Who are the Self-Employed in the Developing World?

Report
Who are the Self-Employed in the
Developing World?
Based on
“
“Self-Employment in the Developing World” (Gindling and Newhouse)
and
“Who Are the World’s Entrepreneurs and What Constraints Do They Face?” (Margolis and
Robalino)
Motivation (1)
 Wage and salary employment is lacking in the developing
100
world
RUS
80
LTU
CUB
UKR
MUS
MYS
CRI
MKD
PAN
60
MDA
TUR
PHL
NIC
HND
ARM
PRY
MAR
URY
MEX
BRA
JAM
EGY
ECU
LKA
40
ARG
CHL
VEN
SLV
PER DOM
COL
THA
20
PAK
GEO
IDN
BGD
0
2000
4000
6000
GDP per Capi ta
8000
10000
Motivation (2)
 Self Employment is a key source of jobs in the developing
world
60
BD
50
AM
ID
CO
30
40
PY
HN
NI
PH
PK GE
EC
LK
MD
MA
PE
DO
VE
JM
TH
SV
EG
BR
PA
TR
CR
CL MX
UY
20
AR
MY
UA
MK
MU
10
LT
RU
0
2000
4000
6000
GDP per Capi ta
8000
10000
Outline
 Constrained occupational choice model of employment status
determination
 Data
 Descriptive statics: Who are the self employed?
 Determinants of “successful” self employment
 Distribution of unsuccessful self employed with potential for
success
Occupational choice with constraints
 Compare the value of self-employment / entrepreneurship and wage / salary employment
 Determinants of the value of a wage/salary job:
 Likelihood of finding a job
•
•
•
Age
Level of education and skills (technical, cognitive, and non-cognitive)
Richness of their social network.
 Stability of the job
 Income from the job
 Non-pecuniary benefits


Possible access to social protection
Health and safety risks
 Determinants of the value of self employment/entrepreneurship:
 Availability of entrepreneurial earnings opportunity
 Startup capital
 Stability of income stream
 Availability of alternative income insurance mechanisms
 Skills
 Individual preferences, risk aversion, time preferences, etc… determine weights
Occupational choice with constraints
 Internal Constraints
 Limited skills
 Tight market for salaried jobs (may be linked to rural/urban status)
 Limited capital/collateral
 External constraints
 “Subsistence activity” is economically non-viable
 Use of inappropriate technologies
 Limited access to capital
 Lack of information about better technologies or opportunities
 Mobility restrictions.
 Regulations that make it difficult to create a business or access credit
 Lack of infrastructure
 Product market imperfections that reduce competition
 Property rights
 Contract enforcement
 Lack of information and ability to process it.
 Lack of adequate social protection systems
Occupational choice with constraints
 A framework for thinking about who becomes self employed
 Allows us to understand why some individuals might be less
successful than others
 Internal or External reasons
 The frequency “constrained gazelles” provides an indication
of the importance of constraints
 We use micro data to address these questions
Data – I2D2 v2
(International Income Distribution Database)
 Compilation of harmonized household micro data sets from
nearly 100 countries
 Maintained by the World Bank’s Development Economics
group
 Covers all income levels
 Some data sets have extra variables
 Household consumption
 Earnings (validity?)
 Assets
Slovenia
Spain
Sweden
United Kingdom
2008
2008
2008
2007
HIC
HIC
HIC
HIC
2.1
46.2
9.4
62.2
Macedonia, FYR
2005
Moldova
2005
Romania
2008
Russian Federation
2003
Tajikistan
2003
Turkey
2005
Turkmenistan
1998
Ukraine
2005
Latin America and Caribbean
3625.7 63%
Argentina***
2006
4137.1 60%
Bolivia
2005
Brazil
2008
Population of
Chile
2009
sample countries
2010 Pop as % of regional
Colombia
2000
population of
(millions) Population
Income
Costa Rica Year
2006 Group
412.2 sample
21% countries Sub-Saharan
Africa
Dominican Republic
2004
2010
Pop as % of regional Angola
14.1
1999
LMIC
Ecuador
2004
population
(millions)
Year
Income
Group
232.5
Burundi El Salvador
1998
2005LIC
412.2
21%
Sub-Saharan
Africa
2.7
Cameroon*
2007
LMIC
Guatemala
2006
14.1
Angola
1999
LMIC
93.6
Chad Haiti
2002
2001LIC
232.5
Burundi
1998
LIC
68.1
Congo, Republic
of
2006
LMIC
Honduras
2003
2.7
Cameroon*
2007
LMIC
1.1
Cote d'Ivoire*
2002
LMIC
Jamaica
2002
93.6
Chad
2002
LIC
350.8
86%
Congo, Democratic
2005of
Mexico Republic
2008LIC
68.1
Congo,
Republic
of
2006
LMIC
3.2
Ethiopia*Nicaragua*
2004
2005LIC
1.1
Cote d'Ivoire*
2002
LMIC
9.6
Gabon
2005
UMIC
Panama
2003
350.8
86%
Congo,
Democratic
Republic
2005
of
LIC
3.8
Gambia, Paraguay
The
1998
2006LIC
3.2
Ethiopia*
2004
LIC
7.6
Ghana Peru
2005
2002LIC
9.6
Gabon
2005
UMIC
4.5
Kenya Uruguay*
2005
2006LIC
3.8
Gambia, The
1998
LIC
16.3
Liberia
2007
Venezuela, Rep. Bol.
2004LIC
7.6
Ghana
2005
LIC
3.3
Malawi Middle East and2005
North Africa LIC
4.5
Kenya
2005
LIC
2.1
MauritiusEgypt
2008
UMIC
2005
16.3
Liberia
2007
LIC
3.6
NamibiaJordan
1993
UMIC
2002
3.3
Malawi
2005
LIC
21.4
Niger*
2002
Morocco
1998LIC
2.1
Mauritius
2008
UMIC
141.8
Nigeria Syrian Arab Rep*
2003
LMIC
2004
3.6
Namibia
1993
UMIC
7.1
Senegal Tunisia
2001
LMIC
2001
21.4
Niger*
2002
LIC
75.7
Sierra Leone
2003
LIC
South Asia
141.8
Nigeria
2003
LMIC
5.2
Swaziland
2000
LMIC
Bangladesh
2005
7.1
Senegal
2001
LMIC
45.8
Tanzania,India**
United Republic
2006
of
2008LIC
75.7
Sierra
Leone
2003
LIC
564.6 98%
Uganda Pakistan
2005
2008LIC
5.2
Swaziland
2000
LMIC
40.7
Zambia Sri Lanka**
2003
2005LIC
45.8
Tanzania,
United
Republic
2006
of
LIC
10.0
HIGH
INCOME
COUNTRIES
564.6 98%
Uganda
2005
LIC
Data – I2D2 v2
UMIC
LMIC
UMIC
UMIC
LIC
UMIC
LMIC
LMIC
2.1
3.6
21.4
141.8
7.1
75.7
5.2
45.8
564.6 98%
40.7
10.0
194.9 of
Population
17.1
sample
countries
as % of
regional
46.3
population
Population
4.6 of
71% 10.2
sample
countries
as % of
regional
13.8
population
6.2
71%
14.4
10.0
7.6
2.7
108.5
5.8
3.5
6.5
29.5
3.4
28.8
155.1 46%
84.5
6.1
32.4
21.6
10.5
1529.2 96%
164.4
1170.9
173.4
20.5
46%
(International Income Distribution Database)
LOW AND MIDDLE INCOME COUNTRIES
ALL COUNTRIES
Year
Income Group
East Asia and Pacific
Cambodia
2004
LIC
Year
Income
Group
Indonesia
2002
LMIC
East
Asia
and
Pacific
Mongolia
2002
LMIC
Cambodia
2004
LIC
Philippines
2006
LMIC
Indonesia
2002
LMIC
Thailand
2009
LMIC
Mongolia
2002
LMIC
Timor Leste
2001
LMIC
Philippines
2006
LMIC
Europe and Central Asia (not High Income)
Thailand
2009
LMIC
Albania
2005
UMIC
Timor
Leste
2001
LMIC
Belarus*
2005
UMIC
Europe
and
Central
Asia
(not
High
Income)
Bosnia & Herzegovina
2004
UMIC
Albania
2005
UMIC
Bulgaria
2008
UMIC
Belarus*
2005
UMIC
Georgia
2005
LMIC
Bosnia & Herzegovina
2004
UMIC
Kazakhstan*
2003
UMIC
Bulgaria
2008
UMIC
Lithuania
2008
UMIC
Georgia
2005
LMIC
Macedonia, FYR
2005
UMIC
Kazakhstan*
2003
UMIC
Moldova
2005
LMIC
Lithuania
2008
UMIC
Romania
2008
UMIC
Macedonia,
FYR
2005
UMIC
Russian Federation
2003
UMIC
Moldova
2005
LMIC
Tajikistan
2003
LIC
Romania
2008
UMIC
Turkey
2005
UMIC
Russian Federation
2003
UMIC
Turkmenistan
1998
LMIC
Tajikistan
2003
LIC
Ukraine
2005
LMIC
Turkey
2005
UMIC
Latin America and Caribbean
Turkmenistan
1998
LMIC
Argentina***
2006
UMIC
Ukraine
2005
LMIC
Bolivia
2005
LMIC
Latin America and Caribbean
No People’s Republic of China
UMIC
LMIC
UMIC
UMIC
2010
UMICPop
(millions)
UMIC
613.9
UMIC
2010
Pop
19.0
LMIC
(millions)
8.5
LMIC
613.9
20.0
LMIC
19.0
11.5
LIC
8.5
3.8
LMIC
20.0
21.6
UMIC
11.5
67.8
UMIC
3.8
85.0
LMIC
21.6
1.5
UMIC
67.8
1.8
LMIC
85.0
24.3
UMIC
1.5
40.9
UMIC
1.8
4.1
UMIC
24.3
14.9
40.9
1.3
LMIC
4.1
2.2
LMIC
14.9
15.9
LMIC
1.3
158.3
LMIC
2.2
12.9
LMIC
15.9
5.8
158.3
LIC1.2
12.9
45.0
LMIC
5.8
33.8
LMIC
1.2
12.9
LMIC
45.0
511.4
33.8
Ma
Na
Ni
Ni
Se
Sie
Sw
Ta
Ug
Za
HI
Au
Be
Ca
Cr
Cz
De
Es
Fin
Fra
Ge
Gr
Hu
Ire
Ita
La
Ne
No
Po
Po
Slo
Slo
Sp
Sw
Un
LO
AL
141.8
UMIC
2003
Russian Federation
7.1
LIC
2003
Tajikistan
75.7
UMIC
2005
Turkey
5.2
LMIC
1998
Turkmenistan
45.8
LMIC
2005
Ukraine
564.6 98%
Latin America and Caribbean
40.7
UMIC
2006
Argentina***
n of
10.0Population of
LMIC
2005
Bolivia
ountries Brazil
sample countries
194.9
UMIC
2008
2010 Pop as % of regional
gional
17.1
UMIC
2009
Chile
n
Year
Income Group (millions) population
46.3
UMIC
2000
Colombia
Sub-Saharan Africa
613.9 71%
4.6
UMIC
2006
Costa Rica
Angola
1999
LMIC
19.0
10.2
UMIC
2004
Dominican Republic
Burundi
1998
LIC
8.5
13.8
LMIC
2004
Ecuador
Cameroon*
2007
LMIC
20.0
6.2
LMIC
2005
El Salvador
Chad
2002
LIC
11.5
14.4
LMIC
2006
Guatemala
Congo, Republic of
2006
LMIC
3.8
10.0
LIC
2001
Haiti
Cote d'Ivoire*
2002
LMIC
21.6
7.6
LMIC
2003
Honduras
Congo, Democratic Republic
2005of
LIC
67.8
2.7
UMIC
2002
Jamaica
Ethiopia*
2004
LIC
85.0
108.5
UMIC
2008
Mexico
Gabon
2005
UMIC
1.5
5.8
LMIC
2005
Nicaragua*
Gambia, The
1998
LIC
1.8
3.5
UMIC
2003
Panama
Ghana
2005
LIC
24.3
6.5
LMIC
2006
Paraguay
Kenya
2005
LIC
40.9
29.5
UMIC
2002
Peru
Liberia
2007
LIC
4.1
3.4
UMIC
2006
Uruguay*
Malawi
2005
LIC
14.9
28.8
UMIC
2004
Venezuela, Rep. Bol.
Mauritius
2008
UMIC
1.3
155.1 46%
Middle East and North Africa
Namibia
1993
UMIC
2.2
84.5
LMIC
2005
Egypt
Niger*
2002
LIC
15.9
6.1
LMIC
2002
Jordan
Nigeria
2003
LMIC
158.3
32.4
LMIC
1998
Morocco
Senegal
2001
LMIC
12.9
21.6
LMIC
2004
Syrian Arab Rep*
Sierra Leone
2003
LIC
5.8
10.5
LMIC
2001
Tunisia
Swaziland
2000
LMIC
1.2
1529.2 96%
South Asia
Tanzania, United Republic
2006
of
LIC
45.0
164.4
LIC
2005
Bangladesh
Uganda
2005
LIC
33.8
1170.9
LMIC
2008
India**
Zambia
2003
LIC
12.9
173.4
LMIC
2008
Pakistan
HIGH INCOME COUNTRIES
511.4 46%
20.5
LMIC
2005
Sri Lanka**
Austria
2008
HIC
8.4
Belgium
2008
HIC
10.9
Data – I2D2 v2
2003
Nigeria
2001
Senegal
2003
Sierra Leone
2000
Swaziland
of
2006
Tanzania, United Republic
2005
Uganda
2003
Zambia
HIGH INCOME COUNTRIES
2008
Austria
2008
Belgium
2001
Canada
2004
Croatia
2008
Czech Republic
2007
Denmark
2008
Estonia
2007
Finland
2007
France
2007
Germany
2008
Greece
2007
Hungary
2008
Ireland
2008
Italy
2008
Latvia
2007
Netherlands
2007
Norway
2008
Poland
2008
Portugal
2007
Slovak Republic
2008
Slovenia
2008
Spain
2008
Sweden
2007
United Kingdom
LMIC
LMIC
LIC
LMIC
LIC
LIC
LIC
158.3
12.9
5.8
1.2
45.0
33.8
12.9
511.4
8.4
10.9
34.2
4.4
10.5
5.6
1.3
5.4
64.9
81.6
11.3
10.0
4.5
60.6
2.2
16.6
4.9
38.2
10.6
5.4
2.1
46.2
9.4
62.2
(International Income Distribution Database)
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
HIC
46%
No United States of America
LOW AND MIDDLE INCOME COUNTRIES
ALL COUNTRIES
3625.7
4137.1
63%
60%
Who are the self employed? (Overall)
•In Low Income and Lower Middle Income countries, less than half of workers are wage
and salary employees.
Over 70% of workers in LICs are own account workers or non-paid employees,
mostly in agriculture.
•As the GNI per capita increases, share of wage and salaried employees or employers
increases, percent of workers who are own account, non-paid or in agriculture falls.
Table Percent of workers in each employment category; by country, region and income group
NON-AGRICULTURE
Region and Income Level
AGRICULTURE
wage and salary
employee
non-paid
employee
employer
own account
All Countries (90)
45.2
2.6
2.1
14.4
35.8
Low and Middle Income Countries
(68)
37.9
3.0
1.8
15.7
41.7
Region (Low and Middle Income Countries)
East Asia and Pacific (6)
35.7
Europe and Central Asia (13)
74.3
59.2
Latin America and the Caribbean (18)
4.1
0.6
2.2
1.8
2.6
3.8
17.2
5.0
18.5
41.2
17.5
16.3
Middle East and North Africa (4)
South Asia (4)
Sub-Saharan Africa (21)
48.0
28.7
13.4
2.3
3.8
2.4
4.0
0.7
1.4
8.7
15.6
19.0
37.1
51.2
63.7
Per Capita GNI
Low Income (17)
Lower Middle Income (27)
Upper Middle Income (22)
High Income (24)
18.6
32.2
65.2
84.0
2.1
3.8
1.7
0.4
1.0
1.3
3.6
3.5
17.9
15.6
14.3
7.5
60.4
47.1
15.1
4.6
(number of countries in sample)
Who are the self employed? (Income level)
•As per capita GDP rises (to about 600-700 2005 US PPP dollars) workers transition out of non-paid
employment and own account in agriculture and into non-agricultural own account.
•As countries move from low to lower middle income (from about $600 to $1200), there is a shift into
wage and salaried work within both agriculture and non-agriculture.
•As middle income countries grow there is a structural transformation into non-agricultural wage and
salary employment, and to a lesser extent non-agricultural employer, and out of all types of agricultural
employment and non-agricultural own account.
80
100
Separating Agricultural workers into wage and salary, employer, own account and
non-paid
60
40
0
20
0
20
40
60
Percent of workers
80
100
Separating Non-agricultural workers into wage and salary, employer, own account and
non-paid
300
500
1000
2500
5000
10000
Per Capita GDP
Non-ag unpaid
Non-ag employer
All agricultural workers
25000
50000
Non-ag own account
Non-ag wage and salaried
300
1000
2000
5000
10000
Per Capita GDP
Ag unpaid
Ag employer
All non-agricultural workers
20000
50000
Ag own account
Ag wage and salaried
Who are the self employed? (Education)
•Most educated: Non-agricultural employers and non-agricultural wage and salaried employees
•Least educated: Agricultural workers.
•Intermediate: Non-agricultural own account workers and Non-agricultural non-paid employees.
•Similar patterns for countries in all regions and income groups.
•In particular, as per capita GNI increases employers do not become more educated
relative to the own account workers or wage and salaried employees
Non-agriculture
Wage and
Salaried
Worker
All Countries
Non-paid
Employees
Employer
Not
Employed
Own Account Agriculture
9.4
7.1
10.4
6.9
4.2
6.7
10.3
13.0
8.3
10.5
9.8
12.8
7.5
10.5
5.7
10.0
8.5
10.2
Latin America and Caribbean
9.8
8.5
10.4
7.7
4.8
7.7
Middle East and North Africa
South Asia
Sub-Saharan Africa
9.3
7.0
9.6
6.8
6.4
5.7
10.2
10.3
8.3
7.2
6.2
6.2
5.7
3.4
4.2
8.4
5.3
6.3
6.7
8.5
10.9
6.0
6.9
8.9
7.8
10.1
11.0
5.3
6.8
8.2
3.9
4.1
6.5
4.9
6.2
8.8
East Asia and Pacific
Europe and Central Asia
Low Income
Lower Middle Income
Upper Middle Income
Who are the self employed? (Gender)
•For countries in all regions and income groups,
•Women are more likely to be non-employed or agricultural non-paid employees,
•Men are more likely to be in any other employment category.
•Men are more likely than women to be employers or own account workers in all regions.
•In general, women are less likely to be in high quality employment categories than
are men.
•The biggest differences between men and women are in MENA and SA.
male
4
2 0
44
11
38
ECA
female 110
33
male
13
4
7
1
58
44
16
22
LAC
female
10
male
1 2
7
4
32
2
4
51
39
20
28
MENA
female
2 01
11
male
18
15
1 3
68
26
37
19
SA
female
2 02
male
5
19
13
72
2 2
29
34
20
EAP
female
10
1
4
17
male
12
1 1
female
13
1 2
20
13
49
45
28
SSA
0
5
40
20
40
40
60
80
percent
own_account
employer
non_paid_employee
wage_and_salary
agriculture
not_employed
100
Who are the self employed? (Age)
•Proportion of both men and women who are employers increases with age from 15
until about 45 years old, and then remains relatively constant (until around 65, when
the proportion of workers in all employment categories falls).
•Proportion of both men and women who are own account workers increases sharply
with age until the late 30s, levels off, and then begins to fall from 40 on.
•For men, the proportion working as non-paid employees is high for teenagers, then
falls sharply from after men reach 20 years old.
•For women, the proportion of working as non-paid employees is high for teenagers
and remains high until they are about 40 years old, after which it begins to fall slowly.
Female
0
0
.02
.05
.04
.1
.06
.15
.08
.2
.1
Male
20
40
Age Years
own_account
non_paid_employee
60
employer
20
40
Age Years
lown_account
non_paid_employee
60
employer
Who are the self employed? (Sector)
100
•In general, wage and salaried employees are much more likely to be in services than
any other industry sector. However, there are some exceptions:
•In EAP and SA, wage and salaried workers more likely in manufacturing than
services.
•In LMICs, wage and salaried workers more likely in manufacturing than services.
9
5
2
9
20
4
2
5
10
22
24
5
18
16
42
4
4
14
11
15
14
2
80
27
6
12
25
23
23
10
16
46
60
36
percent
44
46
71
6
10
65
37
45
46
59
31
40
61
40
3
2
20
13
10
20
6
25
17
4
41
12
39
6
22
21
15
17
29
31
2
24
20
7
11
30
24
17
12
12
11
15
15
0
20
12
2
1
4
18
4
5
11
11
8
21
5
12
11
26
39
45
28
22
12
8
55
41
56
16
16
11
10
48
47
22
6
22
2
10
46
14
21
23
8
12
12
EAP ECA
LAC MENA SA
Wage and Salary
SSA
EAP ECA
LAC MENA SA
SSA
Non-Paid Employee
EAP ECA
LAC MENA SA
Employer
manufacturing
construction
retail
services
other
SSA
EAP ECA
LAC MENA SA
Own Account
SSA
Ranking from richest to poorest:
•Non-agricultural employers
•Wage and salary workers
•Own-Account and Unpaid workers
•Not Employed
•Agricultural workers
100
All Low and Middle Income Countries
80
17
42
37
32
38
64
60
35
40
33
33
34
36
49
25
20
25
35
28
27
12
0
percent
Who are the self employed? (Consumption)
Wage and Salary
Non-Paid Employee
Employer
tercile1
tercile3
Own Account
Agriculture
tercile2
Not Employed
“Successful” self employment
 Definition 1: Employer
 More robust
 Small cell sizes for “success”
Region and Income Level
(number of countries in sample)
All Countries (89)
Low and Middle Income Countries
(66)
Region (Low and Middle Income Countries)
East Asia and Pacific (6)
Europe and Central Asia (13)
Latin America and the Caribbean (17)
Middle East and North Africa (4)
South Asia (4)
Sub-Saharan Africa (21)
Per Capita GNI
Low Income (19)
Lower Middle Income (27)
Upper Middle Income (22)
High Income (24)
NON-AGRICULTURE
Successful
Unsuccessful
2.1
14.4
AGRICULTURE
Successful
Unsuccessful
0.8
15.4
1.8
15.7
0.9
18.2
1.8
2.6
17.2
5.0
1.5
0.3
18.5
4.7
3.8
18.5
1.2
7.3
4.0
0.7
1.4
8.7
15.6
19.0
5.8
0.5
1.0
10.2
17.8
37.1
1.0
1.3
3.6
3.5
17.9
15.6
14.3
7.5
0.6
1.1
0.8
0.2
33.7
17.6
5.4
1.8
“Successful” self employment
 Definition 2: Out of poverty ($2 / day consumption)
 Less clean
 Larger cell sizes for “success”
Region and Income Level
(number of countries in sample)
NON-AGRICULTURE
AGRICULTURE
Successful
Unsuccessful
Successful
Unsuccessful
7.7
9.3
4.3
14.1
Region
East Asia and Pacific (6)
Europe and Central Asia (7)
10.3
4.6
8.7
0.3
6.1
2.0
13.9
0.8
Latin America and the Caribbean (10)
Middle East and North Africa (3)
South Asia (2)
Sub-Saharan Africa (17)
19.0
10.0
5.1
5.2
2.9
2.4
10.8
18.3
4.3
11.9
3.4
4.9
3.6
4.9
15.1
31.1
Per Capita GNI
Low Income (13)
Lower Middle Income (20)
Upper Middle Income (12)
5.7
6.8
13.2
15.0
9.9
1.7
4.9
4.4
3.2
25.3
14.6
1.9
All countries (45)
“Successful” self employment (Methodology)
 Probit estimation
 Models include gender, education dummies and gender/age
interactions
 Mean pseudo R-square for these Probits is 0.0834 for definition
1, and 0.1231 for definition 2
 Models are run country by country
 Robustness checks:
 Control for majority social group
 With and without Sector and Urban/Rural
“Successful” self employment (Results)
 The probability of being an employer is higher in urban areas than rural areas.
 In general, among industry sectors the probability of being successful is lowest in
manufacturing.
 Males are more likely to be successful
 The probability of being successful increases with education
 For both men women:
 Probability of being an employer increases with age from 15 to 49 (and then remains about
the same, or falls, for the 50-65 year old group).
 Probability of being non-poor increases with age, except in low income countries, where
the probability of being successful is highest for those between 25 and 49 years old.
“Successful” self employment (Marginal effects)
Table: Marginal effects of each explanatory variable on the probability that an unsuccessful self employed worker
could be a successful self employed worker; mean by region and income group
DEFINITION 1: unsuccessful=own account
Definition 1: Employer
rural
construct.
retail
services male
no
secondary secondary
post
education incomplete complete secondary
Male
15_24
Male
40_49
Male
50_65
Female
15_24
Female
40_49
Female
50_65
Region
East Asia and Pacific
-0.02
0.11
Europe and Central Asia -0.08
-0.05
Latin America and the Caribbean
-0.03
0.01
Middle East and
-0.10
0.04
South Asia
-0.03
0.02
Sub-Saharan Africa
0.00
-0.02
-0.03
-0.01
0.02
-0.06
-0.01
-0.05
0.00
-0.02
-0.03
-0.03
-0.01
0.01
0.05
0.15
0.10
0.16
0.05
0.03
-0.08
-0.25
-0.08
-0.11
-0.02
-0.02
0.06
-0.02
0.08
0.01
0.03
0.02
0.07
0.10
0.13
0.03
0.04
0.05
0.14
0.23
0.21
0.25
0.05
0.11
-0.04
-0.12
-0.11
-0.15
-0.03
-0.03
0.03
0.06
0.02
0.07
0.01
0.02
0.03
0.06
0.00
0.11
0.01
0.02
-0.03
-0.08
-0.09
-0.08
-0.04
-0.02
0.02
0.07
0.03
0.05
0.02
0.00
0.03
0.10
0.03
0.03
0.04
0.01
Per Capita GNI
Low Income
Lower Middle Income
Upper Middle Income
-0.02
-0.03
0.02
0.02
-0.01
-0.03
0.03
0.05
0.11
-0.01
-0.04
-0.10
0.01
0.04
0.08
0.03
0.06
0.13
0.07
0.10
0.21
-0.03
-0.04
-0.12
0.02
0.02
0.02
0.01
0.02
0.01
-0.02
-0.04
-0.09
0.00
0.02
0.04
0.00
0.03
0.03
Male
15_24
Male
40_49
Male
50_65
Female
15_24
Female
40_49
Female
50_65
-0.01
-0.03
-0.04
0.01
0.04
0.01
Table: Marginal effects of each explanatory variable on the probability that an unsuccessful self employed worker
could be a successful self employed worker; mean by region and income group
DEFINITION 2: unsuccessful=below $2/day
Definition 2: $2/day consumption
rural
construct.
retail
services male
no
secondary secondary
post
education incomplete complete secondary
Region
East Asia and Pacific
-0.20
0.01
Europe and Central Asia -0.03
-0.26
Latin America and the Caribbean
-0.11
-0.01
Middle East and
-0.11
0.03
South Asia
-0.21
0.05
Sub-Saharan Africa
-0.01
0.04
0.05
-0.07
0.02
-0.02
0.03
0.03
0.10
-0.01
-0.01
-0.02
0.07
-0.01
0.01
-0.02
0.01
0.03
0.02
0.06
-0.11
0.00
-0.09
-0.17
-0.06
-0.04
0.18
0.03
0.10
0.09
0.12
0.03
0.21
0.10
0.19
0.01
0.20
0.07
0.40
0.19
0.27
0.18
0.25
0.11
-0.04
0.02
-0.01
-0.10
-0.01
-0.04
0.05
0.04
0.04
-0.05
0.04
-0.07
0.10
-0.04
0.09
0.03
0.06
-0.04
-0.06
-0.05
-0.02
-0.08
-0.03
-0.01
0.07
0.07
0.06
0.09
0.10
-0.01
0.12
0.03
0.12
0.11
0.11
0.01
Per Capita GNI
Low Income
Lower Middle Income
Upper Middle Income
0.03
0.03
0.01
0.03
0.06
0.00
0.07
0.02
0.02
0.00
-0.08
-0.09
0.07
0.13
0.10
0.12
0.19
0.19
0.22
0.26
0.26
-0.04
-0.02
-0.01
-0.03
0.03
0.05
-0.02
0.06
0.09
-0.03
-0.04
-0.01
-0.01
0.09
0.05
-0.01
0.10
0.11
-0.07
-0.19
-0.11
0.07
0.03
-0.01
Unsuccessful self employed with
potential for success (Definition)
 Using estimated probability of success for each country self employed
individual (Grimm, Knorringa and Lay, 2012):
 Calculate mean probability of success among the successful self employed
 Determine a threshold such that the mean probability of success for all
individuals with a predicted probability of success above the threshold
among the “unsuccessful” is the same as the mean predicted probability for
the “successful”
 Requires “common support” for the predicted probability distributions
 Thresholds are country specific
 Define “potentially successful” as those individuals with a predicted
probability of success above the threshold
Unsuccessful self employed with
potential for success (Results)

On average, in Low and Middle Income Countries 36-37% of the non-agricultural own account workers have a high potential to
become successful.

Share of potential employers increases with GNI per capita, but no such tendency with second definition

By region:

High share of “constrained gazelles” in Europe and Central Asia by both definitions

Proportion of self-employed with potential to pull their households out of poverty is much lower in South Asia (only India and Bangladesh, however)
than any other region.

Sub-Saharan Africa has few self-employed with potential to be employers who are not
Definition 1 (Employer)
36%
Definition 2 ($2/day)
37%
Region (Low and Middle Income)
East Asia and Pacific (6, 6)
Europe and Central Asia (6, 2)
Latin America and the Caribbean (15, 10)
Middle East and North Africa (4, 3)
South Asia (3, 2)
Sub-Saharan Africa (16, 15)
34%
55%
40%
41%
36%
27%
43%
63%
47%
50%
29%
52%
Per Capita GNI
Low Income (15, 12)
Lower Middle Income (21, 17)
Upper Middle Income (14, 9)
High Income (23, 0)
34%
34%
42%
72%
42%
35%
47%
All Low & Middle Income Countries (50, 38)
Conclusions
 Successful self-employed (and those with a high potential to be successful) are more educated, older,
more likely to be a household head and less likely to be in agriculture.
 At all levels of development, most self employed workers are unsuccessful.
 Approximately 36% of unsuccessful self-employed have characteristics similar to successful self-
employed
 As per capita income increases:
 Proportion of workers who are unsuccessful self employed falls
 Most of the unsuccessful self employed are absorbed into wage and salary work
 A small minority become successful entrepreneurs.
 Household consumption is correlated with employment status
 Employer households are wealthiest
 Wage and salary worker households better off than own account or unpaid worker households
 Agricultural worker households are the poorest
Conclusions
 In the context of the constrained occupational choice model:
 The characteristics associated with (required by?) wage employment change with level
of development
 Employment opportunities in the wage and salary sector become increasingly
prevalent as countries grow, but self employment is quantitatively important in the
earlier stages of development
 As constraints to entering wage employment fall, people who were previously
constrained to go to self-employment (and are not likely to be successful) opt out of
self employment
 Constraints to success seem present in all regions and income levels
 Vary across regions, and across countries within region
 Further work is needed to identify which constraints are most relevant in each context
 Suggests an agenda for policy intervention that needs to be tailored to country specificities and
populations within countries

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