Who are entrepreneurs in Russia, Brazil, and China? Simeon Djankov, World Bank Yingyi Qian, UC Berkeley and CEPR Gérard Roland, UC Berkeley and CEPR Ekaterina

Who are entrepreneurs in Russia, Brazil, and China?

Simeon Djankov, World BankYingyi Qian, UC Berkeley and CEPR

Gérard Roland, UC Berkeley and CEPREkaterina Zhuravskaya, CEFIR and CEPR

Motivation• Entry and SMEs growth is strongly emphasized as

a priority in policy agenda of most developing and transition countries

• Economic theory, i.e., endogenous growth, development and transition literatures, also stress the importance of entrepreneurship for economic growth and development– So far, however, there has been little evidence on factors

determining entrepreneurial activity– Its understanding is crucial for policy-making– Institutional reforms may be disappointing if roots of

entrepreneurship lie in culture or in personality traits

Three perspectives on entrepreneurship in social sciences

• Institutions: – Credit constraints– Security of property rights– Regulatory burden

• Sociological variables: – Culture, religion, values, trust– Social networks

• Personality traits: – Need for achievement, Belief in personal effort, Self-

confidence, and Attitudes towards risk

• Lots of research within disciplines; little work that looks at each of these factors controlling for the other ones

Large project• Provide empirical evidence on determinants of

entrepreneurship in BRINC (Brazil, Russia, India, Nigeria, China)– countries with sufficient regional variation; unequal length of

experience with entrepreneurship; that cover 44.8% of the Earth’s population

• Using similar instrument, survey entrepreneurs and non-entrepreneurs in order to inquire about:– individual characteristics; sociological variables and

perceptions of institutional environment

• Explore individual, regional, country-level variation• So far: results from pilot studies in Russia, China, and

Brazil

Structure of the pilotsIn each country, survey individuals in seven cities of four regions:

1. A random sample of 400 entrepreneurs (414 in China)• Defined as owner-manager of a business with 5 or more employees

2. An sample of 540 non-entrepreneurs (561 in China)• Partly matched by age, gender, and education

• Russia: Survey in seven cities in 2003-2004 academic year: – Moscow; Nizhny Novgorod and Dzershinsk in the Nizhegorodskaya oblast; Perm and Chaykovsky in

the Permskaya oblast; Rostov on the Don and Taganrog in the Rostovskaya oblast

• China: Survey in seven cities in 2004-2005 academic year: – Beijing; Wuhan and Huangshi in the Hubei province; Guangzhou and Zhongshan in the Guandong

province; Xi’an and Baoji in the Shanxi province

• Brazil: Survey in seven cities in 2005 year: – Sao Paulo; Curitiba and Londrina in the Sul region; Salvador and Feira de Santana in the Nordeste

region; Brazilia and Goiania in the Centro Oeste region

In China and Russia: An additional short survey among a random sample of 1200 respondents about their basic personal characteristics and whether they are entrepreneurs – to get information about the structure of the population. In India – this information came from the population census

There is vast within country variation in entrepreneurship; x-country - the most

widespread in Brazil, and the least in RussiaShare of entrepreneurs and self-employed by cities

18%16%

13%11% 11%

8%6%

25% 24% 24%

18% 18%

14%12%

31%28% 27% 27%

24% 23%

19%

0%

10%

20%

30%

1. Differences in Personality traits, Social environment, Trust, and Values

• Comparison of conditional means– condition on city-level dummies (institutional

environment), age, gender, education and education sqrd

• Standard errors are corrected for clusters in error terms at the city-level

Mobility and attitude towards risk E are more mobile geographically in all three countries;

E are mobile across jobs and industries in Russia and China, and less – in Brazil; E are more risk-loving in Russia and China

0.00 0.50 1.00 1.50 2.00 2.50

Number of localities lived(apart from current)

Number of distinctprofessional activities (apart

from current)

Number of different industries(proxy)

Accept a risk neutral gamble,%

Russian E Russian NE Chinese E Chinese NE Brazil E Brazil NE

(No data for Russia)

Different Scale here

Motivation and happiness: E more happy (in China insignificant); Preference for work over leisure – in three countries; In China and Russia entrepreneurs are greedy; and

in Brazil the relationship is reversed

0 0.5 1 1.5

Very happy or quitehappy in life, %

Retire if won 100 timesGDP pc (controlling for

wealth)

Reason: want moremoney


0,05

0,14

0,31

0,70

0,18

0,24

0,37

0,44

0,43

0,81

0,0 0,2 0,4 0,6 0,8 1,0

Retire if won 100 times GDP pc, %

Retire if won 500 times GDP pc

Retire if won 5000 times GDP pc

Why not retire: I like what I do

Why not retire: I want more money

Why not retire: social mission

Very successful or quite successful

Entrepreneurs Non-entrepreneurs

Example: China (in %)E – want to continue of won a lot of money and the reason is to earn even more money

Over-confidence: both “better then average” bias and “knowledge overconfidence” on trivia questions. In Brazil: the opposite effect to what physiologists predicted: entrepreneurs more adequately assess their abilities and knowledge than non-entrepreneurs.

Legal social norms:In Russia and China entrepreneurs are more tolerant to corruption

and unlawful behavior than NE; in Brazil – the opposite

Respondent can justify to some degree:0.00 0.20 0.40 0.60 0.80 1.00

accepting a bribe, %

avoiding fare on transport, %

buying stolen, %


Work ethic and trust:Work ethic – everywhere; in China and Russia – E lower

general trust and in Brazil higher; E trust government more in China and Brazil

0.000 0.250 0.500 0.750 1.000

Work is very important

Have a lot or some of trustin colleagues, %

Have a lot or some trust inpeople in town, %

Have a lot or some trust ingovernment, %


Social environment:Entrepreneurs have more friends and family members –

entrepreneurs in all three countries0.00 0.50 1.00 1.50 2.00 2.50

Number of relatives -entrepreneurs

Number of school friends -entrepreneurs

Number of adolescent friends -entrepreneurs


Important to note that these may not be causal due to both omitted variable and reverse causality. In Brazil – were able to instrument with birth order and found causal effect

2. Physiological and Sociological determinants of entrepreneurship

(controlling for institutional variation with city-level dummies)

- So far, just summarized the differences b/w E and NE;

- But many of these differences are driven by careers of the respondents. I.e., values and perceptions of social norms and business climate are formed on the basis of people’s experiences

- Next step is to look at factors that arguably can be considered exogenous

1 2 3 4

Pooled Russia only China only Brazil only

Father has secondary or higher education 0.031 0.193 0.002 -0.068 [0.025] [0.057]*** [0.015] [0.027]** Father was a boss or director 0.094 0.01 0.053 0.064 [0.028]*** [0.052] [0.023]*** [0.030]** Mother was a boss or director 0.036 0.19 0.067 0.041 [0.053] [0.101]** [0.053]* [0.050] There are (current or former) entrepreneurs 0.102 0.052 0.049 0.106 among relatives [0.027]*** [0.043] [0.022]*** [0.025]*** There are (current or former) entrepreneurs 0.136 0.069 0.097 0.125 among friends (from last place of study) [0.025]*** [0.049] [0.024]*** [0.028]*** Cognitive test score 0.013 -0.005 0.005 0.018 [0.008]* [0.013] [0.005] [0.009]** Height 0.003 0 0.001 0.004 [0.002]** [0.003] [0.001] [0.002]** Risk-loving 0.058 0.067 0.103 -0.012 [0.021]*** [0.044] [0.014]*** [0.025] Top 10% in secondary school (self-reported) 0.002 0.125 -0.015 -0.009 [0.023] [0.055]*** [0.015] [0.026] Greed 0.008 0.096 0.032 -0.082 [0.021] [0.040]** [0.014]** [0.028]*** Observations 2351 709 870 772

• Probit regressions. Dependent variable: P(entrepreneur vs. non-entrepreneur)• Control for city fixed effects, gender, age, education, and education squared. • Report marginal effects.• Robust standard errors in brackets.

Effect of individual characteristics and social environment controlling for institutional environment

5 6 7

China and Brazil compared to Russia

Effect for

Russia X-term with

China dummy X-term with

Brazil dummy

Father has secondary or higher education 0.195 -0.099 -0.116 [0.064]*** [0.019]*** [0.015]*** Father was a boss or director 0.008 0.072 0.048 [0.042] [0.068] [0.059] Mother was a boss or director 0.161 -0.032 -0.059 [0.090]** [0.047] [0.029] There are (current or former) entrepreneurs 0.042 0.024 0.063 among relatives [0.035] [0.048] [0.054] There are (current or former) entrepreneurs 0.056 0.073 0.055 among friends (from last place of study) [0.040] [0.060] [0.054] Cognitive test score -0.004 0.012 0.019 [0.011] [0.013] [0.013] Height 0 0.002 0.004 [0.003] [0.003] [0.003] Risk-loving 0.056 0.159 -0.056 [0.039] [0.080]** [0.031] Top 10% in secondary school (self-reported) 0.102 -0.082 -0.072 [0.044]*** [0.021]*** [0.021]** Greed 0.077 -0.027 -0.103 [0.031]** [0.039] [0.020]*** Observations 2351

• Probit regressions. Dependent variable: P(entrepreneur/non-entrepreneur)• Also control for gender, age, education, and education squared. • Report marginal effects.• Robust standard errors in brackets.

X-country comparisons of the individual and social effects

(1) (2) (3) (4)Probit OLS Probit Probit

Dependent variable: E Years as EE with

positive sales growth

NE who thought of

own business

Comparison group: All NE ---- The rest of ENE who never

thought

Report: dP(E)/dx dY/dx dp(.)/dx dp(.)/dxFather had higher education 0.005 0.564* -0.221*** -0.003Father was a boss or director 0.011 0.111 -0.011 0.006Mother was a boss or director 0.081 0.498 -0.167 0.191Mother was a party member -0.021* -0.467*** -0.109 0.093Family members - entrepreneurs 0.012* 0.566*** 0.088*** 0.065***Friends - entrepreneurs 0.031*** 0.564*** -0.004 0.078***Cognitive test score 0.004 0.031 -0.031 0.005Height 0.001** 0.016 0.008 0.003Risk-loving 0.078*** 0.661*** 0.157 -0.005Top 10% in secondary school -0.007 -0.012 0.118** -0.018Greed 0.141*** 1.329*** 0.134*** 0.032Favorable local population 0.009 0.144 -0.03 0.015Favorable government 0 -0.174*** 0.035* -0.014City dummies, age, gender, and education with a quadratic term

yes*** yes*** yes*** yes***

Employment and industry dummies yes***Observations 802 785 340 392R-sqrd (Pseudo R-sqrd) (0.38) 0.2 (0.12) (0.2)

Specification:

Standard errors corrected for clusters in the error terms at the city-level

Expl: China

Outcomes in dependent variable:

E Failed ENE who

never was E

Report:Father had higher education 0.005 0.015 -0.02Father was a boss or director 0.007 0.009 -0.016Mother was a boss or director 0.035 0.002 -0.037Mother was a party member -0.023 0.011 0.012Family members - entrepreneurs 0.011** 0.026 c -0.037Friends - entrepreneurs 0.028*** 0.036***c -0.064***Cognitive test score 0.003 -0.002 -0.001Height 0.001 -0.005***ac 0.005**Risk-loving 0.075*** 0.027 c -0.102**Top 10% in secondary school 0.001 0.092**ac -0.093**Greed 0.072*** 0.008 ac -0.08***Favorable local population 0.009 0.004 -0.013Favorable government -0.004* -0.042***ac 0.046***City dummies, age, gender, and education with a quadratic term

yes*** yes*** yes***

ObservationsPseudo R-sqrd

dP(.)/dx; (ΣdP(.)/dx = 0)

(5)Multinomial Logit

0.35802

China: “Failed entrepreneurs”

Failed E: - Have the highest shares of E among family and friends- Shortest- Least smart- Best self-reported performance in school- Consider government as least favorable

Outcomes in dependent variable:Opportunity

ENecessity

E

NE who never was

E

Report:Father had higher education 0.005 -0.004*** -0.001Father was a boss or director 0.001 0.001 -0.002Mother was a boss or director 0.025* -0.007 a -0.019Mother was a party member -0.013 -0.003 0.015Family members - entrepreneurs 0.004 0.002***c -0.006Friends - entrepreneurs 0.016*** 0.004**ac -0.019***Cognitive test score 0.001 0.001*c -0.003Height 0 0 -0.001Risk-loving 0.046*** 0.012***ac -0.057***Top 10% in secondary school -0.004 -0.001 c 0.004Greed 0.043*** 0.015***ac -0.058***Favorable local population 0.005 0.002***c -0.007Favorable government 0 0 -0.001

City dummies, age, gender, and education with a quadratic term

yes*** yes*** yes***

ObservationsPseudo R-sqrd 0.35

782

dP(.)/dx; (ΣdP(.)/dx = 1)

(6)Multinomial Logit

China: “Necessity vs. opportunity”

E by necessity:

In the middle b/w NE and E by opportunity

- E among friends and family

- Risk attitude

- Greed

But they are closer to E than to NE

3. Importance of financial constraints

Personal saving is the main source of financing for start-ups in all three countries

ENTREPRENEURS: How were you able to raise money to set up your first enterprise?

0% 20% 40% 60% 80% 100%

Personal funds

Funds of relatives

Funds of friends

Bank credit

Russia (n=400) China (n=414) Brazil (n=265)

Retained earnings is the main source of financing of expansion

ENTREPRENEURS: From what source do you plan to finance the expansion of your business?

0% 20% 40% 60% 80% 100%

Retained earnings

Funds of relatives

Funds of friends

Bank credit

Government funding

Russia (n=247) China (n=198) Brazil (n=276)

Brazil stands out – much better access to outside finance; more government money

Lack of finance is the main reason

not to start a business in all three countries

RUSSIAN NON-ENTREPRENEURS (n=477): Why did not you become entrepreneur?

Cannot find a project

Do not know how to start

Cannot find moneyDo not want to break law

Too risky

Not capable

Other

CHINESE NON-ENTREPRENEURS, WHO THOUGHT OF BECOMING ENTREPRENEUR (n=84):

Why your thoughts and actions did not realize in actual business?

Did not find a project

Too risky

Other

Did not find money

Better job

Administrative

constraints

BRAZILIAN NON-ENTREPRENEURS, WHO THOUGHT OF BECOMING ENTREPRENEUR (n=123):

Why your thoughts and actions did not realize in actual business?

Not enough skills

Too risky

Did not find a project

Did not find money

Other

Better job

Financial constraints are important reason even not to think about entrepreneurship

Why you do not think about starting business?

(402 obs. of non entrepreneurs)

Too much risk

Satisfied with my job Lack of skills

Lack of money

OtherDo not likeentrep-

reneurship

NE who never thought of own business: why haven't you thought of own business? (n=227)

lack of skills

unfavorable environment

wouldn't find money

satisfied with what you do

too muck risk

dislike entrepreneurs

hip

bureaucratic constraints

other

BRAZIL CHINA

CHINA

0% 20% 40% 60%

small demanddifficult to find money

administrative pressure on larger firmsinsufficient managerial resources

difficult to find employeeshostility from gov't

health problemshigher taxes for larger firms

fear increase in racketshappy with current situation

fear hostility from family and friendsagreement with competitors

In China finance is relatively more important constraint to expand business compared to Brazil

BRAZIL

0% 10% 20% 30% 40% 50% 60% 70% 80%

macroeconomic conditionstaxes

not enough demandsatisfied with current

hard to find moneyhard to find workers

administrative barriersinsufficient managerial

fear of extortion from gov'tpersonal

fear of extortion from criminalsother

agreemant with competitorsfear of envy from people

4. Institutional environment and entrepreneurship

• Methodology: Take city fixed effects after controlling for social and individual characteristics and correlate with average city perceptions of institutions

• Here report correlations for the % of entrepreneurs across cities

• We get the same results with the growth of business

Share of entrepreneurs and petty corruption – significant negative correlation (even

controlling for country differences)

CH: Huangshi

CH: Zhongshan

RU: Taganrog

BR: Curitiba

BR: Brazilia

RU: Perm

BR: Salvador

BR: Feira de Santana

RU: Chaikovsky

RU: Nizhny Novgorod

RU: Dzerzhinsk

CH: Beijing

BR: Londrina

CH: Wuhan

CH: Guangzhou

RU: Moscow

BR: Goiania

RU: Rostov-on-Don

BR: Sao Paulo

CH: Baoji

CH: Xi'An

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.4 -.2 0 .2 .4Bribes not to comply with regulations

coef = -.09105739, (robust) se = .04788555, t = -1.9

Controlling for country differences

CH: Huangshi

CH: Zhongshan

BR: Curitiba

BR: Brazilia

BR: Salvador


CH: Beijing

RU: Taganrog

CH: Wuhan

BR: Londrina

CH: Guangzhou

RU: Perm

BR: Goiania

CH: Baoji

BR: Sao Paulo

RU: Chaikovsky

RU: Nizhny Novgorod

RU: Dzerzhinsk

CH: Xi'An

RU: Moscow

RU: Rostov-on-Don-.

15-.

1-.

050

.05

.1S

hare

of e

ntre

pren

eurs

-.4 -.2 0 .2 .4Bribes not to comply with regulations

coef = -.20748034, (robust) se = .07016332, t = -2.96

No control for country differences

Share of entrepreneurs and state capture –significant negative correlation (even


CH: Huangshi

CH: Zhongshan

RU: Taganrog


RU: Chaikovsky

BR: Brazilia

BR: Curitiba

RU: Perm

BR: Salvador

BR: Londrina

CH: Beijing

CH: Wuhan

RU: Nizhny Novgorod

RU: Dzerzhinsk

BR: Goiania

RU: Moscow

CH: Guangzhou

BR: Sao Paulo

CH: Baoji

RU: Rostov-on-DonCH: Xi'An

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.4 -.2 0 .2 .4Bribes to change rules

coef = -.09620558, (robust) se = .04331472, t = -2.22


CH: Huangshi

CH: ZhongshanRU: Taganrog


BR: Brazilia

BR: Curitiba

RU: Chaikovsky

CH: BeijingCH: WuhanBR: Salvador

CH: Guangzhou

BR: Londrina

RU: Perm

CH: Baoji

BR: Goiania

BR: Sao Paulo

RU: Nizhny Novgorod

RU: Dzerzhinsk

RU: Moscow

CH: Xi'An

RU: Rostov-on-Don-.

15-.

1-.

050

.05

.1S

hare

of e

ntre

pren

eurs

-.4 -.2 0 .2 .4Bribes to change rules

coef = -.15017679, (robust) se = .06734293, t = -2.23


Share of entrepreneurs and crime –significant negative correlation (even


RU: Taganrog


RU: Dzerzhinsk

CH: Huangshi

BR: Salvador

CH: Beijing

CH: Baoji

CH: Zhongshan

CH: Wuhan

BR: Curitiba

BR: Brazilia

RU: Moscow

BR: Londrina

RU: Nizhny Novgorod

RU: Rostov-on-Don

RU: Perm

RU: Chaikovsky

BR: Sao PauloCH: Xi'An

BR: Goiania

CH: Guangzhou

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.2 -.1 0 .1 .2Probability of theft

coef = -.2480609, (robust) se = .07602441, t = -3.26


CH: HuangshiCH: Beijing

CH: Baoji


CH: ZhongshanRU: Taganrog

CH: WuhanBR: Salvador

RU: Dzerzhinsk

CH: Xi'An

BR: Curitiba

BR: Brazilia

BR: Londrina

CH: Guangzhou

BR: Sao Paulo

RU: Moscow

BR: Goiania

RU: Nizhny Novgorod

RU: Rostov-on-Don

RU: Perm

RU: Chaikovsky-.

15-.

1-.

050

.05

.1S

hare

of e

ntre

pren

eurs

-.2 -.1 0 .1 .2Probability of theft

coef = -.27976281, (robust) se = .12013597, t = -2.33


Share of entrepreneurs and quality of courts – positive (insignificant) correlation controlling for country differences

RU: Rostov-on-Don

RU: Moscow

CH: Xi'AnBR: Sao Paulo

BR: Goiania

CH: Wuhan

RU: Chaikovsky

BR: Brazilia

CH: Guangzhou

BR: Curitiba

RU: Taganrog

CH: Baoji

CH: Beijing

BR: Salvador

CH: Zhongshan

RU: DzerzhinskBR: Londrina


RU: Nizhny Novgorod

CH: HuangshiRU: Perm

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.1 -.05 0 .05 .1Effectiveness of courts

coef = .19405452, (robust) se = .12718354, t = 1.53


RU: Rostov-on-Don

BR: Sao Paulo

RU: Moscow

BR: Goiania

BR: Brazilia

BR: Curitiba

RU: Chaikovsky

RU: Taganrog

BR: Salvador

BR: Londrina


CH: Xi'An

RU: Dzerzhinsk

CH: Wuhan

CH: Guangzhou

RU: Nizhny Novgorod

RU: Perm

CH: Baoji

CH: Beijing

CH: Zhongshan

CH: Huangshi

-.15

-.1

-.05

0.0

5.1

Sha

re o

f ent

repr

eneu

rs

-.2 -.1 0 .1 .2Effectiveness of courts

coef = .02618685, (robust) se = .1521357, t = .17


Share of entrepreneurs and rackets –insignificant correlation

RU: Taganrog


CH: Zhongshan

CH: Guangzhou

CH: Huangshi

BR: Londrina

BR: Salvador

RU: Moscow

CH: Wuhan

CH: Beijing

RU: Dzerzhinsk

RU: Chaikovsky

CH: Baoji

BR: Curitiba

RU: Rostov-on-Don

RU: Nizhny Novgorod

BR: Sao Paulo

BR: Brazilia

BR: Goiania

RU: Perm

CH: Xi'An

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.2 -.1 0 .1 .2Rackets

coef = -.10339224, (robust) se = .09762329, t = -1.06


CH: Zhongshan

CH: Guangzhou

CH: HuangshiCH: WuhanCH: Beijing

CH: Baoji


RU: TaganrogCH: Xi'An

BR: Londrina

BR: Salvador

RU: Moscow

BR: Curitiba

BR: Sao Paulo

RU: Dzerzhinsk

RU: Chaikovsky

BR: Brazilia

RU: Rostov-on-Don

RU: Nizhny Novgorod

BR: Goiania

RU: Perm

-.15

-.1

-.05

0.0

5.1

Sha

re o

f ent

repr

eneu

rs

-.3 -.2 -.1 0 .1 .2Rackets

coef = -.07358125, (robust) se = .08384264, t = -.88


Share of entrepreneurs and attitude of population towards entrepreneurs – no correlation

BR: Brazilia

CH: Xi'AnBR: Sao Paulo

RU: TaganrogCH: Beijing

BR: Londrina

CH: Wuhan

RU: Nizhny Novgorod

RU: Chaikovsky

RU: Moscow

CH: Baoji

BR: Goiania

BR: Salvador

RU: Rostov-on-Don

RU: PermCH: Huangshi

RU: Dzerzhinsk

CH: Guangzhou

CH: Zhongshan


BR: Curitiba

-.1

-.05

0.0

5S

hare

of e

ntre

pren

eurs

-.1 -.05 0 .05 .1 .15Attitude of population towards entrepreneurs

coef = .0227087, (robust) se = .13747114, t = .17


BR: Brazilia

BR: Sao Paulo

CH: Xi'An

BR: Londrina

RU: Taganrog

CH: BeijingCH: Wuhan

RU: Nizhny Novgorod

RU: Chaikovsky

BR: Goiania

BR: Salvador

RU: Moscow

CH: Baoji

RU: Rostov-on-Don

RU: Perm

CH: Huangshi

RU: Dzerzhinsk


CH: Guangzhou

CH: Zhongshan

BR: Curitiba

-.15

-.1

-.05

0.0

5.1

Sha

re o

f ent

repr

eneu

rs

-.15 -.1 -.05 0 .05 .1Attitude of population towards entrepreneurs

coef = -.08823711, (robust) se = .17920342, t = -.49


Paternalistic governments are negatively associated with plans to

expand businessLocal gov’t tries to create a favorable -1.677 business environment, % of city population [0.273]***

Local gov't hampers -0.825 business environment, % of city population [0.293]***

Regional gov’t tries to create a favorable -1.208 business environment, % of city population [0.277]***

Regional gov't hampers -0.761 business environment, % of city population [0.376]**

Central gov’t tries to create a favorable 0.749 business environment, % of city population [0.292]***

Central gov't hampers -0.603 business environment, % of city population [0.316]*

• Probit regressions. Dependent variable: P(plans to expand)• Control for city fixed effects, gender, age, education, and industry. • Report marginal effects.• Robust standard errors in brackets.

0.04

0.06

0.09

0.17

0.08

0.25

0.15

0.12

0.10

0.10

0.10

0.48

0.45

0.26

0.26

0.28

0.42

0.38

0.28

0.36

0.43

0.39

0.00 0.15 0.30 0.45 0.60

High taxes

Complicated tax rules and forms

Competition

Rackets

Inflation and macroeconomic instability

Poor functioning of courts

Diff iculty of raising outside finance

Government administrative regulations

Bureaucratic constraints

Corruption

Crime

Bad public infrastructure

Poor public goods provision

Non-transparent "rules of game"

Entrepreneurs Non-entrepreneurs

CHINA: Perceptions of institutional environmentE perceive business climate as more friendly than non-entrepreneurs

Conclusions: (1) similarities…What is similar in all three countries: • Entrepreneurs is a special group of people with distinct

values and personality traits compared to non-entrepreneurs– particularly, work ethics and value of power common to all three

countries

• Social environment is extremely important for entrepreneurship and robust in all three countries: 1. Presence of entrepreneurs among family and childhood friends

increases the probability of a person to become an entrepreneur (subject to possible endogeneity problem)

2. Social class: boss or director in the family and having richer families

• Effect of institutions (corruption, courts, credit constraints)

Conclusions: (2) differences…What is different:• Effects of some personality traits differ across

countries:– Greed, risk-loving, mobility across jobs and industries

is higher for E than for NE in China and Russia, but the sign is reversed in Brazil

• Attitude towards legal norms (China - Russia vs. Brazil)

• Why?– One possibility is the absence of history of entrepreneurship in China

and Russia (all entrepreneurs are “start-up” entrepreneurs) while in Brazil – long-surviving family firms and established norms and traditions

Documents

Who are entrepreneurs in Russia, Brazil, and China? Simeon Djankov, World Bank Yingyi Qian, UC Berkeley and CEPR Gérard Roland, UC Berkeley and CEPR Ekaterina