Human Capital in China

Presented by Chantelle Blachut & Emiko Nishii

Outline.

Measuring Human Capital (HK) in China

What do these results really tell us?

Why is HK underinvested in, in China? (policy issues)

Can further HK investment help to reduce the income gap in China? (yes/No)

Policy Implications.

“Human Capital in China” (2010). Measuring human capital in China - how is this approach superior?

1. Contains larger time periods (1985-2007)

2. Constructs separate human capital measures by gender, location, and age

3. Takes ‘life-time earnings’ into consideration (the JF approach).

“Human Capital in China” (2010): Methodology.

Step 1: estimating earnings for all individuals in the population

Uses the fitted parameters estimated by the annual Urban Household Survey (UHS) for 1986-1997 to generate the parameters for ‘urban’ for 1985-2007.

Uses the CHNS to compute the urban-rural ratio for 1985-2007

Applies the above ratio to the imputed parameters for the urban population to find the parameters for ‘rural’.

“Human Capital in China” (2010): Methodology.

Step 2: estimating the lifetime expected earnings for all individuals in the population

The life cycle is divided into 5 stages - retired, no school no work (M>60, F>55)

- work, but no school (25<M<59, 25<F<54) - school & work (16<M/F<24) - school but no work (6<M/F<15) - no school, no work (0<M/F<5)

“Human Capital in China” (2010): Methodology Cont’d.

Step 3: To implement the JF method, the authors need to have data for annual population by age, sex and educational attainment (rural and urban).

Problem: data only exists for some years - for all others we need to ‘build’ it (by using a perpetual inventory method) in order to categorise population by age, sex, educational attainment and location for any given year.

“Human Capital in China” (2010): Methodology Cont’d.

Step 4: estimating lifetime earnings for all by taking into account the real income growth rate & discount rate for Urban/Rural.

Assumption: MPL=real wage(i.e. GDP of secondary ind./# of labor=urban prod. Growth)

The discount rate=4.58%

“Human Capital in China” (2010): Methodology Cont’d.

Total HK Stock, GDP and PK Stock: Ratio of est. HK: nom. GDP declined until 05-07. However total HK stock is > total PK stock.

HK:PK appears to be continuously declining.

Not clear if this indicates govt has overly weighted investment in PK.

THK grown at 6.66% p.a. BUT GDP grew at 9.33%.

* HK growth rate still much higher than other countries.

“Human Capital in China” (2010): Methodology Cont’d.

Per capita HK: This increase in total HK could be driven solely by

population growth, or even demographic changes (eg. size of retirement group). Thus we also need to examine HK per capita (= total HK : non-retired portion of population).

Per capita HK Growth rates p.a. 1985-94 1995-2007 Men 5% 7.0% Women 2.6% 7.8% Rural 2.75% 7.05% Urban 4.57% 5.49%

“Human Capital in China” (2010): Methodology Cont’d.

One more Step: to devise Divisia Indices

that look inside HK and determine what actually drives growth rates.

The growth rate of aggregate HK stock is calculated as a weighted sum of the growth rates of the number of individuals across different educational, age, gender and location categories.

Role of 2 determinants of the growth rate of HK p.a. 1986-94 1995-2007 Population Growth 74% 23% pcHK growth 24% 77%

“Human Capital in China” - what you need to remember:

1985 - 07: Total HK stock increased over 3 times (6.66% p.a.).

The total HK in urban areas increased faster than in rural (8.73% vs 4.44%) - thus, the gap continues to widen.

Per capita HK increased rapidly and from 1995 it has grown at the same rate as total HK ( = education & not population alone).

“Human Capital in China” - what you need to remember:

The gender gap in total HK has been widening on the national level BUT diminishing in per capita terms.

Education has a greater impact on HK accumulation than gender has.

Did China under-invest in HK?

Physical vs. Human Capital in China

According to Heckman (2005), when compared with world standards, the % of GDP devoted to HK is very low (e.g. in 2002, 3.3%).

Restriction on the flow of resources & investing in education at different rates in different regions

>> return on HK investment < return on PK investment.

Inequality in HK & Hukou Policy

Hukou policy charges children of interregional immigrants additional fees for schooling, that can amount to as much as 10% of total family income, just for the right to attend school.

Schooling is mostly funded at the local level >>rich provinces produce more HK per capita than poor provinces.

How can this be a problem in the future?

Lucasian growth: HK is used entirely to apply technologies imported from the tech. frontier in the productive process.

As a country develops further (approaches the technological frontier), more and more HK must be used to innovate new technologies (Romerian growth: R&D).

>> for the transition, large HK investment is needed>> existing inequality might be a big obstacle….

Inequality in Literacy Rate.

“Can Educational Expansion Improve Income Inequality in China?” Ning (2010).

With the presence of the Hukou policy, can further HK investment in education reduce urban-rural inequality? - No!

Data: the China Health and Nutrition Survey (CHNS) data collected in 1997 and 2006.

Aim: By using a quantile regression, investigates the contribution of education to the convergence of regional income.

“Can Educational Expansion Improve Income Inequality in China?” Ning (2010).

Nine provinces are chosen in the study (representative of a typical province).

Only takes the individuals with college and university degrees as an example (huge gap in income: the avg. annual income in 2005=21,030.54 yuan. The max=216,000 yuan, the min=1200 yuan).

“Can Educational Expansion Improve Income Inequality in China?” Ning (2010).

With the same level of education, income inequality is driven by what?

where unit captures the type of work unit (e.g. govt., state service, state-owned enterprises, small collective enterprise=1, otherwise 0), unitscale is size of work unit, hukou is household registration (1=urban, 0=rural).

“Can Educational Expansion Improve Income Inequality in China?” Ning (2010).

Having a high degree is not sufficient to guarantee a high income. Only entering a monopoly sector, through a social network can ensure a high and stable income.

Now, estimates a quantile regression model to analyze the returns to the education rate at different income distribution points.

The dependent variable=yearly income.

Now ‘years of education’ is included as an independent variable.

“Can Educational Expansion Improve Income Inequality in China?” Ning (2010).

Results:

the return rates at 0.1, 0.25, 0.5, 0.75 and 0.9 point are 7.22%, 6.8%, 6.74%, 5.58%, and 5.24%.

The return rate shows a tendency of decreasing with income.

>> Further educational expansion helps little in narrowing the income gap with the presence of the Hukou policy….

Can we lower regional inequality by investing in Human Capital?

…YES! How?

”Build a prosperous and cultured, new socialist countryside” (1997).

“Human Capital, Economic Growth & Regional Inequality in China”, (Li, et. al, 2007).

Aim: to examine the impact of HK, infrastructural capital and foreign investment on economic growth in China.

Data: China Statistical Yearbook Census (1983, 1993, 2001) & Annual Population change Survey (State Statistical Bureau, 1996, 1998, 1999, 2003, 2003).

Section 5: Hypothetically examines the impact of one-time increases in HK (and infrastructure) investments on regional inequality.

“Human Capital, Economic Growth & Regional Inequality in China” (cont’d).

1: Estimate national average rate of return p.a. of additional schooling to investment in higher education:

Internal rates of return to investment in education. Direct

Contribution to production through Secondary School.

High School Grads (% population – 2003).

Indirect contribution to production through Higher Education.

College Grads (% population – 2003).

Coastal 0.4932 42.88 0.3046 6.20 North-east 0.5180 53.32 0.3087 6.58 Far-West 0.4855 38.95 0.2863 6.00 Interior 0.4975 37.58 0.3755 4.15 National 0.4966 40.86 0.3323 5.17

(*regional calculations are arithmetic means of the constituent provinces. Interior = almost 52% of total population).

“Human Capital, Economic Growth & Regional Inequality in China” (cont’d).

2. Interior region (black line) has very low pc GDP relative to the coast and North-East (blue) (<1/2).

Real p.c. GDP ratios.

“Human Capital, Economic Growth & Regional Inequality in China” (cont’d).

3.

“Human Capital, Economic Growth & Regional Inequality in China”.

In sum: Investing in HK and higher education in China, generates comparable, or higher returns, in the less developed areas relative to the more developed coastal region.

Therefore - a policy such as this, aimed at fostering growth in regional educational attainment levels, should be effective in achieving the goals of economic efficiency and humanitarian equality.

Policy Implication.

In understanding the importance of HK for growth, reducing regional inequality to give the right incentives to acquire skills, what should happen first?

further educational expansion

abolish Hukou policy & opening the labour market

Bibliography

Heckman JJ (2005), ‘China’s Human Capital Investment’, China Economic Review, 16, pp. 50 - 70.

Li H, Liang, Y, Fraumeni, BM, Liu Z, Wang X (2010), ‘Human Capital in China’, 31st Conference of the International Ass. for Research in Income and Wealth, St Gallen, Switzerland, August 26.

Li H, Fleisher, B, Qiang Zhao, M (2007) ‘Human Capital, Economic Growth, and Regional Inequality in China’, William Davidson Institute Working Paper, No. 857, Jan.

Heckman, J (2003) ‘China’s Investment in Human Capital’. Ning, G (2010) ‘Can Educational Expansion Improve

Income Inequality in China? Evidences from the CHNS 1997 and 2006 Data’.

Another interesting literature……

If you are interested in reading a paper assessing the HK investment in China for the past decades (if China underinvested in HK? Or China actually is moving to the

right direction in terms of HK investment), the following meta-study might be helpful….

Liu, E (2005).’A META-ANALYSIS OF THE ESTIMATES OF RETURNS TO SCHOOLING IN CHINA’. University of Houston.