Understanding Inequality and Intergenerational Mobility in Hong Kong

Endowed Professorships Public Lecture Series: I The University of Hong Kong 11 April 2014 Understanding Inequality and Intergenerational Mobility in Hong Kong Y C Richard Wong Philip Wong Kennedy Wong Professor in Political Economy

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

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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

Intergenerational Mobility Estimates for the 1971-1993 Birth Cohorts Rank-Rank Slope 0 0.2 0.4 0.6 0.8 1971 1974 1977 1980 1983 1986 1989 1992 Child's Birth Cohort Income Rank-Rank Forecast Based on Age 26 (Child Age 30; SOI Sample) Income and College Attendance Income Rank-Rank (Child Age 26; Pop. Sample) College-Income Gradient (Child Age 19; Pop. Sample)

Probability Child in Top Fifth of Income Distribution 0% 10% 20% 30% 40% Probability of Reaching Top Quintile by US Birth Cohort 1971 1974 1977 1980 1983 1986 Child's Birth Cohort Parent Quintile Q1 Q3 Q5 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 90,000 80,000 Mean Earnings (HK$) 70,000 60,000 Degree or above 50,000 40,000 30,000 Post Secondary 20,000 10,000 0 Secondary and Matriculation Primary or lower 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 Age 29

Hong Kong- Mean Earnings by age, 1981 12,000 11,000 Mean Earnings(HK$) 10,000 9,000 8,000 Degree or above 7,000 6,000 5,000 4,000 3,000 2,000 1,000 0 Post Secondary Secondary and Matriculation Primary or lower 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 Age 30

Hong Kong - Earnings of degree graduates divided by secondary and matriculation students, 1981 & 2011 6.0 Ratio 5.5 5.0 4.5 4.0 2001 3.5 3.0 2.5 1981 2.0 1.5 1.0 0.5 0.0 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 Age 31

Annual Percentage Growth of Real Median Monthly Individual Income by Decile Groups (1981-2011) 8 7 Annual Percentage Growth 1981-1996 1996-2011 7.16 6 5.69 5.68 5 5.04 5.12 4.74 4.72 4.46 4.26 4.62 4 3 2 1 0-1 0.25 1st decile (lowest) 1.99 2.10 2.08 1.50 1.34 1.08 0.70 0.37-0.20 2nd 3rd 4th 5th 6th 7th 8th 9th 10th (highest) Decile Income Groups 32

Annual Percentage Increase in Population Aged 15+ by Education (1961-2011) 24 22 20 18 16 14 12 10 8 6 4 2 0-2 -4-6 -8 Percentage (%) 21.6 15.2 13.6 12.5 5.1 4.6 6.2 5.2 5.4 4.0 4.2 4.1 4.1 4.3 2.8 3.1 0.9 0.4 0.8 0.3 1.3 1.2-2.3-1.9-4.9 1961-1971 1971-1976 1976-1981 1981-1986 1986-1991 1991-1996 1996-2001 2001-2006 2006-2011 Upper Secondary & Matriculation Non-degree post-secondary Degree course 33

Average Years of Schooling in Hong Kong and Singapore (aged 25+) 12 11 10 9 8 7 6 5 Years of Schooling 7.3 8.3 10.2 9.2 9.2 7.3 5.6 10.6 5.0 6.7 9.2 8.0 8.1 5.9 9.7 4 3.7 3 2 1 0 Hong Kong Singapore Hong Kong Singapore Men 1981 1991 2001 2011 Women 34

Total Factor Productivity in Hong Kong and Singapore 1960-2011 1.4 TFP Level at current PPPs(USA=1) 1.2 1.0 0.8 0.6 Hong Kong 0.4 Singapore 0.2 0.0 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 35

Labor Force Participation Rates in Hong Kong and Singapore 2011 (in %) Men 75.6 79.3 89.2 94.8 92.1 97.4 92.1 94.8 67.0 64.9 64.5 63.2 30.2 11.5 15.8 14.6 3.0 11.6 15.2 9.8 33.4 49.6 47.6 57.0 Women 61.8 68.9 69.7 75.8 79.9 83.7 64.6 62.5 Age Group Overall 65+ 55-64 45-54 35-44 25-34 20-24 15-19 100 90 80 70 60 50 40 30 20 10 0 10 20 30 40 50 60 70 80 90 100 Labor Force Participation Rate% Hong Kong-Women Singapore - Women Hong Kong- Men Singapore - Men 36

Percentage of Men not in the Labor Force for No Compelling Reason by Age 5.0% 4.5% % of relevant age group Men 4.0% 3.5% 3.0% 2.5% Age 20 to 29 Age 30 to 39 Age 40 to 49 Age 50 to 59 2.0% 1.5% 1.0% 0.5% 0.0% 1976 1981 1986 1991 1996 2001 2006 2011 37

Percentage of Women not in the Labor Force for No Compelling Reason by Age 5.0% 4.5% % of relevent age group Women 4.0% 3.5% 3.0% 2.5% Age 20 to 29 Age 30 to 39 Age 40 to 49 Age 50 to 59 2.0% 1.5% 1.0% 0.5% 0.0% 1976 1981 1986 1991 1996 2001 2006 2011 38

Social Welfare and Public Expenditures 90 % of total public natural expenditure Social welfare Expenditure as a % of total public expenditure logarithm 80 70 log[social Welfare Expenditure (HK$bn)] 4.5 4.0 3.5 60 3.0 50 2.5 40 2.0 30 1.5 20 1.0 10 0.5 0 0.0 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 25,000 No. of Households 8.2% Households with Minmum Wage Workers 9.0% 20,000 6.7% 7.6% 6.4% 7.0% Households with Minmum Wage Workers as % of households in this decile 8.0% 7.0% 6.0% 15,000 4.9% 5.0% 10,000 3.1% 15,412 20,302 17,188 15,917 14,684 14,226 3.9% 4.0% 3.0% 5,000 8,115 8,094 1.9% 1.2% 2.0% 4,353 2,662 1.0% 0 the Lowest Decile 2nd Decile 3rd Decile 4th Decile 5th Decile 6th Decile 7th Decile 8th Decile 9th Decile the Highest Decile 0.0% 42

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 130 per 1000 households 18% 120 110 100 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) 13.6% 15.4% 16% 14% 90 11.5% 12% 80 70 8.7% 9.2% 8.6% 9.5% 10% 60 117.4 8% 50 40 30 20 10 0 6.0% 100.7 74.2 52.4 29.4 33.8 16.7 19.5 9.5 0.79 1.66 2.93 3.98 5.11 6.54 7.83 8.27 1971 1976 1981 1986 1991 1996 2001 2006 2011 6% 4% 2% 0% 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 50,000 45,000 40,000 No. First marriage of both parties Divorce decrees granted Remarriage 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 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 2012 48

Number of Divorced and Separated Men per 1000 Households by Housing Tenure 100 90 80 70 60 50 per 1000 households Divorced Private Housing Renters Divorced Public Housing Renters Divorced Private Housing Owners Divorced Subsidized Sale Flats (HOS/PSPS/TPS etc.) 40 30 20 10 0 1976 1981 1986 1991 1996 2001 2006 2011 49

Number of Divorced and Separated Women per 1000 Households by Housing Tenure 100 90 per 1000 households 80 70 60 50 Divorced Private Housing Renters Divorced Public Housing Renters Divorced Private Housing Owners Divorced Subsidized Sale Flats (HOS/PSPS/TPS etc.) 40 30 20 10 0 1976 1981 1986 1991 1996 2001 2006 2011 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 Cross-border brides Women than Men? 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 40,000 (No.) 60% 35,000 50% 30,000 25,000 42.3% 40.7% 5,678 40% 20,000 27.9% 30% 15,000 10,000 5,000 15,669 15,028 21,268 20% 10% 0 782 4,380 0% 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 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

No. Are Recent Immigrants More Likely to Divorce? 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 rate Divorce Rates among Recent Immigrant Men Regression Effects 1976 1981 1986 1991 1996 2001 2006 2011 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 rate Divorce Rates among Recent Immigrant Women Regression Effects 1976 1981 1986 1991 1996 2001 2006 2011 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 0.550 Gini coefficient Ratio 13.11 14 0.530 Gini-coefficient of Monthly Household Income (according to C&SD estimates) Gini-coefficient of Monthly Individual Income 12 0.510 0.490 Household income percentile ratio P90/P10 Individual income percentile ratio P90/P10 8.82 10.19 10.84 10 0.470 7.44 8.15 8 0.450 0.430 0.410 6.22 5.00 4.26 6.75 5.00 4.61 5.00 6.05 6.38 6.33 6 4 0.390 0.370 0.430 0.429 0.451 0.453 0.476 0.518 0.525 0.533 0.537 2 0.350 0.411 0.398 0.42 0.434 0.461 0.466 0.472 0.487 1971 1976 1981 1986 1991 1996 2001 2006 2011 0 63

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 67

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 69

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 71

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 72

Percentage Shares of Housing, Education, Health and Social Welfare in Government or Public Expenditure, 1971/72-2014/15 24 22 20 As% of Government Expenditure/Public Expenditure 20.0 As a % Government Expenditure As a % Public Expenditure 22.7 18 16 16.8 17.1 14 12 10 10.4 13.8 14.1 12.9 8 6 6.1 5.8 4 2 1.9 0 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 2014/15F Social welfare Health Education Housing 73

Actual and Projections of Population Numbers and Health Care Cost Standardized Population Numbers 1950-2100 30,000 27,500 25,000 22,500 20,000 17,500 15,000 12,500 ('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 10,000 7,500 5,000 2,500 0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100 74

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 75

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 76

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 77

80% Homeownership by 2023 78

Happy Ending by 2023 Thank you 79