Who are the Self-Employed in the Developing World?
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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
