Entrepreneurship training and self-employment among university graduates: Evidence from a randomized trial in Tunisia Patrick Premand (World Bank) Stefanie Brodmann (World Bank) Rita Almeida (World Bank and IZA) Rebekka Grun (World Bank) Mahdi Barouni (CNSS) IZA/World Bank/OECD Conference on Activation and Employment Policies Istanbul, May 1, 2012
High youth unemployment among graduates Figure 1: High unemployment among graduates (Unemployment rate, by level of education and age group) 50,0 45,0 44,2 44,3 40,0 38,2 35,0 33,6 30,0 25,0 20,0 18,7 Tertiary, 15-29 All, 15-64 15,0 13,2 13,5 13,3 10,0 5,0 0,0 Source: Tunisia Labor Force Surveys 2005 2009 2010 2011 2
No good jobs available Figure 2: Lack of good jobs main obstacle to get a job (What is the primary obstacle in (country for youth to get a job or a better job that enables them to start a family?) Tunisia Egypt Syria Lebanon Palestine Jordan UAE Yemen Bahrain Kuwait Algeria Saudi Arabia Iraq Qatar Libya Djibouti Morocco 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% No good jobs available Jobs given only to connected people Lack training Other Source: Gallup opinion poll 3
Intervention: The entrepreneurship track Objective: Increase self-employment among graduates, by improving skills and affecting attitudes towards entrepreneurship National reform during 09-10 academic year (inter-ministerial committee: Min of Vocational Training & Employment; Industry; Education & Higher Education) Entrepreneurship track for third year university students in applied programs Business training: Entrepreneurship courses offered by the public employment office (20 days/full time, small groups) Practical research on the ground and interactive sessions, aimed at fostering participants : (i) behavioral skills; (ii) business skills; and (iii) networking skills Initial business idea: modified after evaluation by bankers and experts Personalized coaching: Private sector entrepreneurs or specialized coaches (8 sessions, either individually or in small groups) University professors: Supervision in development and finalization of the business plan Graduation and possibility to enter into business plan thesis competition 4
Questions & key findings Questions of interest: What are the impacts on labor market outcomes? What are the channels behind the employment results? Key findings: The entrepreneurship track was effective in increasing selfemployment; However, the overall employment rate among beneficiaries remained the same as for the control group; The program fostered business skills, expanded networks, and affected a range of behavioral skills; Participation also heightened graduates sense of opportunities and optimism towards the future; 5
Evaluation design, data & empirical strategy 6
Impact Evaluation Design Beginning of the 2009/10 academic year: All students enrolled in the third year of their licence appliquée invited to apply for the program at the 1,702 students apply (out of 18,000), 1506 projects Given over-subscription of interested students no resources to reach all interested students Half of the students randomly assigned to entrepreneurship track, other half assigned to standard curriculum Stratification by gender and study subject (14 licences ) 757 projects assigned to treatment group; 742 to control group Randomization achieved good balance Few systematic differences; differences quantitatively small
Data Baseline Application Survey (online and paper, December 2009) Baseline Entrepreneurship Survey (phone, January February 2010) Capture broader range of characteristics, particularly on personal traits, preferences, attitudes towards entrepreneurship, 90% re-contact rate Qualitative work (October - November 2010) To finalize content of follow-up survey instrument and provide feedback on program implementation Follow-up survey (face-to-face; April-June 2011) 93% re-contact rate (uncorrelated with treatments status) 1-year after graduation First labor-market survey after the revolution; only panel survey tracking the cohort of 2009-2010 graduates.
Intent-to-Treat Estimates (ITT) Impact of offering business training and coaching: Y i = βt i + γx i + π is + ε i With: Y i = employment outcomes T i = randomized assignment to entrepreneurship track X i = baseline controls π is = strata fixed effects (by gender and subject) Standard errors clustered by strata Robustness checks: Different sets of baseline controls Standard errors clustered by governorate 9
Treatment on the treated Estimates (TOT) Impact of actually completing entrepreneurship training and coaching: IV estimation: (1 st Stage) U i = βt i +γx i + π is + η i With: U = Actual program take-up (from administrative data) (2 nd Stage) Y i = фû i +ξx i + π is + ε i With: Û = Predicted Program take-up (from (1)) Actual take-up considered as completing training and coaching (59%) Local-average treatment effects (LATE) to be interpreted as impact on compliers (those who complete the training if offered, and do not complete if not offered) In practice, take-up among control very low (3.4%) 10
Results 11
Results : Outline What are the impacts on labor-market outcomes? Self-Employment Employment Quality of Employment What are the channels behind the employment results? Business skills Networks Preferences Behavioral Skills (Entrepreneurial Skills, Big 5, ) Attitudes towards the future and opportunities Access to credit 12
Results: Labor-Market Outcomes 13
Labor-market Outcomes: Self-Employment Mean C Mean T ITT SE TOT SE Self-employed (last 12 months) Self-employed, including seasonal (last 7 days) Self-employed, excluding seasonal (last 7 days) 0.05 0.09 0.04*** 0.01 0.07*** 0.02 0.04 0.08 0.03** 0.01 0.05** 0.02 0.03 0.04 0.01* 0.01 0.02* 0.01 Note: n = 1580. The intervention led to an increase in self-employment Small absolute effects Effect sizes ranging between 48%-81% for ITT 14
Labor-market Outcomes: Employment Mean C Mean T No evidence that the program significantly affected overall employment (note: general equilibrium effects not captured) ITT SE TOT Employed (last 7 days) 0.28 0.29-0.00 0.02-0.00 0.04 Self-employed (last 7 days) 0.04 0.08 0.03** 0.01 0.05** 0.02 Salaried worker (last 7 days) 0.21 0.18-0.03 0.02-0.05 0.03 Unemployed (last 7 days ) 0.48 0.49 0.01 0.03 0.01 0.05 Studying (last 7 days) 0.19 0.18-0.00 0.02-0.01 0.03 Inactive (last 7 days) 0.03 0.03 0.01 0.01 0.01 0.01 Suggests substitution between employment and self-employment (as in Fairlie et al. (2012) in the US) SE 15
Labor-market Outcomes: Quality of Employment Mean Mean ITT SE TOT SE C T Monthly labor earnings 74.79 88.97 17.51 33.86 29.80 56.38 Reservation wage (private sector) 473.50 491.20 17.13* 8.73 28.85** 14.68 Reservation wage (public sector) 487.86 491.45 4.15 7.30 6.99 12.00 Has contract 0.12 0.10-0.02 0.02-0.03 0.03 Covered by Social Security 0.05 0.06 0.01 0.01 0.01 0.02 Work in large firm 0.07 0.07 0.00 0.01 0.00 0.02 Hours worked in last week 8.55 9.35 0.66 0.98 1.12 1.64 N= 1580 No evidence of impacts on earnings Increase in reservation wage for private sector wage jobs (but not public sector wage jobs) No effects on other measures of quality of employment 16
Results: Channels 17
Channels: What is behind these employment results? Channels Business skills +++ Networks ++ Preferences Behavioral skills: Big Five ++ Behavioral skills: Entrepreneurial skills Attitudes towards the future +++ Access to credit + 18
Channels: Behavioral skills (Big Five Personality traits) Measures of Behavioral Skills (10-item Big Five Scale from Gosling, 2003) Suggests the intervention affected a range of behavioral skills (personality traits) Consistent with Cobb-Clark and Tan (2010): agreeableness negatively associated with probability of being a manager or business professional Trade-off in soft-skills for wage employment and self-employment? 19
Channels: Attitudes towards the future Subjective measures of optimism and attitudes towards the future (inspired by de Mel et al. (2010) and positive items from a depression scale) Suggests beneficiaries have higher optimism and more positive attitudes towards the future 20
Channels: Access to credit? Entrepreneurship track did not directly aim to alleviate credit constraints (clients main hypothesis was that skills are the constraint, not credit) Training involved providing information to students about credit applications, as well as connecting them to bankers Mean Mean N ITT SE TOT C T Knows how to apply for credit 1,580 0.20 0.22 0.02 0.02 0.03 0.03 Expect to be able to obtain credit 1,568 0.30 0.39 0.08** 0.04 0.14** 0.06 Has applied for credit ( business idea) 674 0.04 0.08 0.04** 0.02 0.06** 0.02 SE Treatment group more confident to be able to obtain credit and more likely to have actually applied for credit (conditional on business idea) However, not more likely to report knowing how to apply for credit Many applications remain pending, too few observations to identify impact on access to credit at follow-up 21
Credit as the main perceived constraint to self-employment Personality traits Lack of follow-up Lack of technical skills Lack of ideas Lack of business skills Lack of experience Lack of opportunities Lack of finance 0% 10% 20% 30% 40% 50% 60% 70% 80% Women Men More than 70% of graduates state that access to credit is the main constraint for entry into self-employment. 22
Conclusions 23
Conclusions Diagnostics: Insufficient labor demand / high youth UE among graduates How To: Operations manual; joint / short / French MFPE/WB report Design of entrepreneurship tack, who does what, lessons from implementation Impact: Entrepreneurship track led to higher self-employment Employment rate among beneficiaries remained unchanged Affected a range of behavioral skills Costs:? Scalability: Confirms (at least some) non-cognitive skills are malleable highlights potential trade-offs between skills for self-employment and for wage empl.? Scaled up and expanded to engineering and masters program Despite large effect size, not a mass effective channel given low base Can skills create jobs? Intervention did not alleviate capital constraint for most (consider accompanying measures (i.e., credit, incubation focus on women?) Ensure quality service delivery (in particular staffing at public employment office and external coaches) 24
Thank you 25
Contribution to the broader evidence base A unique randomized impact evaluation in the context of a national higher education reform, providing skills training to the more educated while still at university Effectiveness of policies to foster employability and productivity among youth in developing countries [Almeida et al., 2011a; Angel-Urdinola et al., 2010; Betcherman et al., 2004, 2007; and Kluve et al., 2010 for recent reviews] Focus mostly on Latin American programs and on vocational training programs for atrisk youth [e.g., Ibararran and Rosas, 2008; Attanasio et al., 2011; Card et al., 2011] Effectiveness of entrepreneurship-support interventions in developing countries Focus mostly on activation of existing low productivity workers, the inactive, or the unemployed [e.g., Almeida and Galasso, 2010; De Mel et al., 2010; Klinger and Schündeln, 2011] Effectiveness of business training for micro finance clients, mainly women [e.g., Karlan and Valdivia, 2011; Drexler et al., 2010; Bruhn and Zia, 2011] Profiles of successful entrepreneurs [Elston et al., 2005; Djankov et al., 2006; de Mel et al., 2010] Effects of training programs on behaviors and attitudes [e.g., Carneiro et al. 2010; Blattman, Fiala and Martinez, 2011; Blattman and Annan, forthcoming] 26
Randomization achieved balance N Mean Control Treatment Difference StEr Application form Male 1,702 0.34 0.34 0.33-0.01 0.00 Age 1,700 23.02 22.97 23.08 0.11* 0.06 Average grade in 2nd year of university 1,679 11.48 11.46 11.51 0.05 0.07 Took entrepreneurship course 1,702 0.75 0.74 0.76 0.02 0.02 Ever worked 1,702 0.71 0.70 0.72 0.02 0.02 Age at first job 1,189 17.31 17.44 17.18-0.27 0.16 Duration of first job (months) 1,181 6.44 6.31 6.57 0.26 0.84 Household size 1,700 6.47 6.46 6.48 0.03 0.09 Father is salaried worker 1,702 0.35 0.37 0.34-0.03 0.02 Father is self-employed 1,702 0.28 0.28 0.28 0.00 0.02 Mother is salaried worker 1,702 0.09 0.09 0.09 0.00 0.01 Mother is self-employed 1,702 0.08 0.07 0.08 0.01 0.01 HH earnings between 0 and 300 TND 1,702 0.25 0.24 0.25 0.01 0.02 HH earnings between 301 and 500 TND 1,702 0.30 0.30 0.29-0.01 0.02 HH earnings between 501 and 800 TND 1,702 0.21 0.22 0.20-0.02 0.01 Family can provide financial support 1,702 0.63 0.64 0.62-0.02 0.02
Channels: Business skills Measures of self-reported business skills related to the core content of the training and business plan (BP): Mean Mean ITT SE TOT SE C T Has experience in projects 0.37 0.48 0.10*** 0.02 0.17*** 0.04 Knows how to produce a BP 0.45 0.77 0.31*** 0.03 0.53*** 0.05 Knows BP contains commercial analysis 0.23 0.41 0.18*** 0.03 0.30*** 0.05 Knows BP contains demand assessment 0.30 0.55 0.24*** 0.03 0.40*** 0.04 Knows BP contains supply assessment 0.33 0.62 0.28*** 0.03 0.47*** 0.05 Knows BP contains marketing plan 0.26 0.55 0.28*** 0.04 0.48*** 0.05 Knows BP contains market share analysis 0.20 0.40 0.20*** 0.03 0.34*** 0.04 Knows BP contains technical analysis 0.24 0.57 0.32*** 0.03 0.55*** 0.04 Knows BP contains financial analysis 0.35 0.64 0.28*** 0.03 0.48*** 0.05 Knows BP contains profitability analysis 0.27 0.47 0.19*** 0.04 0.32*** 0.06 N=1580 Unsurprisingly, significantly better knowledge about topics taught in entrepreneurship track 28
Channels: Networks Mean Mean N ITT SE TOT SE C T Registered at Employment Office 1,702 0.78 0.82 0.04 0.02 0.07* 0.04 Knows an employment agent 1,580 0.14 0.28 0.13*** 0.02 0.22*** 0.03 # spoke to employment agent (in month) 329 2.26 1.83-0.31 0.39-0.42 0.47 Knows an entrepreneur 1,580 0.44 0.49 0.05* 0.02 0.08* 0.04 # spoke to entrepreneur (in month) 726 5.05 5.11-0.01 0.65-0.01 0.98 Knows a banker 1,580 0.25 0.31 0.06*** 0.02 0.09*** 0.03 # spoke to a banker (in month) 440 2.44 3.67 1.16** 0.53 2.00** 0.88 Would seek advice from professor 1,580 0.08 0.05-0.03* 0.01-0.04** 0.02 Would seek advice from employment agent 1,580 0.32 0.31-0.00 0.02-0.01 0.03 Would seek advice from an entrepreneur 1,580 0.48 0.51 0.03 0.02 0.05 0.04 Entrepreneurship training expanded participants business and employment networks 29
Channels: Preferences Self-reported preference parameters often associated with entrepreneurs: Mean C Mean T ITT SE TOT SE Willingness to take risk (0-10) 6.06 6.10-0.02 0.14-0.03 0.24 Certainty equivalent for lottery with 50% chance of winning 0 and 50% chance of winning 2000DT Risk taker (Certainty Equivalent>1000DT) Patience (prefers 1000 DT in 6 months to 800DT now) 674.44 694.33 16.21 19.53 27.43 31.83 0.18 0.18-0.01 0.02-0.01 0.03 0.27 0.29 0.02 0.02 0.03 0.04 N = 1427; controls include behavioral measures from baseline phone survey. No evidence that entrepreneurship training affected time or risk preference 30
Channels: Behavioral Skills (Entrepreneurial skills) Measures of entrepreneurial skills (as in de Mel et al., 2010) Mean Mean ITT SE TOT SE C T Impulsiveness 0.00-0.12-0.12** 0.05-0.21** 0.09 Passion for work 0.00 0.03 0.03 0.05 0.06 0.09 Tenacity -0.00 0.03 0.04 0.05 0.07 0.08 Polychronicity -0.00-0.05-0.05 0.05-0.08 0.08 Locus of control -0.00 0.02 0.02 0.06 0.03 0.10 Achievement -0.00 0.02 0.04 0.06 0.06 0.10 Power Motivation 0.00-0.05-0.04 0.05-0.07 0.09 Centrality of work -0.00 0.09 0.10* 0.05 0.16* 0.09 Personal organization -0.00 0.08 0.08 0.07 0.14 0.11 N = 1427; controls include behavioral measures from baseline phone survey. Some evidence of changes in entrepreneurial skills such as impulsiveness and centrality of work. 31
Channels: Opportunities and the revolution Perceptions of the effects of the revolution on labor-market (from 1 = very negatively, to 5 = very positively): Mean C Mean T ITT SE TOT Revolution affected desire to find a job 3.64 3.66 0.02 0.05 0.04 0.08 SE Revolution affected desire to work in public sector Revolution affected desire to work in private sector Revolution affected desire to work on a project 3.70 3.66-0.04 0.06-0.07 0.10 3.18 3.22 0.04 0.05 0.07 0.09 3.34 3.28-0.06 0.05-0.10 0.09 Revolution affected desire to emigrate 2.65 2.52-0.12 0.07-0.20* 0.12 Overall, heightened sense of opportunities because of the revolution (higher desire to find a job, lower desire to emigrate) Particularly so for beneficiaries? 32