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WHAT IS “CHINA MODEL”?

MIT Sloan

School of Management

Yasheng Huang

Professor

MIT Sloan School of Management

Founder

China Lab and India Lab

1

AGENDA

What is China Model?

– Beijing Consensus: State capitalism

– Gradualism: Gradual reforms but acceleration over time

– Reversal story: Substantial reforms but followed by reversals

Major challenges

– 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

2

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

3

BUT STRONG FEATURES OF STATE

CAPITALISM

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 state-

owned

4

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

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

7

THE TRUE CHINA MIRACLE

How did China miracle begin?

Getting the political economy right

Financial liberalization

Reversal of policies in the 1990s

8

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 three times by Mao

Deaf 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.

FINANCIAL LIBERALIZATION AND

REVERSAL15

16

FINANCIAL REVERSAL

DEFINITIONS AND MEASUREMENTS

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.

MIT, March 9 2011

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 enterprises

No Yes

Interest rate regulation More flexibility in rate determination

Controlled interested rate

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

shareholders Put under supervision of local government again

Entry barrier Deregulated, competition from nongovernmental capital is encouraged

Competition is repressed. Informal financing institutions were 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).

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.”

19

FINANCIAL LIBERALIZATION 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 well-

established private enterprises as solid borrowers.”

20

SUBSTANTIAL CREDIT ACCESS IN THE

1980S

THE GREAT REVERSAL

• 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.

21

MIT, March 9 2011

22

THE SURVEY

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

23

THE SAMPLE

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

24

ACCESS TO FINANCE

Figure 1A: % of households receiving formal or informal loans in the two periods.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

% of households receiving

Bank or RCC loans


informal loans


bank, RCC, or informal

Loans

Access to Finance

1986-1991 Survey

1995-2002 Survey

MIT, March 9 2011

25

Baseline result

-- a sharp drop in households’ access to bank loan in the 90s.

Table 3: Baseline results for reduction of credit access as evidence of financial reversal

(1) (2) (3) (4) (5) (6)

Y: Dummy that equals one if loans are obtained from banks or RCCs

Y: log (value of the loan obtained from banks or RCCs)

Y: log (deflated value of the loan obtained from banks or RCCs

Reversal measure

Dummy (1995–2002 period) -1.96** -3.21** -9.30** -13.43** -1.75** -2.30**

[0.45] [0.86] [1.62] [3.40] [0.09] [0.19]

Economic variables

Log(cultivated land) 0.46** 0.52** 2.20** 2.76** 0.15** 0.32**

[0.02] [0.03] [0.12] [0.14] [0.01] [0.01]

Log(number of working 0.27** 0.23** 1.22** 1.06** 0.10** 0.14**

household members) [0.04] [0.05] [0.21] [0.24] [0.02] [0.02]

Investment needs

Log(fixed assets investment) 0.12** 0.12** 0.66** 0.62** 0.09** 0.10**

[0.01] [0.01] [0.03] [0.04] [0.00] [0.00]

Internal and external funding capacity

Log(net household income) -0.42** -0.45** -1.78** -1.90** -0.10** -0.18**

[0.02] [0.03] [0.11] [0.14] [0.01] [0.01]

Log(remittance received) -0.02 -0.02 -0.1 -0.09 -0.01** -0.01

[0.01] [0.01] [0.05] [0.06] [0.00] [0.01]

Education 0.15** 0.11** 0.79** 0.55** 0.08** 0.06**

[0.02] [0.02] [0.09] [0.11] [0.01] [0.01]

Control variables structural changes in the second sample period; Fixed effects: Year, Province, Subsidized family Production category

Observations 66,579 66,579 66,579 66,579 66,579 66,579

Pseudo R2 0.15 0.15 0.08 0.08 0.06 0.06

MIT, March 9 2011

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Informal loan and household financial assets --- 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) (4) (5) (6)

Access to formal credit (banks and RCCs)

Access to informal credit

Access dummy

Log (amount)

Log (deflated amount)

Access dummy

Log (amount)


Dummy (1995–2002 period) -2.04** -8.26** -1.41** -0.85** -3.02** -1.76**

[0.36] [1.75] [0.11] [0.24] [1.10] [0.17]

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** -0.25** -1.24** -0.28**

[0.01] [0.05] [0.01] [0.01] [0.04] [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* 0.05** 0.18** 0.11**

Log(financial assets) [0.01] [0.07] [0.01] [0.01] [0.05] [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 66,516 66,516 66,516

0.20 0.11 0.07 0.12 0.21 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) (3) (4)

Remaining balance on formal loans

Remaining balance on total loans

Log (amount)


Log ( amount)


Reversal measure Dummy (1995–2002 period) -10.76** -9.30** -1.95** -4.07**

[1.82] [0.72] [0.12] [0.16]

Informal credits and internal financial strength

Log(amount of 0.60** 1.19** 0.10** 0.63**

informal loan) [0.03] [0.01] [0.00] [0.00]

Log(financial assets) -0.69** -0.87** -0.11** -0.36**

[0.05] [0.02] [0.01] [0.01]

Dummy (1995–2002 period) * 0.33** 0.56** -0.02** 0.16**

Log(informal loan amount) [0.05] [0.02] [0.01] [0.01]

Dummy (1995–2002 period) * 0.20** 0.42** 0.10** 0.28**

Log(financial assets) [0.07] [0.03] [0.01] [0.01] Other controls (economic, investment, funding capacity) Structural changes in the second sample period Fixed effects: Year, Province, Subsidized family Production category

Observations 66516 66516 66516 66516

Pseudo R2 0.11 0.18 0.07 0.14

MIT, March 9 2011

28

Interest payment

-- was the cost of loans higher in 90s than in 80s?

Table 6: Robustness check for interest payment

Observation # Mean of interest payment rate Difference

t-test of difference

1st period

Bank and RCC loans only 2,281 5.43%

Informal loans only 5,967 1.63%

Both types of loans 2,288 2.43%

All observations 10,536 2.63%

2nd period

Bank and RCC loans only 643 5.66% 0.22% 0.26

Informal loans only 2,899 1.03% -0.60% -1.38

Both types of loans 503 1.77% -0.65% -0.93

All observations 4,045 1.86% -0.77% -2.23

MIT, March 9 2011

29

Is the reversal due to bad loan performance in the in

the 1980s?

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

30

Bank activitiesBank performance and growth in lending activities during the 1980s and 1990s

Panel A: Payback rate of loans Variable (rate in %) 1986–1991 1995–2002 t-statistics of difference

Loan payback rate in RCCs 81.65 84.09 -1.46 Loan payback rate in ABC 91.71 84.58 5.41 TVE loans/total loans from ABC 0.87% 1.26% -1.53 Agriculture loans/total loans from ABC 1.20% 4.13% -4.33

Panel B: The growth rate of various type of loans, deposits, and organizations Variable (average growth rate in %) 1986–1991 1995–2002 t-statistics of difference

RCC total loans 33.52 16.23 5.28 RCC new loans 474.03 RCC total deposits 30.24 18.63 2.89 RCC new deposits 85.87 ABC total loans 12.41 18.98 -0.59 ABC new loans 31.89 6.02 3.29 ABC new loans to TVE -260.66 -4.02 -0.95 ABC total agriculture loans 20.85 -4.85 4.47 ABC new agriculture loans 47.89 -19.10 1.64 ABC # of institutions -3.73 ABC # of employees 21.53

MIT, March 9 2011

31

Bank performance

Figure 5B: Agricultural Bank of China: Equity net worth

MIT, March 9 2011

32

-- Reduction of loan follows good performance.

-- Reversal is worse in provinces that had performed better in the

1st period.

Table 11: Bank loan and bank performance

(1) (2) (3) (4) (5) (6)

Y: A dummy that equals one if loans are accessed from banks or RCCs

Y: log (value of the loan obtained from banks or RCCs)

Bank performance lag 1 year -0.47** -0.56** -0.60** -2.48** -2.85** -3.06** [0.14] [0.15] [0.15] [0.69] [0.71] [0.71] Bank performance forward 1 year 1.54** 1.74** 6.26* 7.44** [0.57] [0.58] [2.54] [2.56] Dummy (1995–2002 period) -3.12** -2.98** -2.79** -13.16** -12.29** -11.19** [0.80] [0.80] [0.80] [3.45] [3.44] [3.46] Better performing provinces 1986-1991 -0.23** -1.33** * Dummy (1995–2002 period) [0.08] [0.38] Economic controls YES YES YES YES YES YES

Structural changes in the controls YES YES YES YES YES YES

Various fixed effects YES YES YES YES YES YES

Constant 0.79** -0.52 -0.67 0.07 -5.21* -0.67 [0.27] [0.55] [0.56] [1.26] [2.47] [0.56] Observations 64,199 62,741 62,741 64,199 62,741 62,741 Pseudo R2 0.16 0.16 0.16 0.08 0.08 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 to informal credit

Access dummy

Log (amount)


Access dummy

Log (amount)


Log(durable goods) -0.28** -1.36** -0.16** -0.02 0.07 0.08**

[0.03] [0.14] [0.01] [0.02] [0.11] [0.02]

Dummy (1995–2002 period) * 0.16** 0.97** 0.16** 0.09** 0.38* 0.02

Log(durable goods) [0.05] [0.23] [0.02] [0.03] [0.16] [0.03]

Days worked on nonfarm business 0.17** 0.91** 0.17** 0.07** 0.39** 0.08**

[0.02] [0.09] [0.01] [0.02] [0.09] [0.02]

Dummy (1995–2002 period) * -0.09** -0.48** -0.13** 0.00 -0.01 -0.01

Days worked on nonfarm business [0.03] [0.12] [0.01] [0.02] [0.11] [0.02]

Political status 0.02 0.12 0.02 -0.01 -0.07 -0.02

[0.05] [0.22] [0.02] [0.03] [0.18] [0.03]

Dummy (1995–2002 period) * 0.17* 0.74* 0.03 0.06 0.37 0.06

Political status [0.09] [0.41] [0.03] [0.06] [0.29] [0.05]

Dummy (1995-–2002 period) -1.89** -9.30** -1.36** -0.89** -3.40** -1.88**

[0.43] [2.49] [0.12] [0.27] [1.22] [0.18]

All other controls; Structural change in the controls; Various fixed effects

Observations 63,017 63,017 63,017 63,017 63,017 63,017

Pseudo R2 0.21 0.11 0.07 0.12 0.06 0.04

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

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

36

37

THE GREAT CONSUMPTION COLLAPSE

0,0

10,0

20,0

30,0

40,0

50,0

60,0

China

Household final consumption expenditure % GDP. From World Bank’s WDI.

38

THE ROOTS OF GLOBAL IMBALANCES:

THE GREAT DIVERGENCE

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

19

80

19

81

19

82

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

China

United States

Household final consumption expenditure % GDP. From World Bank’s WDI

39

CHINA’S UNUSUAL CONSUMPTION

DECLINE

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

19

80

19

81

19

82

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Brazil

China

South Africa


40

IT IS NOT AN EAST ASIAN

PHENOMENON

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

China

Japan

Korea, Rep.


41

CHINA AND INDIA: CONSUMPTION GAP

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

China

India


HAS CHINA RELBANCED? 15% RETAILS GROWTH in 2009 and 18% in

2010

42

43

NO.

INSTITUTIONAL RETAIL CONSUMPTION

HAS RISEN SHARPLY

0%

5%

10%

15%

20%

25%

30%

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

% of institutional retail sales

44

45

HOUSEHOLD CONSUMPTION HAS

DECLINED FURTHER IN 2008 AND 2009

0,0

10,0

20,0

30,0

40,0

50,0

60,0

198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009

China


STABILIZING THE CONSUMPTION

SHARE OF GDP DURING THE

CRISIS PERIOD

46

THE KEY TO REBALANCING IS

PERSONAL INCOME, NOT GDP OR

SAVINGS RATE.

47

48

WHY DID CONSUMPTION DECLINE IN

CHINA?

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

Rural income and consumption growth:

– 1980s and since 2003: Consumption growth matched

income growth

– 1990s: Income growth exceeded consumption growth but by

a slim margin

Zhou Xiaochuan (07/09, governor of China’s central

bank)

– No increase in household savings rate in recent years

No support for the pre-cautionary savings hypothesis

49

CAUTIONARY SPENDING HYPOTHESIS

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

50

51

GDP AND PERSONAL INCOME

DIVERGENCE

GDP AND HOUSEHOLD INCOME

GROWTH: 1978-200852

REAL RURAL CONSUMPTION GROWTH

(1978 PRICES)

53

DATA INCONSISTENCIES

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

54

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:

– 721 million rural residents in 2008

– 230 million rural migrants (NBS 2009)

– There are many “rural cities” in China (contrast with India)

Supply side (=Entrepreneurship):

– 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?

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

58

A VERY SMALL SERVICE SECTOR

59

60

URBANIZATION AND

PERSONAL INCOME:

SURVEY EVIDENCE

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

61

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)

0

500

1000

1500

2000

2500

1996 1997 1998 1999 2000 2001 2002 2003 2004

Size of urban area: KM2

Mean

Median

Standard deviation

SPATIAL MEASURE: CONSTRUCTED AREA (

城建区)

0

20

40

60

80

100

120

1996 1997 1998 1999 2000 2001 2002 2003

Completed construction area: KM2

Mean

Median

Standard deviation

65

CONSUMPTION DECLINED SHARPLY

AFTER 2000

0,0

10,0

20,0

30,0

40,0

50,0

60,0

China


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

66

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)

0

5000

10000

15000

20000

25000

30000

35000

40000

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Real GDP per capita

Real GDP per capita

68

GDP AND WAGE DATA IN

GUANGDONG (SURVEY DATA)

0

5000

10000

15000

20000

25000

30000

35000

40000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Real GDP per capita

Real annual starting wage

Rural migrant survey data from Zhongshan University

69


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


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


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

Matching personal income growth with GDP

growth

Reforms, not government spending

– Land reforms

– Urban registration reform

– Social provisions

– Political reforms

73

ENERGY INTENSITY OF GDP

74

75

PER CAPITA ENERGY USE: CHINA AND

INDIA

0

200

400

600

800

1000

1200

1400

1600

19

71

19

72

19

73

19

74

19

75

19

76

19

77

19

78

19

79

19

80

19

81

19

82

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

China

India

ELECTRIC POWER CONSUMPTION

0,0

500,0

1000,0

1500,0

2000,0

2500,0

China

India

kWh per capita. World Bank’s WDI.

76

“CHINA EFFECT” ON ENERGY MARKET

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)

77

KEY FEATURES OF CHINESE ENERGY

CONSUMPTION

Acceleration of energy intensity since the 1998-

2001 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

78

% OF HOUSEHOLD ELECTRIC

CONSUMPTION PEAKED IN 2000

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

14,00%

16,00%

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

% Share of personal electricity consumption

National Bureau of Statistics, Statistical Yearbook,, 2009

79

PERSONAL ENERGY CONSUMPTION

SURGED VERY RECENTLY

0,0

50,0

100,0

150,0

200,0

250,0

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

Personal energy consumption

NBS data; kg coal equivalent

80

MODEST HOUSEHOLD ELECTRIC

CONSUMPTION

0,0

500,0

1000,0

1500,0

2000,0

2500,0

19

83

19

84

19

85

19

86

19

87

19

88

19

89

19

90

19

91

19

92

19

93

19

94

19

95

19

96

19

97

19

98

19

99

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

Personal electricityconsumption

Total electricityconsumption

NBS data; kWh per capita

81

WOULD CHINA’S ENERGY

DEMAND FALL SUBSTANTIALLY IF

CHINA SUCCEEDS IN

REBALANCING?

82

83

THANK YOU!

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