Transcript Slide 1

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.
Population G
pcHK g rowth
rowth
1986 -94
1995 -2007
74%
23%
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 p roduction
through
Secondary
School.
Hig h School
Grads
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
4.1 5
National
0.4966
40.86
0.3323
5.17
(% populatio
– 2003).
n
Indirect
contribution to
production
through Highe
Education.
College Gr a ds
r
(% populatio n
– 2003).
(*regional calculations are arithmetic means of the constituent provinces.
“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.