants More Likely to Divorce?
• No. • Multiple regressions of divorce rates of men and
women on years of arrival of recent immigrants over 0-5,6-10, 11-15,16-20 year intervals show their divorce rates are significantly lower
• Recent immigrants more likely to stay married • Stories of fake marriages among recent immigrants
are probably exaggerated • However, in 2006 and 2011 those who live in either
public or private rental housing are about twice as likely to be divorced 54
Divorce Rates among Recent Immigrant Men Regression Effects
1976 1981 1986 1991 1996 2001 2006 2011 Divorce rate
0.011 0.012 0.016 0.016 0.025 0.033 0.042 0.048
Immig05 -52% -81% -48% -55% Immig10 -47% -65% -73% -45% -52% Immig15 -23% -49% -44% -66% Immig20 -81% -39% -30% -43% Private owner -96% -67% -66% -74% -78% -103% -112% -88% Public owner -97% -85% -92% -123% -134% -84% Public renter -103% -52% -36% -40% -31% -43% -36%
55
Divorce Rates among Recent Immigrant Women Regression Effects
1976 1981 1986 1991 1996 2001 2006 2011 Divorce rate
0.008 0.009 0.015 0.019 0.031 0.048 0.068 0.079
Immig05 -55% -63% -73% -102% -111% -86% -53% Immig10 -52% -45% -42% -78% -29% Immig15 -37% -33% -31% Immig20 -27% -18% -18% Private owner -61% -41% -50% -53% -82% -108% -103% -80% Public owner -70% -57% -103% -116% -107% -67% Public renter -82% -59% -74% -65% -65% -54% -13% 17%
56
Duped? Abused? Taken advantage of, probably, but surely exaggerated
57
Who is Duping Who?
58
Intergenerational Mobility in HK
• Regress percentile rank of schooling attainment of 25-29 year old men and women, who live with parents, against their mother’s or father’s percentile rank of schooling attainment (holding constant sex alone)
• Estimated coefficient has declined over 1976-1986, but has been quite stable during 1991-2011
• Lower estimates for 1991 and 1996 probably reflect the effects of emigration ahead of 1997
• Men have a lower schooling attainment than women
59
• More variables were included into separate multiple regressions
• Schooling attainment of individuals are lower if they live with a single parent
• Schooling attainments are lower if they themselves are recent immigrants, but the effect of whether parents are recent immigrants is weak
• Schooling attainment is lower if they live in public rental housing, but higher if parents are homeowners
60
Relationship between father and child percentile ranks in schooling
1976 1981 1986 1991 1996 2001 2006 2011 Father school 0.430 0.375 0.336 0.254 0.265 0.312 0.303 0.318
Father school 0.389 0.347 0.313 0.227 0.234 0.266 0.253 0.264 Male child -5.07 -4.54 -4.22 -5.41 -6.41 -5.58 -5.12 -4.30 Parent Immig05 15.52 -2.42 -4.53 -5.83 1.37 -7.77 -3.65 -4.33 Child Immig05 - -4.63 2.17 -10.8 -6.38 -12.9 -16.5 -5.53 Private owner 5.21 5.86 7.75 6.26 5.68 5.82 4.91 4.46 Public owner - 15.0 11.6 3.87 5.07 1.70 -0.13 -0.16 Public renter -9.40 -4.75 -0.48 -1.90 -1.93 -3.99 -6.51 -7.75 Single father -5.51 -6.04 -5.29 -6.80 -7.84 -4.90 -5.78 -2.62 Single mother -2.82 -4.08 -4.01 -3.75 -4.00 -4.76 -5.36 -3.64
61
Relationship between mother and child percentile ranks in schooling
1976 1981 1986 1991 1996 2001 2006 2011 Mother school 0.421 0.370 0.326 0.279 0.261 0.307 0.298 0.293
Mother school 0.384 0.343 0.303 0.252 0.232 0.267 0.252 0.240 Male child -4.84 -4.33 -4.50 -5.13 -6.29 -5.55 -4.91 -4.35 Parent Immig05 9.81 -2.34 -4.55 -5.94 -0.24 -6.93 -3.36 -3.03 Child Immig05 -10.2 -4.51 2.27 -11.1 -6.37 -13.7 -18.1 -5.99 Private owner 5.56 5.98 7.98 6.01 6.05 5.87 5.66 4.14 Public owner - 12.9 11.7 4.00 5.62 2.07 0.84 -0.73 Public renter -9.02 -4.67 -0.23 -1.64 -1.39 -3.84 -5.47 -7.89 Single father -5.84 -6.95 -5.59 -7.25 -8.26 -5.52 -6.84 -3.22 Single mother -1.47 -2.74 -3.41 -3.23 -3.41 -4.49 -5.19 -3.48
62
Household and Individual Income Inequality
63
0.430 0.429 0.451 0.453 0.476 0.518 0.525 0.533 0.537
0.411 0.398 0.42 0.434 0.461 0.466 0.472 0.487
6.22
7.44
6.75
8.15
8.82
10.19
10.84
13.11
5.00
4.26
5.00 4.61
5.00
6.05 6.38 6.33
0
2
4
6
8
10
12
14
0.350
0.370
0.390
0.410
0.430
0.450
0.470
0.490
0.510
0.530
0.550
1971 1976 1981 1986 1991 1996 2001 2006 2011
Ratio Gini coefficient
Gini-coefficient of Monthly Household Income (according to C&SD estimates)
Gini-coefficient of Monthly Individual Income
Household income percentile ratio P90/P10
Individual income percentile ratio P90/P10
• Should we be worried? • About what?
– Inequality? – Intergenerational mobility?
• Individual earnings inequality has increased over time, but not by a lot
• Household earnings inequality has risen by more • Intergenerational upward mobility has not changed
very much over time
64
What is to be done? Vladimir I Lenin
65
It Pays to Invest in Early Education
• Nobel economist James Heckman evaluated numerous programs and concluded that early interventions makes a huge difference
• IQ becomes more difficult to change after 10 • Other factors like conscientiousness and motivation
also play a huge role • When it comes to the matter of forming skills,
parenting is critical • Alfred Marshall, in his Principles of Economics,
remarked “The greatest capital that you can invest in is human capital, and, of that, the most important component is the mother.”
66
Head Start Programs for Promising Youth without Means
• Some kids grow up in one of the worst circumstances financially, living in some of the worst ghettos, and still they succeed
• They succeed because an adult figure, typically a mother, maybe a grandmother, nourishes the kid, supports the kid, protects the kid, encourages the kid to succeed
• Some body or some program has to spend time with the kid; it is a time intensive activity
• This overcomes the bad environment he was born into
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A Toddler can Barely Walk Unassisted after One Year A Foal can Stand Up to Feed One Hour after Birth
Throwing Money at It Does Not Always Work
• What the US War against Poverty was doing 50 years ago was to give people money to change poverty and hopefully raise the standards of the next generation
• But it didn’t seem to have done much good • What we failed to understand was that the real
poverty was parenting (or an equivalent substitute spent using time)
• Of course, when the kid is starving and doesn’t get any food, then of course money would matter, but this is not what we are facing today here
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• So what we are getting now is kids growing up in a new form of child poverty
• That new form of child poverty is actually threatening their ability to go to school, their willingness to learn, their attitudes and their motives
• That’s a major source of worsening intergenerational mobility and poverty
4/16/2014 70
How Housing Policy Can Lower Divorce Rates, Improve Intergenerational Mobility and Reduce Poverty
• Homeownership encourages the poor not to divorce • Poor children get a better deal • Why concentrate the poorest in Public Rental
Housing estates where divorce rates are highest • Better role models in a mixed neighborhood is good
for children’s development • A city of homeowners is less politically divided • Today’s median household income is $20000 plus,
the poor can never become homeowners unless the property market collapses permanently
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How Housing Strategy Can Lower Divorce Rates, Raise Intergenerational Mobility and Reduce Poverty?
• Current housing strategy will push our the fiscal budget further into deficit
• Historically for every 4 PRH units we build we also build 2 HOS units
• 1 of the HOS units is allocated to PRH households the other to low income private sector renters
• PRH units incur recurrent losses and have to be financed by profits from sale of HOS units
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Percentage Shares of Housing, Education, Health and Social Welfare in Government or Public Expenditure,
1971/72-2014/15
1.9
13.8 14.1
10.4
12.9
20.0
22.7
17.1
6.1
16.8
5.8
0
2
4
6
8
10
12
14
16
18
20
22
24
1971
-72
1972
-73
1973
-74
1974
-75
1975
-76
1976
-77
1977
-78
1978
-79
1979
-80
1980
-81
1981
-82
1982
-83
1983
-84
1984
-85
1985
-86
1986
-87
1987
-88
1988
-89
1989
-90
1990
/91
1991
/92
1992
/93
1993
/94
1994
/95
1995
/96
1996
/97
1997
/98
1998
/99
1999
/00
2000
/01
2001
/02
2002
/03
2003
/04
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
2011
/12
2012
/13
2013
/14R
20
14/1
5F
As% of Government Expenditure/Public
Expenditure
Social welfare Health Education Housing
As a % Government Expenditure
As a % Public Expenditure
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Actual and Projections of Population Numbers and Health Care Cost Standardized Population Numbers
1950-2100
0
2,500
5,000
7,500
10,000
12,500
15,000
17,500
20,000
22,500
25,000
27,500
30,000
1950
19
55
1960
19
65
1970
19
75
1980
19
85
1990
19
95
2000
20
05
2010
20
15
2020
20
25
2030
20
35
2040
20
45
2050
20
55
2060
20
65
2070
20
75
2080
20
85
2090
20
95
2100
('000 persons)
Health Care Cost Standardized Population
Health Care Cost Standardized Population (C&SD)
Health Care Cost Standardized Population (UN)
Total Population (actual)
Total Population(C&SD Projection)
Total Population(UN Projection)
Projection
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Public and Private Health Expenditure Projection (2012-2041)
• Public health expenditure will explode in the future • Projections from 2012-2041 are as follows: • Optimistic scenario 2.9% to 5.8% of GDP • Pessimistic 2.9% to 7.2% of GDP • It depends on costs rising as they have done so in the
past • Increasing the supply of health and medical care
personnel will help hold down costs
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Re-orient Subsidized Housing Strategy
• Re-orient our housing strategy towards subsidized homeownership scheme (SHS) for low-income families
• Similar in nature to Singapore’s HDB • Land premiums on SHS units must be discounted to
affordable levels benchmarked against income
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Subsidized Homeownership Scheme (SHS)
• Unify PRH, TPS and HOS units into a single SHS scheme
• Convert existing PRH, TPS and HOS units into SHS • Convert PRH into SHS scheme via a revised TPS • Reduce exorbitant land premium for HOS and TPS
units to converge on SHS units • Allow no restrictions on resale after 5 years on open
market • Permit redevelopment rights
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80% Homeownership by 2023
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Happy Ending by 2023
Thank you
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