1
MIT Sloan
School of Management
WHAT IS “CHINA MODEL”?
Yasheng Huang
Professor
MIT Sloan School of Management
Founder
China Lab and India Lab
AGENDA
2

What is China Model?
–
–
–

Major challenges
–
–
–
–
Beijing Consensus: State capitalism
Gradualism: Gradual reforms but acceleration over time
Reversal story: Substantial reforms but followed by reversals
State capitalism and consumption decline
Rebalancing Chinese economy
Personal income, not GDP growth
Prospects
Can urbanization contribute to rebalancing?
— Effect of rebalancing on energy demand from China
–
3
IS CHINA MIRACLE DUE TO STATE
CAPITALISM?

Microeconomic studies contradict this claim
 Case
study: Zhejiang
 Wenzhou
model: Capitalism and financial liberalization
 Middle of the country in per capita income in late 1970s
 Now the richest (outside Beijing, Shanghai and Tianjin)
 Higher asset income
 Higher personal income/GDP ratio
 Business innovations: Alibaba.com, Wanxiang, Wahaha
 TFP
studies:
 TFP
growth of private sector outpaced that of state sector
BUT STRONG FEATURES OF STATE
CAPITALISM
4

No democracy
Top-down political controls

Tightening rather than loosening
– 1980s vis-à-vis 1990s
–

Funding bias:
90% of the stimulus program went to SOEs
– 80% of bank loans to SOEs with 20% of
employment
–

National champions are overwhelmingly stateowned
A CHINA-INDIA COMPARISON

Boston Consulting Group: “The 2009 100 BCG
New Global Challengers”
–

Research on emerging firms based in developing
economies
Of 100 firms selected:
China: 38
– India: 19
–
5
THE CHINA-INDIA DIVIDE
The biggest difference between China
and India: India’s growth is far more
driven by private sector.
6
7
STATE CAPITALISM IS NOT A
CONSTANT

Relatively liberal phase: 1980s
 Fast
personal income and consumption growth
 No mercantilism: Fast GDP growth with an overvalued
exchange rate and trade deficit in several years
 Some initial improvement in income distribution


Reversal: 1990s
Intensification and entrenchment of state capitalism:
Since late 1990s
THE TRUE CHINA MIRACLE
8

How did China miracle begin?
 Getting
the political economy right
 Financial liberalization
 Reversal of policies in the 1990s
POLITICAL ECONOMY PUZZLE

Vibrant rural entrepreneurship but why did rural
entrepreneurs trust the Chinese state?
 Many
landlords were executed in the 1950s
 Cultural Revolution (1966-1976): “Nasty, brutish and
long”
 Capricious politics: The Chinese prisoner’s dilemma

Policy credibility hinges on constraints on rulers
 Academic
literature (Weingast, North, Acemoglu and
Johnson, and many others)
 Is China different?
CHINESE POLITICS IN THE 1980S

Statics vis-à-vis dynamics in Chinese politics:
 Statics:
China is/was not a democracy
 Dynamics: A substantial move away from the status quo
ante of the Cultural Revolution

Entrepreneurs’ incentive depends
 Not
on a convergence with the best-practice political
institutions
 But on a dynamic movement toward convergence with
these institutions
THE DENG XIAOPING EFFECT

Final puzzle: How did rural entrepreneurs know that
politics had changed?
 Tens,
even hundreds of millions of them
 Uncoordinated actions
 Lack of information and transparency

The Deng Xiaoping effect: Observability of
policy/political changes
 Deng
was observably different from Mao.
THE DENG XIAOPING EFFECT

Deng Xiaoping:
 Purged
 Deaf
three times by Mao
ear to Mao
 His
son was crippled by Mao’s red guards
 These Deng attributes: Widely known and cognitively
easy to interpret

Implications:
 The
signaling was unambiguous
 More policy credibility than implied by political changes
alone
CHINA WAS NOT LIBERAL; IT WAS
DIRECTIONALLY LIBERAL

Directional liberalism of the 1980s
 (All
discontinued after 1989)
 Substantial media freedom in the early 1980s (by
Chinese standard)
 Village elections introduced
 Recruiting capitalists into the Party (1981)
 Returning confiscated properties to former capitalists
(1979)

Timing matters: The political effects were exogenous
to, not endogenous of, growth.
15
FINANCIAL LIBERALIZATION AND
REVERSAL
FINANCIAL REVERSAL
DEFINITIONS AND MEASUREMENTS
16
Rajan and Zingales (2003)
 Financial
development: the ease with which any
entrepreneur or company with a sound project can
obtain finance, and the confidence with which
investors anticipate an adequate return;
 Motive of reversal: an interest group theory where
incumbents oppose financial development to deter
competition;
 Measurements: size of financial system -- Bank
deposit/GDP, equity market capitalization, # of
listed firms/population, equity issuance/fixed
capital formation.
17
KEY RESULTS (QIAN AND HUANG
2011)

We document a financial reversal that occurred during the early 1990s in
rural China.




There were liberal financial policies in the 1980s to encourage market
operation and competition, but tight government controls in the 1990s.
As a result, there was a sharp curtailment of credit flows to the rural
population and reduced financial resources to fund the nonfarm business
operations run by Chinese rural entrepreneurs.
Little support for the view that emphasizes endogenous determinants such
as formal/informal loan substitution, labor migration etc
Reversal was due to deliberate policy.
MIT, March 9 2011
18
EVIDENCE FROM BANK
DOCUMENTS
A1: Documentary evidence of financial liberalization during 1980s and reversal during 1990s in rural China.
Features of the financial system
1980s
1990s
Credit rationing of private
No
Yes
enterprises
Interest rate regulation
More flexibility in rate
Controlled interested rate
determination
Collateral, guarantee
Qualification based
Mandated
Loan decisions
Decentralized
Centralized
Loan officers
Local and elected by members
Appointed by top managers
Government intervention
Give control rights back to
Put under supervision of local
shareholders
government again
Entry barrier
Deregulated, competition from
Competition is repressed. Informal
nongovernmental capital is
financing institutions were
encouraged
designated illegal and cracked
down upon
Sources: People’s Bank of China (1999, 2001); Agricultural Bank of China (1984, 1985, 1986, 1988a, 1988b,1992a,
1992b,1994, 1995, 1998); State Council (1994, 1996, 1998); China Finance Association (1986, 1997, 2000 ); Chen
Muhua (1987); Dai Xianglong (1997); Shi Jiliang (1999); Rural Work Leadership Team of Fujian Communist Party
Committee (1997); Editorial Committee of Wenzhou Financial History (1995).
MIT, March 9 2011
FINANCIAL LIBERALIZATION IN THE
1980S
19

Han Lei, President of the ABC, July 20, 1984
 “Rural
areas need state-owned banks and credit
cooperatives for finance but at the same time, under
bank supervision, we need to allow the existence of
private (私人) free lending and borrowing.”

Chen Muhua, Governor of PBoC (1987):
 “Non-governmental
(民间) capital mobilization and
non-governmental rural cooperatives have emerged.
The various methods of financial mobilization have
made a positive contribution to local economic
development.”
20
SUBSTANTIAL CREDIT ACCESS IN THE
1980S

Surveys and research in the 1980s:
 Average
of six surveys of private firms (1987): 41%
received banks loans (Highest=66% in Shaanxi)
 World Bank TVE study (1990): Private firms in Tianjin
financing 39-44% of investments with bank loans.
 William Byrd: “Banking institutions already see wellestablished private enterprises as solid borrowers.”
THE GREAT REVERSAL
21
• Chen Muhua (1986):
• Under the banking regulations, individuals are not allowed to engage
in financial operations. The emergence of private (私人) credit shows
that our financial work falls short of what is needed. This requires
that our credit cooperatives and agricultural banks improve their
services.
 State Council (1998):
 Those funds, mutual assistance associations, savings associations,
capital service departments, share capital service departments, fund
clearing centers, and investment companies established prior to this
order and operating above the state law should be restructured with a
deadline according to the regulations of the State Council. Those
entities that operate after the deadline and continue to engage in
illegal financing should be stamped out according to this order. Those
with serious violations of a criminal nature should be held
accountable for their legal responsibilities.
THE SURVEY
22



A fixed-site rural household survey (FSRHS), conducted by China’s Ministry of
Agriculture;
Implemented annually from 1986 to 1991; once in 1993, and again annually from
1995 to 2002.
Nationwide, 300 to 400 villages, stratified by socioeconomic development level
and geography, were sampled each year, 20 to 120 households from each village
were selected randomly.
MIT, March 9 2011
THE SAMPLE
23

Limiting to the six province data may in fact operate against our
hypotheses – i.e., underestimate the degree of the 1990s’ financial reversal.




Two out of the six are among the most developed provinces
Sample average income level is higher than national average, so is the access to
bank loans, particularly so in 1990s. (National average values for certain
variables are published by the Central Committee, Policy Research Office and
the Ministry of Agriculture 2000).
Using the over 100 reconciliation equations to check the quality/consistency
of the survey answers.
Our final sample includes 34,571 household* year for the 1986–1991
survey and 32,460 for the 1995–2002 surveys.
MIT, March 9 2011
ACCESS TO FINANCE
24
Figure 1A: % of households receiving formal or informal loans in the two periods.
Access to Finance
0.35
0.3
0.25
0.2
1986-1991 Survey
0.15
1995-2002 Survey
0.1
0.05
0
% of households receiving % of households receiving % of households receiving
Bank or RCC loans
informal loans
bank, RCC, or informal
Loans
MIT, March 9 2011
Baseline result
-- a sharp drop in households’ access to bank loan in the 90s.
25
Table 3: Baseline results for reduction of credit access as evidence of financial reversal
(1)
(2)
Y: Dummy that equals
one if loans are
obtained from banks or
RCCs
Reversal measure
Dummy (1995–2002 period)
(3)
(4)
Y: log (value of the
loan obtained from
banks or RCCs)
(5)
(6)
Y: log (deflated value
of the loan obtained
from banks or RCCs
-1.96**
[0.45]
-3.21**
[0.86]
-9.30**
[1.62]
-13.43**
[3.40]
-1.75**
[0.09]
-2.30**
[0.19]
0.46**
[0.02]
0.27**
[0.04]
0.52**
[0.03]
0.23**
[0.05]
2.20**
[0.12]
1.22**
[0.21]
2.76**
[0.14]
1.06**
[0.24]
0.15**
[0.01]
0.10**
[0.02]
0.32**
[0.01]
0.14**
[0.02]
0.12**
[0.01]
0.12**
[0.01]
0.66**
[0.03]
0.62**
[0.04]
0.09**
[0.00]
0.10**
[0.00]
-0.42** -0.45**
-1.78**
[0.02]
[0.03]
[0.11]
Log(remittance received)
-0.02
-0.02
-0.1
[0.01]
[0.01]
[0.05]
Education
0.15**
0.11**
0.79**
[0.02]
[0.02]
[0.09]
Control variables structural changes in the second sample period;
Fixed effects: Year, Province, Subsidized family Production category
-1.90**
[0.14]
-0.09
[0.06]
0.55**
[0.11]
-0.10**
[0.01]
-0.01**
[0.00]
0.08**
[0.01]
-0.18**
[0.01]
-0.01
[0.01]
0.06**
[0.01]
Observations
Pseudo R2
66,579
0.08
66,579
66,579
MIT,
9
0.06 March
0.06
Economic variables
Log(cultivated land)
Log(number of working
household members)
Investment needs
Log(fixed assets investment)
Internal and external funding capacity
Log(net household income)
66,579
0.15
66,579
0.15
66,579
0.08
2011
Informal loan and household financial assets
26
--- Is the decrease of formal loan due to substitution of informal loan or
households’ increased financial strength?
Table 5: Formal, informal loan and financial strength of the households
(1)
(2)
(3)
Access to formal credit
(banks and RCCs)
Access
Log
Log
dummy
(amount)
(deflated
amount)
Dummy (1995–2002 period)
-2.04**
-8.26**
-1.41**
[0.36]
[1.75]
[0.11]
Log(amount of
0.18**
0.89**
0.14**
informal loan)
[0.01]
[0.03]
[0.00]
Log(financial assets)
-0.05**
-0.25**
-0.02**
[0.01]
[0.05]
[0.01]
Dummy (1995–2002 period) *
0.03**
0.14**
0.039**
Log(informal loan amount)
[0.01]
[0.05]
[0.01]
Dummy (1995–2002 period) *
-0.01
-0.06
0.01*
Log(financial assets)
[0.01]
[0.07]
[0.01]
Other controls (economic, investment, funding capacity)
Structural changes in the second sample period
Fixed effects: Year, Province, Subsidized family Production category
Observations
66,516
66,516
66,516
0.20
0.11
0.07
(4)
(5)
Access to informal credit
Access
dummy
Log
(amount)
(6)
-0.85**
[0.24]
-3.02**
[1.10]
Log
(deflated
amount)
-1.76**
[0.17]
-0.25**
[0.01]
-1.24**
[0.04]
-0.28**
[0.01]
0.05**
[0.01]
0.18**
[0.05]
0.11**
[0.01]
66,516
0.12
66,516
0.21
66,516
0.15
MIT, March 9 2011
27
Total loan balance
-- Does the loan decrease because of a high amount of
cumulated remaining balance?
Table 4: Evidence of reversal in the total loan balance
(1)
(2)
Remaining balance
on formal loans
Log
Log (deflated
(amount)
amount)
Reversal measure
Dummy (1995–2002 period)
Informal credits and internal financial strength
Log(amount of
informal loan)
Log(financial assets)
-10.76**
[1.82]
0.60**
[0.03]
-0.69**
[0.05]
Dummy (1995–2002 period) *
0.33**
Log(informal loan amount)
[0.05]
Dummy (1995–2002 period) *
0.20**
Log(financial assets)
[0.07]
Other controls (economic, investment, funding capacity)
Structural changes in the second sample period
Fixed effects: Year, Province, Subsidized family Production category
Observations
66516
2
Pseudo R
0.11
(3)
(4)
Remaining balance
on total loans
Log
Log (deflated
( amount)
amount)
-9.30**
[0.72]
-1.95**
[0.12]
-4.07**
[0.16]
1.19**
[0.01]
-0.87**
[0.02]
0.56**
[0.02]
0.42**
[0.03]
0.10**
[0.00]
-0.11**
[0.01]
-0.02**
[0.01]
0.10**
[0.01]
0.63**
[0.00]
-0.36**
[0.01]
0.16**
[0.01]
0.28**
[0.01]
66516
0.07
66516
0.14
66516
0.18
MIT, March 9 2011
Interest payment
-- was the cost of loans higher in 90s than in 80s?
28
Table 6: Robustness check for interest payment
Mean of interest
Observation # payment rate
Difference
t-test of
difference
0.22%
-0.60%
-0.65%
-0.77%
0.26
-1.38
-0.93
-2.23
1st period
Bank and RCC loans only
Informal loans only
Both types of loans
All observations
2,281
5,967
2,288
10,536
5.43%
1.63%
2.43%
2.63%
643
2,899
503
4,045
5.66%
1.03%
1.77%
1.86%
2nd period
Bank and RCC loans only
Informal loans only
Both types of loans
All observations
MIT, March 9 2011
Is the reversal due to bad loan performance in the in
the 1980s?
29
Historical bank performance data


We hand collect historical data on bank lending activities and loan
performance (the Agricultural Bank of China’s Statistical Yearbook 1979–
2008 and the China Finance Associations’ Almanac of China’s Finance and
Banking 1985–2004).
Balance sheet information, annual transaction flows at the province level,
including new loans, pay back rate, and new loans classified by borrower
type, etc for both the Agricultural Bank of China’s (ABC) and the Rural
Credit Cooperatives (RCCs).
MIT, March 9 2011
Bank activities
30
Bank performance and growth in lending activities during the 1980s and 1990s
Panel A: Payback rate of loans
Variable (rate in %)
Loan payback rate in RCCs
Loan payback rate in ABC
TVE loans/total loans from ABC
Agriculture loans/total loans from ABC
1986–1991
81.65
91.71
0.87%
1.20%
Panel B: The growth rate of various type of loans, deposits, and organizations
Variable (average growth rate in %)
1986–1991
RCC total loans
33.52
RCC new loans
474.03
RCC total deposits
30.24
RCC new deposits
85.87
ABC total loans
12.41
ABC new loans
31.89
ABC new loans to TVE
-260.66
ABC total agriculture loans
20.85
ABC new agriculture loans
47.89
ABC # of institutions
ABC # of employees
1995–2002
84.09
84.58
1.26%
4.13%
t-statistics of difference
-1.46
5.41
-1.53
-4.33
1995–2002
16.23
t-statistics of difference
5.28
18.63
2.89
18.98
6.02
-4.02
-4.85
-19.10
-3.73
21.53
-0.59
3.29
-0.95
4.47
1.64
MIT, March 9 2011
Bank performance
31
Figure 5B: Agricultural Bank of China: Equity net worth
MIT, March 9 2011
-- Reduction of loan follows good performance.
-- Reversal is worse in provinces that had performed better in the
1st period.
32
Table 11: Bank loan and bank performance
Bank performance lag 1 year
Bank performance forward 1 year
Dummy (1995–2002 period)
Better performing provinces 1986-1991
* Dummy (1995–2002 period)
Economic controls
Structural changes in the controls
Various fixed effects
Constant
Observations
Pseudo R2
(3)
(2)
(1)
Y: A dummy that equals
one if loans are accessed from
banks or RCCs
-0.60**
-0.56**
-0.47**
[0.15]
[0.15]
[0.14]
1.74**
1.54**
[0.58]
[0.57]
-2.79**
-2.98**
-3.12**
[0.80]
[0.80]
[0.80]
-0.23**
[0.08]
YES
YES
YES
YES
YES
YES
YES
YES
YES
0.79**
[0.27]
64,199
0.16
-0.52
[0.55]
62,741
0.16
-0.67
[0.56]
62,741
0.16
(5)
(4)
Y: log (value of the
loan obtained from
banks or RCCs)
-2.85**
-2.48**
[0.71]
[0.69]
6.26*
[2.54]
-12.29**
-13.16**
[3.44]
[3.45]
(6)
YES
YES
YES
YES
YES
YES
-3.06**
[0.71]
7.44**
[2.56]
-11.19**
[3.46]
-1.33**
[0.38]
YES
YES
YES
0.07
[1.26]
64,199
0.08
-5.21*
[2.47]
62,741
0.08
-0.67
[0.56]
62,741
0.16
MIT, March 9 2011
33
Patterns consistent with with policy changes:
-- sectoral priority, party/government control, and mandatory
collateral requirements
Table 13: Explaining reversal by policy change indicators: political status, sectoral priority,
and collateral requirement changes
Access to formal credit
(banks and RCCs)
Access
Log
Log
dummy
(amount)
(deflated
amount)
Log(durable goods)
-0.28**
-1.36**
-0.16**
[0.03]
[0.14]
[0.01]
Dummy (1995–2002 period) *
0.16**
0.97**
0.16**
Log(durable goods)
[0.05]
[0.23]
[0.02]
Days worked on nonfarm business
0.17**
0.91**
0.17**
[0.02]
[0.09]
[0.01]
Dummy (1995–2002 period) *
-0.09**
-0.48**
-0.13**
Days worked on nonfarm business
[0.03]
[0.12]
[0.01]
Political status
0.02
0.12
0.02
[0.05]
[0.22]
[0.02]
Dummy (1995–2002 period) *
0.17*
0.74*
0.03
Political status
[0.09]
[0.41]
[0.03]
Dummy (1995-–2002 period)
-1.89**
-9.30**
-1.36**
[0.43]
[2.49]
[0.12]
All other controls; Structural change in the controls; Various fixed effects
Observations
63,017
63,017
63,017
2
Pseudo R
0.21
0.11
0.07
Access to informal credit
Access
dummy
Log
(amount)
Log
(deflated
amount)
-0.02
[0.02]
0.09**
[0.03]
0.07**
[0.02]
0.00
[0.02]
-0.01
[0.03]
0.06
[0.06]
-0.89**
[0.27]
0.07
[0.11]
0.38*
[0.16]
0.39**
[0.09]
-0.01
[0.11]
-0.07
[0.18]
0.37
[0.29]
-3.40**
[1.22]
0.08**
[0.02]
0.02
[0.03]
0.08**
[0.02]
-0.01
[0.02]
-0.02
[0.03]
0.06
[0.05]
-1.88**
[0.18]
63,017
0.12
63,017
0.06
63,017
0.04
MIT, March 9 2011
34
KEY RESULTS (QIAN AND HUANG
2011)



Rather than simply not having launched any financial reforms, China
actually reversed those were initiated;
The financial reversal was related to exogenous policy changes rather
than to endogenous economic or political economy determinants.
The financial reversal in the early 1990s mattered for credit access,
rural entrepreneurship, development of non state-owned financial
institutions, and rural income.
THE BIGGEST CHALLENGE:
CONSUMPTION DECLINE
35
PROBLEMS WITH STATE CAPITALISM
36

Two functions of state capitalism
Able to build infrastructures rapidly
– Resource mobilization to target funding
–

Biggest problem with state capitalism:
Low personal income growth (relative to GDP
growth)
– Huge and growing imbalances: Declining
consumption
–
THE GREAT CONSUMPTION COLLAPSE
China
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Household final consumption expenditure % GDP. From World Bank’s WDI.
37
THE ROOTS OF GLOBAL IMBALANCES:
THE GREAT DIVERGENCE
80.0
70.0
60.0
50.0
China
40.0
United States
30.0
20.0
10.0
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
0.0
Household final consumption expenditure % GDP. From World Bank’s WDI
38
CHINA’S UNUSUAL CONSUMPTION
DECLINE
39
80.0
70.0
60.0
50.0
Brazil
40.0
China
South Africa
30.0
20.0
10.0
Household final consumption expenditure % GDP. From World Bank’s WDI.
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
1982
1981
1980
0.0
IT IS NOT AN EAST ASIAN
PHENOMENON
40
70.0
60.0
50.0
40.0
China
30.0
20.0
10.0
0.0
Household final consumption expenditure % GDP. From World Bank’s WDI.
Japan
Korea, Rep.
CHINA AND INDIA: CONSUMPTION GAP
41
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Household final consumption expenditure % GDP. From World Bank’s WDI.
China
India
42
HAS CHINA RELBANCED?
15% RETAILS GROWTH in 2009 and 18% in
2010
43
NO.
INSTITUTIONAL RETAIL CONSUMPTION
HAS RISEN SHARPLY
44
% of institutional retail sales
30%
25%
20%
15%
10%
5%
20
07
20
06
20
05
20
04
20
03
20
02
20
01
20
00
19
99
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
0%
HOUSEHOLD CONSUMPTION HAS
DECLINED FURTHER IN 2008 AND 2009
45
China
60.0
50.0
40.0
30.0
20.0
10.0
0.0
198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009
Household final consumption expenditure % GDP. From World Bank’s WDI.
46
STABILIZING THE CONSUMPTION
SHARE OF GDP DURING THE
CRISIS PERIOD
47
THE KEY TO REBALANCING IS
PERSONAL INCOME, NOT GDP OR
SAVINGS RATE.
WHY DID CONSUMPTION DECLINE IN
CHINA?
48

Precautionary savings hypothesis:
–
–

High and rising savings rate is the problem
Measures to reduce the savings by 1) product
marketing and distribution and 2) social protection
Cautionary spending hypothesis
–
–
Low income growth, not high savings rate
Policy and institutional reforms to improvement
employment and income growth
NO EVIDENCE ON RISE OF SAVINGS
RATE
49

Rural income and consumption growth:
–
–

Zhou Xiaochuan (07/09, governor of China’s central
bank)
–

1980s and since 2003: Consumption growth matched
income growth
1990s: Income growth exceeded consumption growth but by
a slim margin
No increase in household savings rate in recent years
No support for the pre-cautionary savings hypothesis
CAUTIONARY SPENDING HYPOTHESIS
50

Cautionary spending hypothesis:
–
–

Low personal/household income growth relative
to GDP growth
Low expectations of future income growth
The case of rural migrant workers
–
Low consumption due to both precautionary
savings and cautionary spending
51
GDP AND PERSONAL INCOME
DIVERGENCE
GDP AND HOUSEHOLD INCOME
GROWTH: 1978-2008
52
REAL RURAL CONSUMPTION GROWTH
(1978 PRICES)
53
DATA INCONSISTENCIES
54

National Bureau of Statistics data
Moderate growth in the 1990s but still there was
growth
– Relative decline of income at the lowest income
group but absolute gains
–

Ministry of Agriculture household survey data:
–
No income (nominal) gains from 1995 to 2000 at
the lowest quintile
Ministry of Agriculture data: No income (nominal) gains
from 1995 to 2000 at the lowest quintile
56
RURAL ECONOMY AND
URBANIZATION
WHY RURAL SECTOR MATTERS

Demand side:
–
–
–

Supply side (=Entrepreneurship):
–
–
–

721 million rural residents in 2008
230 million rural migrants (NBS 2009)
There are many “rural cities” in China (contrast with India)
Rural China is more entrepreneurial due to lack of social protection and less
political control
Households=business units in rural China
Households are unambiguously private
Global crisis:
–
–
Huge supply effect of rural migrant workers but almost no consumption effect
Policy discussions to revive rural entrepreneurship and rural finance
57
URBANIZATION AS THE KEY?
58


Most policy makers and economists believe
that urbanization is the key to the rural
development
But China’s urbanization is:
–
–
–
Politically driven due to state ownership of land
Instigating substantial social conflicts due to land
disputes
Accompanied by a sharp consumption decline and
stagnant service sector
A VERY SMALL SERVICE SECTOR
59
60
URBANIZATION AND
PERSONAL INCOME:
SURVEY EVIDENCE
61
IS URBANIZATION A SOLUTION TO
IMBALANCE?

Features of Chinese urbanization
 State
ownership of land
 No recognition of incumbency rights
 Substantial institutional rigidities during fast
urbanization (such as Hukou system)

No evidence that urbanization has boosted
household consumption
URBANIZATION (CHINESE STYLE)
 Agglomeration

effects of market-based urbanization
Reduce transaction costs and lower the provision costs of
public goods.
Raise income and consumption: Middle class
Political urbanization
Geographic expansions
Government pricing of land transactions
62
SPATIAL MEASURE: URBAN AREA (市区)
Size of urban area: KM2
2500
2000
1500
Mean
Median
Standard deviation
1000
500
0
1996
1997
1998
1999
2000
2001
2002
2003
2004
SPATIAL MEASURE: CONSTRUCTED AREA (
城建区)
Completed construction area: KM2
120
100
80
Mean
60
Median
Standard deviation
40
20
0
1996
1997
1998
1999
2000
2001
2002
2003
CONSUMPTION DECLINED SHARPLY
AFTER 2000
China
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Household final consumption expenditure % GDP. From World Bank’s WDI.
65
66
SURVEY EVIDENCE ON RURAL
MIGRANT WORKERS

4 waves of survey data
 2006
 2008
 2009
 2010

Key results:
 One-time
increase from rural to industrial reallocation
of labor
 No or modest subsequent wage increase until 2005
 Wage growth substantially lagged GDP growth
2009 SURVEY ON RURAL MIGRANTS IN
GUANGDONG
 Wage
growth is very recent
 95%
of respondents experienced first on-job wage
increase in 2005
 53%
of the sample migrated before 2000
 Wage increase through job change: 3 times on average
 10%
wage growth between 2005 and 2008
 A small decline in 2009: Survivor bias
 Stagnant
wage growth in the 1990s
 German

survey in Shenzhen (1993)
Real annual wage growth between 1993-2005: 1%
67
GUANGDONG’S GDP PER CAPITA
(DEFLATED BY CPI)
68
Real GDP per capita
40000
35000
30000
25000
20000
Real GDP per capita
15000
10000
5000
0
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
GDP AND WAGE DATA IN
GUANGDONG (SURVEY DATA)
69
40000
35000
30000
25000
Real GDP per capita
20000
Real annual starting wage
15000
10000
5000
0
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008
Rural migrant survey data from Zhongshan University
2009 SURVEY ON RURAL MIGRANTS IN
GUANGDONG
 Consumption:
 High
savings rate:
 40%
(Urban: 20%)
 But 47% with zero deposit balances
 Very
economical on food: 10 yuan per day
 But substantial spending on children education: 1/3
spent on private education on children
 2010
survey
 Average
electricity consumption: 70 kwhs
 Median electricity consumption: 45 kwhs
70
2009 SURVEY ON RURAL MIGRANTS IN
GUANGDONG
 Hukou
system and precautionary savings
 27%
have expectations for a hukou change
 #2
savings motivation: Build house and return to home
village
 Exclusion
of public goods
 Barred
from access to local public schools
 Education of children ranked #1 savings motivation
71
2009 SURVEY ON RURAL MIGRANTS IN
GUANGDONG
 Human
capital trap
 But
almost no expenditure on skill training
 No public investments in private schools for migrant
children
 Substantial achievement gaps
 Public/private school teacher pay: 5:1
 Barred from college entrance examination in
Guangdong
 Forced
to return to and attend inferior high schools in
home provinces
72
REBALANCING CHINESE ECONOMY:
WHAT IS REQUIRED
73


Matching personal income growth with GDP
growth
Reforms, not government spending
–
Land reforms
–
Urban registration reform
–
Social provisions
–
Political reforms
ENERGY INTENSITY OF GDP
74
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
PER CAPITA ENERGY USE: CHINA AND
INDIA
1600
1400
1200
1000
800
China
India
600
400
200
0
75
ELECTRIC POWER CONSUMPTION
76
2500.0
2000.0
1500.0
China
India
1000.0
500.0
0.0
kWh per capita. World Bank’s WDI.
“CHINA EFFECT” ON ENERGY MARKET
77

China vis-à-vis India
–
–
–
–
–
Energy consumption gap
between the two countries
dated to the 1970s
Bigger GDP
Faster growth
More energy intensive
Despite smaller share of
imported energy
Net import of energy use (World Bank WDI)
KEY FEATURES OF CHINESE ENERGY
CONSUMPTION
78

Acceleration of energy intensity since the 19982001 period
Not due to consumption boom
– But due to urbanization and intensification of state
capitalism
–

China’s energy use is dominated by
industry/commerce rather than by household
sector
–
The household energy consumption only experienced
modest growth over time
% OF HOUSEHOLD ELECTRIC
CONSUMPTION PEAKED IN 2000
79
% Share of personal electricity consumption
16.00%
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
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
National Bureau of Statistics, Statistical Yearbook,, 2009
PERSONAL ENERGY CONSUMPTION
SURGED VERY RECENTLY
80
Personal energy consumption
250.0
200.0
150.0
100.0
50.0
0.0
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
NBS data; kg coal equivalent
MODEST HOUSEHOLD ELECTRIC
CONSUMPTION
81
2500.0
2000.0
Personal electricity
consumption
1500.0
Total electricity
consumption
1000.0
500.0
NBS data; kWh per capita
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
1988
1987
1986
1985
1984
1983
0.0
WOULD CHINA’S ENERGY
DEMAND FALL SUBSTANTIALLY IF
CHINA SUCCEEDS IN
REBALANCING?
82
83
THANK YOU!