1. Human Capital Estimates in China: New Panel Data on China by Provinces 1985-2010 Haizheng Li School of Economics Georgia Institute of Technology Email: haizheng.li@econ.gatech.eduhaizheng.li@econ.gatech.edu Qinyi Liu School of Economics and Trade Hunan University Bo Li China Center for Human Capital and Labor Market Research Central University of Finance and Economics Barbara Fraumeni Muskie School of Public Service University of Southern Maine Xiaobei Zhang School of Economics Zhejiang University of Finance and Economics 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

2. Human capital “The knowledge, skills, competencies and attributes embodied in individuals that facilitate the creation of personal, social and economic well-being” --OECD, 2001 Importance of Human Capital A central determinant of economic growth  Significant contributions to 30 years’ economic growth in China Enhances the ability in  Developing technological innovations  Adapting and implementing technologies developed Reduce poverty and inequality 2 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

3. Human capital Importance of Human Capital Measurement  Trace the distribution and dynamics of human capital  Aid empirical studies and policy analysis  Promote the creation of human capital satellite account 3 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

4. Human capital measurement Challenges The unique characteristics make it difficult to estimate its value  Partial measurements like education are commonly used  Lack of data  existing method cannot be applied to China  Arduous work for data collection, processing and calculation, especially at provincial level  Empirical researches desire panel data of human capital o Panel data of comprehensive measures of human capital at a state or province level are lacking for most countries including China 4 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

5. Research team and sponsors Research Team (starting in 2008) China Center for Human Capital and Labor Market Research (CHLR) special-term faculty, full-time faculty, doctoral and Master’s student, and staff Sponsors National Natural Science Foundation of China Central University of Finance and Economics 5 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

6. Methodology Jorgenson-Fraumeni Lifetime Income-based Approach Include all aspects of human capital services measured by market value Widely used in measuring a nation’s total human capital stock Argentina (Coremberg, 2010), Australia (Wei, 2007, 2008), Canada (Gu and Wong, 2009), India (Gundimeda et al., 2007), New Zealand (Le, Gibson, and Oxley, 2005), Norway (Liu and Greaker, 2009), Sweden (Ahlroth, Bjorkland, and Forslund, 1997), United Kingdom (O’Mahony and Stevens, 2004 and Jones and Chirpanhura, 2010), and the United States (Christian, 2010) The OECD human capital consortium OECD, 2010; Mira and Liu, 2010; Liu, 2011 China’s national level human capital Li et al., 2010; Li, Liang et al., 2013 6 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

7. Methodology Jorgenson-Fraumeni lifetime income-based approach  Calculate human capital stock for each individual as the estimated present value of expected future lifetime earnings Backward recursive estimation beginning with the oldest covered age Divide life cycle into five stages Retirement, Work-only, Work-school, School-only, Pre-school Modifications  Incorporate the Mincer model (National level)  Expand Mincer model to include macro-variables (Provincial level)  Derive total human capital stock separated by urban and rural in estimation  Adjustment for cross-province comparison with a living cost adjustment index 7 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

8. Augmented Mincer model Lack of data in China  use the Mincer model to estimate earnings Extended model for earnings in provinces  ln(inc)= β 0 + β 1 · ln(Avwage)+ β 2 · Sch+ β 3 · Sch · Avgdp+ β 4 · Sch · Ratio+ β 5 · Exp+ β 6 · Exp 2 +u ln(inc): the logarithm of earnings Sch: years of schooling Exp: years of work experience Avwage: average wage of a province Avgdp: provincial GDP per capita Ratio: provincial primary industry employment proportion of the total labor force u: random error 8 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

9. Augmented Mincer model Extended model  Avwage reflects the income gap among provinces Reflect provincial differences in earnings of those with no schooling and no labor-market experience  Avgdp and Ratio capture the provincial economic development stage and labor market structure Return to schooling is affected by the development stage and labor market structure (Li 2003, Zhang et al., 2005, and Yang, 2005) 9 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

10. Data Imputing population by cohort  Population data into 4-dimensions National Censuses (1982, 1990, 2000 and 2010) 1% sample of national population survey (1987, 1995 and 2005) Provincial Statistical Yearbooks (1982-2010)  Age distribution & Enrollment rates The China Health and Nutrition Survey (CHNS 1989, 1991, 1993, 1997 and 2000) The Chinese Household Income Project (CHIP 1995) The China Education Statistical Yearbook (2003-2010) 10 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

11. Data Estimating Mincer parameters Micro: Annual Urban Household Survey (UHS 1986-1997) China Health and Nutrition Survey (CHNS 1989, 1991, 1993, 1997, 2000, 2004, 2006 and 2009) Chinese Household Income Project (CHIP 1988, 1995, 1999, 2002 and 2007) Chinese Family Panel Studies (CFPS 2009) China Household Finance Survey (CHFS 2010) Macro: provincial statistical yearbooks (1982-2010) Growth rate & Employment rate Provincial statistical yearbooks (1982-2010) Discount rate 4.58% --used by Jorgenson and Fraumeni (1992a) and the OECD consortium (OECD 2010) 11 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

12. Results--Human Capital panel data Provide provincial human capital panel data 22 provinces/cities Guangdong, Jiangsu, Shandong, Henan, Hubei, Hunan, Anhui, Shanghai, Liaoning, Beijing, Guizhou, Gansu, Tianjin, Heilongjiang, Zhejiang, Guangxi, Shaanxi, Hainan, Jiangxi, Jilin, Chongqing, Sichuan 1985-2010  cover most of the reform era Total human capital(HC), Per capita HC, Labor force human capital(LFHC), Average LFHC Urban/rural, Education, Age, Gender 12 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

13. Total human capital(HC)  Human capital reserve population aged 0-15 (have not entered the labor market) full-time students aged 16+ (not in the labor force)  Human capital in use non-retired population aged 16+ and in the labor force  The average annual growth rate  lower than the growth rate of the Chinese economy  much faster in the latter period Similar change happens at urban/rural, education, age, gender 13 1985-20101985-19941995-2010 6.4%1.2%9.3% 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

14. Table 1 Descriptive Statistics for Human Capital 14 Sample Mean Variable 1985199520052010 Total human capital (Billion RMB) 1,6021,7224,7238,177 Of: Urban 6267653,1275,954 Rural 1,0231,0031,6732,328 Male 9871,0853,0405,354 Female 6156381,6832,822 Age 0-15 (human capital reserve) 8608762,1603,273 Age 16-59 (labor force human capital including students) 7428462,5634,903 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

15. Total human capital(HC)  Urban-rural Urban increase by 8.5 times; rural 1.3 times from 1985 to 2010 Urban/rural o 60-76% in 1985-1995  2.6 times in 2010  Fast urbanization in China  Increasing educational attainment gap  Gender Annual growth: male 6.6% ; female 6.1% Male/total: 61.6% in 1985  65.5% in 2010  Rising gender ratio of male for China’s one-child policy  Rising gender inequality in educational attainment 15 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

16. Total human capital(HC) Age (Figure 1)Figure 1 Human capital reserve (aged 0-15) : Its ratio in total: 54% in 1985  40% in 2010 Its population share in total: 39% in 1985  23% in 2010 Labor force age human capital(aged 16-59, including students): Its ratio in total: 46% in 1985  60% in 2010 Its population share in total: 61% in 1985  77% in 2010 16 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

17. Figure 1 Human Capital for Different Cohorts-Provincial Average 17 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

18. Total human capital(HC)  Age (Figure 2)Figure 2 Labor force human capital(16-59, excluding students) o The share in total declined since 2000, increase starts at 2005 o Full-time students(aged 16-59) in school increase Its share in labor force: grows from 2.9% in 1985 to 6.9% in 2010 Due to expanded education opportunities since 1999 18 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

19. Figure 2 Population & Human Capital Share-Provincial Average 19 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

20. Labor force human capital(LFHC) Trend: Average annual growth in 1985-2010 LFHC grows faster than total HC (fewer young people) 20 %HCLFHCLabor force Total6.46.81.6 Urban8.89.24.3 Rural3.44.30.0 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

21. Labor force human capital(LFHC) Education(Figure 4)Figure 4 Human capital share in education: Illiterate and primary: declined rapidly Junior school remains the largest, and started to decline since 2006 Senior: flat College or above The highest increase (close to 20% annual growth) Increased from 1.7% in 1985 to 26.3% in 2010  much higher than its population share, 12.3% in 2010 o A rising return to college education documented by Zhang et al. (2005) 21 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

22. Figure 4 Education Share in Labor Force Human Capital (LFHC) 22 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

23. Per capita human capital (PCHC)  Measure of the intensity of human capital  Compare the annual average growth rates Since 1995 they grew at a similar annual growth rate Average annual growth rates of population 1.2% in 1985-1994; 0.6% in 1995-2010  much slower than the growth of HC  HC growth is not driven solely by population growth 23 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

24. Table 2 Descriptive Statistics for Per Capita Human Capital 24 Sample Mean Variable 1985199520052010 Per capita human capital (Thousand RMB) 4946121202 Of: Urban 7365165267 Rural 403677116 Male 5855148247 Female 403690150 Age 0-15 (human capital reserve) 6971221382 Age 0 (Average lifelong income for new-born) 7678247407 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

25. Per capita human capital (PCHC) (Table 2)Table 2  Urban/rural Gap enlarged Rural/Urban: 54% in 1985  43% in 2010  Education (Figure 3)Figure 3 Average years of schooling 5.5 years in 1985  8.8 years in 2010  Gender Female/male: 69% in 1985  61% in 2010  Age 0-15 Average annual growth PCHC: 6.6%; Population: -1.5% 25 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

26. Figure 3 Average Years of Schooling (Avsch) and Per Capita Human Capital (PCHC) 26 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

27. Top 5 Provinces for Human Capital in 2010 27 Total human capital (Billion RMB) Total population 1 Guangdong21,974 Guangdong 2 Jiangsu21,029 Henan 3 Shandong18,386 Shandong 4 Zhejiang15,335 Sichuan 5 Henan13,888 Jiangsu Per capita human capital (Thousand RMB) Per capita GDP 1 Shanghai378 Shanghai 2 Beijing345 Beijing 3 Zhejiang337 Tianjin 4 332 Liaoning 5 Jiangsu329 Heilongjiang 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

28. Average labor force human capital(ALFHC)  Urban/rural: Urban: RMB 167 thousand; Rural: RMB 90 thousand in 2010 Average annual growth Since 1995, urban ALFHC has grown much faster than rural Education gap between urban and rural areas Higher labor quality and thus higher productivity in urban areas, if the age structure in urban and rural areas were identical  urban/rural gap will continue to rise. 28 %1985-20101985-19941995-2010 Urban4.98.2 Rural4.3-0.26.8 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

29. Top 5 Provinces for Labor Force Human Capital in 2010 29 Labor force human capital (Billion RMB) 1 Guangdong12,220 2 Jiangsu8,552 3 Zhejiang7,122 4 Shandong6,498 5 Henan5,796 Average labor force human capital (Thousand RMB) 1 Shanghai263 2 Beijing255 3 Tianjin222 4 Zhejiang206 5 Jiangsu184 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

30. Human capital as a measure of social development--beyond GDP measures “…beyond Gross Domestic Product…”  measure of economic and social progress--Stiglitz Commission report Expected average lifetime income for newborns rises rapidly It Annual growth rate of 6.7%  faster than PCHC (5.6%) Provincial difference: 30 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

31. Figure 5 Ratios of Labor Force Human Capital (LFHC), Physical Capital (PC), and GDP 31 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

32. Human capital and physical capital LFHC/physical capital Decreases rapidly across time 12 times in 1985  5 times in 2010 Possible reason: High physical capital investment in China Increased at an average annual growth of 18.9% during 1992- 1997 32 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

33. Human capital and GDP GDP/LFHC  Measure of labor use efficiency Provincial ratio is between 6-11% on average Shows a slow and stable growth  Compared with GDP/physical capital: In the range of 49-66% Decline since 1995   Human capital rises faster than physical capital in efficiency 33 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

34. Illustration of Data Applications 34 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

35. Table 4 Production function estimation 35 Var.Definition Pooled OLSFE Labor Human capital Labor Human capital lnKlog(physical capital)0.647***0.449***0.603***0.533*** (0.007)(0.012)(0.015)(0.037) lnLlog(labor)0.366*** 0.185 (0.021) (0.183) lnH log(labor force human capital) 0.551*** 0.221*** (0.023) (0.063) Cons -5.376***-13.224***-2.058-4.623*** (0.348)(0.583)(3.056)(1.532) Obs. 546 R2R2 0.9540.9660.9810.986 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

36. Illustration of Data Applications Pooled OLS (Table 4)Table 4 LFHC has much higher output elasticity than labor When human capital is included Smaller elasticity of physical capital, even smaller than that for human capital Constant returns to scale Fixed Effects LFHC still has higher elasticity than that of labor Elasticity of labor and LHFC become much smaller than OLS Decreasing returns to scale 36 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

37. Illustration of Data Application 37 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

38. Table 5 Sources of China’s Economic Growth using Solow Growth Accounting 38 1986-2010 Growth rate (% per year) Output10.29 Physical capital16.48 Labor1.64 TFP (with labor)3.76 Labor force human capital 7.03 TFP (with labor force human capital) 0.14 Contribution to GDP growth (%) Physical capital53.32 Labor10.69 TFP (with labor)35.99 Labor force human capital 45.87 TFP (with labor force human capital) 0.81 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

39. Illustration of Data Application Contributions to economic growth (Table 5)Table 5 With traditional labor input Physical capital accounts for 53.3% of growth  Economic growth in China has been mainly driven by physical capital Labor input: 10.7% TFP: 36% With human capital input LFHC: 45.9% TFP: 0.8% Consistent with studies that use two-step procedure to estimate how human capital affect TFP growth 39 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

40. Summary The data provide very rich information in studying China’s human capital A comprehensive picture of China’s human capital distribution and dynamics Demonstrations of applications of the new data Estimating a production function Conducting the growth decomposition exercise using the data Compared the results with the traditional estimation based on labor inputs The new panel data on China’s provincial human capital are quite reliable; and should be a valuable new resource for related studies and policy analysis 40 中国人力资本与劳动经济研究中心 China Center for Human Capital and Labor Market Research

41. Questions? 41