Income Inequality and An Economy in Transition

Transcription

1 Income Inequality and An Economy in Transition Li Gan Texas A&M University and Southwestern University of Finance and Economics April, 2014

2 Outline An Introduction to China Household Finance Survey Household income and Income Inequality in China Inequality and Insufficient Consumption Household Assets and the Housing Market Urbanization 2

3 An Introduction to China Household Finance Survey

4 Sampling In 2011, divide 2,585 counties/districts of the country in 28 provinces (except Tibet, Xinjiang, and Inner Mongonia) into 10 groups by per capita GDP and (PPS) randomly select eight counties/districts from each group. Total 80 counties. In 2013, revisit the households of An expansion of the sample size: the symmetric sampling. Ranking all counties in each province by per capita GDP. Draw counties in each province symmetric to the counties in new counties (total 262) are in the full sample.

5 Coverage of CHFS

6 Sampling Four communities (neighborhood, village) were PPS selected. Number of neighborhoods or villages are chosen based on the urban resident ratios. Total 320 communities. For each community, carefully mapping all apartments/houses to be used as the end-sampling frame. Based on local average housing prices, randomly draw between 20 to 50 households from each community. Total sample size: 8,438 households/29,350 individuals.

7 Household Map for each community: manually drawn

8 Household Map for each Community: computer assisted

9 Implementation Help from local branches of the Central Bank and the Agricultural Bank of China. Representatives from local bank branches introduce the project and interview teams to local communities. Representatives from local communities introduce our interviewers to the selected households. Maintaining close relationships with communities is the key. Help from SRC/NORC/Fed/CHALRS/CFPS/CGSS

10 Implementation Every interviewer received 56 hours of training Implementation arrangements: Households had to refuse to be interviewed six times before being excluded from the survey Working in teams ensured safety and reduced moral hazard Dedicated and innovative interviewers (students) from Southwestern University of Finance and Economics.

11 Sample size 2011 sample: 8,438 households, 29,324 individuals. More than 600 students from SWUFE participated sample: 28,141 households, more than 99,000 individuals. More than 1,600 students from SWUFE participated.

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13 Overview of the Questionaire Demographic characteristics and labor market Assets and liabilities Non-financial assets Family business Land and real estates Vehicles Other non-financial assets Financial assets Social and Commercial Insurance Expenditure and non-labor income

14 Overview of the Questionaire Example: Financial assets Checking CD Stocks Bonds Mutual fund Derivatives Financial wealth-management products Non-RMB assets Gold Cash Lending

15 CHFS Low Refusal Rates Year Overall Urban Rural % 16.5% 3.2% % 15.4% 0.9% Refusal Rates of Old/New Sample in 2013 Overall Urban Rural 2013 New Sample 12.6% 17.4% 0.9% Successfully contacted 2011 sample 5.4% 8.2% 0.7% 2013 contact success rate 82.1% 2011 sample response rate 77.7%

16 Low refusal rate: international comparison Datasets Year Refusal rate Survey of Consumer Finance (SCF, US) 2007 AP Sample List Sample 32.3% 67.3% Consumer Expenditure Survey (CEX, US) 2005 Interview Diary 25.5% 29% Survey of Household Income and Wealth (SHIW, Italy) Eurosystem Household Finance and Consumption Survey (HFCS) % 2010 Belgium 57.6% Germany 69.7% France 30.0% Portugal 10.3% Finland 11.1%

17 Monthly Telephone Interviews We obtained households phone numbers from face-to-face interviews. Computer Assisted Telephone Interview (CATI) questionnaire includes: Expectations about interest rate, CPI, housing price, stock index Employment status Financial market participation and earning status Assets: house price, loan, vehicle, debts Income and consumption Indicators of rural area development

18 Monthly Telephone Interviews In April and July 2012 two rounds of telephone interviews (CATI) were successfully implemented First CATI from the second wave is already underway. So far 4442 samples are successfully completed. Benefits of CATI: A timely picture of Chinese households economic situation Quickly builds up a panel

19 Sample size large enough? Randomness is a lot more important than the sample size for a sample to be representative. Even a sample of 400 thousand households, when compared to China s 400 million people, is so tiny. Sample size helps determining the standard errors in statistical analysis. Consider average income at 54,000 RMB and standard deviation at 200K RMB. If a random sample of 8,438, the sampling error is 2,177 RMB. If a random sample of 28,000, the sampling error is 1,190 RMB. If a random sample of 400,000, the sampling error is 316 RMB.

20 Is it representative? Comparing with the NBS data Indicator NBS CHFS Urban Population (by residence) Household residence (by Hukou) Urban Rural Average Age Proportion of Males

21 Sample age structure comparison Population Age Structure Census 2010 CHFS 2011

22 Building a baseline database for China Original motivation is to for academic purpose. Later development suggested different perspectives. Asset information provides a key baseline information. Household income and much of other information provide verification for NBS data. Proven to be useful for business and people s daily life.

23 Household Income and Income Inequality

24 Disposable Income and its Growth Urban Rural NBS CHFS CHFS / NBS NBS CHFS CHFS / NBS ,109 24, % 5,919 9, % ,565 28, % 7,917 10, % Two year growth rate 28.2% 16.3% 33.7% 11.7% CHFS per capita income is higher than NBS, but its growth rate is lower than NBS.

25 Household Income Gini Coefficient Overall Urban Rural NBS 2010: : : world average:0.44

26 Per capita income by category in 2012 NBS Urban CHFS CHFS / NBS NBS Rural CHFS CHFS / NBS Salary % % Business % % Asset income % % Transfer income % % CHFS has higher income in salary, business and transfers than NBS.

27 Why so much higher than NBS? Comparing distributions Vastly different at low income groups and high income groups. Caused by difference in high income groups

28 2012 per capita income by quintile for urban residents NBS CHFS CHFS/NBS Overall 24,565 30, % Lowest 20% 10,352 3, % 20% 40% 16,761 10, % 40% 60% 22,419 17, % 60% 80% 29,814 27, % 80% 90% 39,605 43, % Highest 10% 63, , % High income group: CHFS >> NBS

29 2012 per capita income by quintile for rural residents NBS CHFS CHFS/NBS Overall 7,917 11, % Lowest 20% 2, % 20% 40% 4,808 3, % 40% 60% 7,041 6, % 60% 80% 10,142 10, % Highest 20% 19,009 28, % High income group: CHFS >> NBS

30 Quantiles of per capita disposable income Urban 2012 Rural Quantiles CHFS NBS (estimated) CHFS/ NBS CHFS NBS (estimated) CHFS/ NBS 25% % % % % % Estimation is carried by fitting a log-normal distribution

31 Why CHFS Gini is much higher than NBS? Major differences in the rich household sample. Nationwide Urban Rural Excluding the lowest 0.5% sample Excluding the lowest 5.0% sample Excluding the highest 0.5% sample

32 How to understand the high Gini? A consequence of market economy and efficient resource allocation. More developed market economies have higher Ginis than less developed market economies. East: 0.60 Central: 0.56 West: 0.54 Very little change of Gini when excluding households working in monopoly industries and public sector employees. Excluding households work in monopoly industries: 0.60 Excluding households work in public sector: 0.60

33 Gini of OECD countries based on market incomes Gini before transfer Gini coefficients of market income from OECD countries are close to 0.5. China has much higher heterogeneity than OECD countries, and very little income transfer programs. Gini in China is expected to be higher than 0.5.

34 Income Inequality and Insufficient Consumption

35 Rising Household Saving Rates Urban Rural Overall Urban Rural Overall Income CHFS Consumption Saving Rate 31.6% 22.8% 29.2% 33.3% 26.5% 31.8% Income NBS Consumption Saving Rate 29.5% 26.0% 28.7% 32.1% 25.4% 30.6%

36 Proportion of households have positive saving in that year Urban 56.8% 64.1% Rural 57.0% 55.6% Overall 56.9% 60.6%

37 Unequal distribution of saving Saving rates Income group Highest 5% 73.5% 72.2% Highest 10% 66.5% 45.2% Highest 25% 56.4% 42.9%

38 Proportions of total saving and financial assets from high income households (2012) Percentage of total Saving Financial assets Highest 20% Highest 10% Highest 5% Highest 20% Highest 10% Highest 5% Urban 75.8% 62.4% 50.3% 54.3% 39.6% 27.4% Rural 76.8% 59.4% 44.4% 50.6% 37.2% 26.5% Overall 77.1% 62.4% 50.6% 60.6% 44.6% 30.6%

39 Proportion of positive saving by non-housing assets and by income 2010 Non- Housing Asset Lowest 25% Lowest 25% Income groups 25%-50% 50%-75% Highest 25% 19% 53% 75% 89% 25%-50% 14% 53% 82% 90% 50%-75% 4% 45% 74% 85% Highest 25% 1% 26% 53% 84% Poor do not have money to consume. Rich already consume at the optimal.

40 Proportion of positive saving by non-housing assets and by income 2012 Urban Income category Non- Housing Asset Lowest 25% Lowest 25% 25%-50% 50%-75% Highest 25% 24% 73% 95% 98% 25%-50% 20% 67% 89% 96% 50%-75% 10% 55% 80% 95% Highest 25% 7% 34% 70% 90%

41 Various measures to encourage Chinese consumption had limited success China s poor don t have money to spend China's rich are already spending what they need, and pocketing most of the rest. Unequal income distributions and liquidity constraints cause insufficient domestic demand. Improving income distribution would promote economic restructuring.

42 Short Term Solution: Transfer Payments

43 Increasing the Minimum Wage Does Not Have Much Effect on the Gini Coefficient Overall Urban Rural GINI before adjustment Strict enforcement of the current minimum wage Minimum wage increases by: % %

44 Income Tax Policy Does Not Have Much Effect on Gini Coefficient Household income Salary and wage income Before tax After tax Before tax After tax Overall Urban Rural

45 Brazil Experience Transfer payment/gdp(%) Gini Transfer payment/gdp Gini A large scale of transfer payment can reduce Gini effectively

46 Transfer payments can effectively reduce Gini Gini before transfer after transfer

47 Ratio of social welfare spending to fiscal expenditure : China vs US China U.S. Excluding social security funds 12.3% 36.6% Including social security funds 21.2% 46.7% According to the US Congressional Budget Office: the poorest 20% of households: market income: $ 7,500; after transfer payments: $ 30,000.

48 Financial Resources to Implement Large-scale Government Transfer Payments In 2012 China's total fiscal revenue was more than 11.7 trillion yuan, an increase of 1.35 trillion RMB ( average annual growth of 1.62 trillion) State-owned enterprises realized profits of 1.98 trillion RMB in 2010, more than 2 trillion RMB in Current state budget deficit is 1.6% of GDP, accounting for only 8% of tax revenues; room for additional budget deficit for redistribution. 70% state-owned profit +50% incremental revenue + additional deficit (GDP 2%) = 3.8 trillion RMB: redistribution amount reaches 36% of government spending, similar to the US level.

49 3.8 trillion RMB in Transfer Payments Can Dramatically Narrow the Income Gap Subsidy per family (Yuan) Overall City Rural Before transfer Subsidize all 9, Subsidize the bottom 80% 12, Subsidize the bottom 60% 15,

50 Incentive Compatible Welfare System Conditional Cash Transfer (CCT) project Motivate families health and education investments Example: Free Lunch Program Earned Income Tax Credit system (EITC) Negative tax rate for working class 30% of American households benefit from this system, according to documented negative rates of up to 30% Currently happening within governments

51 Non-production government transfers in China used for consumption Income group before subsidies % of households have subsidies % of subsidies used for consumption Lowest 20% 30% 77% 20%-40% 20% 56% 40%-60% 17% 29% 60%-80% 13% 20% Highest 20% 11% 9% Overall 18% 48% Transfers to low-income households can effectively raise consumption.

52 Long Term Solution: Education

53 Comparison of China and OECD Countries Expenditures on Education per Student (USD) Primary Middle High Higher Education Japan ,729 8,985 9,527 15,957 S. Korea ,658 7,536 11,300 9,513 US ,109 12,247 12,873 29,201 OECD Average ,719 8,854 9,755 13,728 China , ,547 Chinese government spends too little in education.

54 Income gap narrows as the education increases Gini Coefficient Primary school or below 0.56 Middle or high school 0.56 Junior college 0.52 College or above 0.50

55 Improving the educational can lower the Gini in the long run Overall Urban Rural Improve the education to: -Average level of the OECD countries Average level of the US

56 Conclusions The current income inequality in China is substantial. High Gini coefficients are common in economies with high growth rates, and it s also a natural consequence of the efficient allocation of resources. In short-term, China s government has fiscal capacity to reduce the income inequality through the transfer policy. In long-term, China s government can invest more in education and reduce the inequality of opportunity to reduce the income gap.

57 Household Wealth and Housing

58 Growth rates of Household Wealth Total assets Housing Overall 19.6% 26.8%

59 80.0% 60.0% 40.0% 20.0% 0.0% Household asset distribution in 2011 Top 10% s share in total assets:63.9% 63.9% 2011 年

60 Household Asset Gini Coefficients in Overall Urban Rural

61 Asset inequality improved substantial over last two years 80.0% 60.0% 40.0% 20.0% 0.0% Middle-asset households (30%-70%) s share in total assets: 2010 : 10.7% 2013: 13.5% 60.6% 2011 年 2013 年

62 Household Asset Gini decreased Overall 全国 Urban 城市 Rural 农村 2011 年 2013 年

63 Asset components in China and US China US Housing 62.7% 66.4% 40.6% Agriculture 0.5% 1.3% Land 4.8% 3.5% Business 16.4% 11.8% 17.5% Vehicle 3.1% 4.5% 3.2% Other non-financial asset 4.0% 2.3% 0.8% Financial asset 8.3% 10.1% 37.9% Huge difference in housing and financial assets

64 70.0% 60.0% Shares of different assets 66.4% 62.7% 50.0% 40.0% 30.0% 20.0% 10.0% 16.8% 13.2% 4.8% 3.5% 10.1% 7.1% 6.8% 8.3% 0.0% 农业工商业 Business Housing 房屋 Land 土地耐用品汽车 Durable/car 金融资产 Financial 2011 年 2013 年

65 Housing wealth as a percentage of total wealth Price/income ratio 90.0% 60.0% 30.0% 83.8% Beijing 25 Shanghai 76.5% % 青海省山东省宁夏回族自 安徽省四川省陕西省广西壮族自 湖北省江西省河北省吉林省河南省内蒙古自治区黑龙江省湖南省山西省重庆市云南省广东省甘肃省浙江省海南省辽宁省天津市福建省贵州省上海市江苏省北京市 0

66 The Rich:Top 5% Criteria Quantile Average Wealth Average net wealth Average Income By wealth 5% By net wealth 5% By income 5% 2,629,850 6,507,023 6,205, ,811 2,534,100 6,489,605 6,225, , ,510 3,809,924 3,643, ,095

67 The Rich:Top 1% Criteria Quantile Average Wealth Average net wealth Average Income By wealth 1% 7,393,500 16,300,000 15,400, ,322 By net wealth 7,132,000 16,300,000 15,500, ,322 1% By income 1% 485,000 8,051,315 7,767,108 1,151,662

68 Immigration 14.0% 12.0% 11.6% 10.0% 8.0% 6.0% 6.0% 6.8% 8.1% Plan Wait and See 4.0% 2.0% 2.3% 2.8% 0.0% National Top 5% Top 1%

69 Home ownership in the city Home ownership rate % with only one house % with two or more houses % 69.2% 15.5% % 68.1% 18.9% Home ownership: World average: 63% US: 65% Japan: 60%

70 Housing Demand No house Total Demand Residential demand Has house New migrants House in a different city Living with parents Annual incremental demand New adults Demolition and relocation 70

71 Sources of incremental demand 2012 no house 14.6% Has house but house in a different city 6.1% Has the demand of living apart 5.6% Total residential demand in % 26.3% Total residential demand in units million Upgrading demand in % 13.6% Upgrading demand in units million

72 Housing Supply Total Demand Housing stock Incremental supply Multi-housing Commercial residential housing Production capacity: startups

73 Demand and Supply Analysis 2012 Current total residential demand Current total supply Difference Annual incremental demand Startups in million 47.1 million 38.8 million 5.8 million 13.3 million The housing demand will be satisfied within 5 years given current industry capacity. Only 40% of current capacity is needed to satisfy incremental demand.

74 % of home buyers housing status at the purchasing year 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% < 首套房 No house 改善型住房 Upgrading 投资性购房 Investment

75 Regulation suggestions of housing market Basic characteristics: Oversupply price expectation leads to price appreciation. Regulation suggestions: Less new construction, particularly less affordable housing construction. Push the existing stock into the market Effectively guide price expectation

76 Provide accurate information to the market to help develop reasonable price expectation: Put more efforts on collecting and releasing information in time Encourage independent research organization to complement government effort. Replace affordable housing construction with rental vouchers. Make use of the stock of multiple houses. Build an effective renting market.

77 Property tax plan Tax rate Tax Revenue (RMB) Shanghai Plan 8.4 billion New Purchase only 10% 902 billion All houses 0.5% 902 billion Multiple houses only 2.1% 902 billion Total land sales were 4.1 trillion in % of land sales or 902 Billion in 2013 was fiscal net revenue, the rest was cost and compensation.

78 Property tax plan in other countries Taxable Properties Tax rate US All 1%-3% Spain All 3% Germany All 1%-1.5% France All 3% Singapore First house Others 4% 10%

79 Tax burden of different income groups: tax on multiple houses Income interval Tax per household Household income Tax/income Below 25% 13,964 7, %-50% 12,778 32, %-75% 11,907 62, %-90% 17, , %-95% 23, , %-99% 34, , Above 99% 57,538 1,311,

80 Houses with Small-Property-Right In 2012, average housing price is 6,993 RMB per square meter, where the land sales amounts to 2,934 RMB per square meter. Small-property-right houses: 4.7% of total stock. Average price: 2,236 RMB per square meter. 18% of sales of commercial housing in If small-property-right houses pay average land sales of 2,934 RMB per square meter to become full-property-right 84% of local government net revenue Price is still 26% lower than commercial housing.

81 Urbanization

82 2013 Population flows Total population By registration ( hukou ) By residence Percentage Total number of migrants Rural 45.2% Rural household Urban area: Same county 13.5% 181 Millions Total population Urban area: Other county 5.2% 70 Millions Urban household Local downtown 31.1% Urban migrants 5.1%

83 Proportion of rural households who are migrants by age-groups 70% 60% 58.7% 50% 40% 30% 46.6% 30.5% 25.8% 40.1% 20% 10% 0% and above all

84 Proportion of rural households who are migrants by education 80% 74.60% 70% 60% 57.40% 50% 40% 39.00% 30% 20% 23.10% 10% 0% no formal education elementary or middle school high school college or above

85 Prediction of urbanization rate in next five years Urbanization Rate Nationwide 0.84% First-tier cities 0.39% Second-tier cities 0.42% Third-tier cities 0.55% Forth-tier cities 0.88% Average urbanization rate over last five years: 1.35%

86 Li Gan Thank You! Let China understand herself. Let the world know China.