Getting Unemployed Youth into. experiments in middle income countries

Transcription

1 Getting Unemployed Youth into Jobs: Lessons for New Zealand from experiments in middle income countries DavidMcKenzie McKenzie, World Bank

2 The problem

3 30 The Problem: Unemployment Rates Around the World in Youth Adult 5 0 Source ILO Global Employment Trends 2012

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5 Why might youth have such trouble finding employment? Lack of work experience and untested so employers find it difficult to assess quality. Lack of soft skills employers complain graduates lack key soft skills like how to work well in teams, dress and behave in professional manner, etc. Skills mismatch may have dropped out of school, or trained in areas with low labor demand

6 Policy response Whole range of different active labor market policies designed to try and help youth find jobs Training programs Employment centres Internship/Job experience programs Hiringsubsidies subsidies, etc. (and of course real solution may lie in policies to stimulate lb labor demand d private sector development policies).

7 But do any of these work? Consider a training program run by a Government for unemployed youth. The program notes that 50% of all people trained were employed a year later. Is this good or bad?

8 The problem of knowing whether our programs worked? The revealed ldpreference approach: youth are choosing to take these programs, they tell us afterwards they thought they were good so they must be But might just reflect low opportunity cost of time/desperation. The before after approach: none of them were employed before, 50% are afterwards, so program is big success. But maybe they would have found jobs anyway The difference in differences approach: compare them to unemployed youth who didn t go through the program: Suppose we find only 30% of those who didn t go through program are employed afterwards, vs 50% for those trained This might just reflect that more motivated people are more likely to take the course, and also to find jobs afterwards.

9 Randomized experiments Basic idea: take 1000 unemployed Use a random number generator to randomly choose 500 of them to be the Treatment group (offered training) The other 500 are the control group (not offered training) Two groups should be comparable, with only difference due to chance So comparing outcomes should enable us to see what would have happened.

10 Illustration 1: Jordan At the time of graduation, 93% of female community college graduates in Jordan say they want to work But 16 months later, only 23% are employed Request to try out different policies to help them find jobs. Jordan NOW (New Opportunities for Women) Jordan NOW (New Opportunities for Women) pilot program.

11 Obtaining the Experimental Sample 8 main public community colleges Baseline surveys taken in July 2010 of all second year students inthese colleges, givingdata on1755female students, before students had taken their final examinations. In August 2010 this was then merged with administrative data on examination results gave 1395 who had passed Randomly selected 1350 of these to be experimental sample

12 Who are these graduates? Typical age % married at baseline; only 16% ever 13% married at baseline; only 16% ever worked

13 The Interventions Wage Subsidy Graduate given a job voucher they could take to firm when lookingfor work Voucher would pay the firm 150 JD ($225) per month for up to 6 months if they hired worker (= minimum wage) Firm hdt had to be legally ll registered, it dhave a bank account, and give job offer in writing Monthly monitoring to ensure worker still employed. If worker leaves firm before 6 months up, they take the voucher with them can apply remaining months at another firm. Valid for max of 6 months in 9 month window (Oct 2010 Aug 2011).

14 Why might wage subsidies work? short term subsidies bidi may have long term effects by raising the productivity of youth through work (Bell et al., 1999 may encourage employers to take a chance on hiring inexperienced, untested workers (World Bank, 2006). May provide youth with the crucial experience needed to find other jobs Might give youth confidence to approach employers (Galasso et al, 2004).

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16 Employability skills training Training course of 45 hours (5 hours/day for 9 days) on key soft skills employers want graduates to have Provided by BDC, local NGO with widespread local name recognition and good reputation for skills training. covered effective communication and business writing skills (e.g. making a presentation, writing business reports, different types of correspondence), team building andteam work skills (e.g. characteristics of a successful team, how to work in different roles within a team), time management, positive thinking and how to use this in business situations, excellence in providing customer service, and C.V. and interviewing skills. Sessions were based on active participation and cooperative learning rather than lectures, with games, visual learning experiences, group exercises, and active demonstrations used to teach and illustrate concepts

17 Why might this work? Growing evidence that non cognitive or soft skills are important for employment and a range of other life outcomes (e.g. Bowles et al, 2001; Heckman et al., 2006). May enhance employment prospects by giving youth better skills and confidence for looking for jobs and by making them more productive in their first months in the job by reducing the amount of time firms need to spend training them on the basics of working in a business environment.

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19 Experimental Design 1350 students randomly allocated into one of four groups: 450 into a Control group 300 offered just the wage subsidy 300 offered just the soft skills training 300 offered both the wage subsidy and soft skills training.

20 Isn t this unfair? Gut reaction of some people to randomization is that it is unfair that we are giving a program to some people and not others. But Funding and training capacity limited we did not have funds to give to everyone so this way everyone gets the same chance of being chosen. Funding has an opportunity cost before spending lots of public money on such a program, want to know whether or not it actually works it is unfair to taxpayers to spend lots of their money on something that doesn t work.

21 Randomization ensures similar looking groups Table 2. Comparison of Means of Baseline Characteristics by Treatment Group Voucher Training Voucher & Control Only Only Training Group Stratifying Variables In Amman, Salt, or Zarwa Tawjihi score above median Low desire to work full time Is allowed to travel to the market alone Other Baseline Variables Age Married Mother Currently Works Father Currently Works Has Previously Worked kd Has a Job Set Up for After Graduation Has Taken Specialized English Training Household Owns Car Household Owns Computer Household Has Internet Prefers Government Work to Private Sector Sample Size Note: The only statistically significant difference across groups is internet access which is significant at the 10% level.

22 Timeline Baseline July 2010 Graduation August 2010 Soft skills training: Sept Nov 2010 Voucher period: Oct 2010 Aug 2011 Midline survey: April 2011 Endline survey: December 2011

23 Proportion of Female Graduates Employed in April 2011 (while voucher is still active) Voucher Training Both Control

24 0.60 Proportion of Female Graduates Employed in December 2011 (threemonthsafter allvouchers ended) Voucher Training Both Control

25 Proportion Employed in April vs. December Voucher Training Both Control 0.10

26 Modest benefits Voucher did increase lb labor market experience (by about 2 months), and labor force participation rates (by about t10% at endline), but thd had no lasting impacts on employment over period we looked at. Soft skills did improve mental health/subjective wellbeing, even if no employment effect Raises two key questions: Why not? Is this a surprising result?

27 Why not more impact? Some of the young women would have found jobs anyway so subsidies for them at most speed up this process. Main reason firms give for firing workers is that they aren t productive enough high minimum wage means these workers don t get employed. Firms that hired young women were from sectors that already typically do so didn t succeed in breaking down stereotypes/gender segregation, so little learning by firms.

28 Is this a surprising result? Expectations elicitation exercise While presenting these results at World Bank, InterAmerican Development Bank, University of Virginia, Paris School of Economics, and in Jordan, solicited expectations about impacts. Alsodid this through World Bank s Development Also did this through World Bank s Development Impact blog.

29 Midline Voucher Freque ncy More Expected ITT of Voucher Midline Training Frequency More Expected ITT of Training

30 Endline Voucher Expected ITT of Voucher Endline Training Frequency Frequency More Expected ITT of Training

31 Example 2: Turkey Turkish hemployment Agency (ISKUR) s main active labor market policy for the unemployed Vocational ltraining i courses Rapid expansion of courses from 25,000 people taking them in 2008, to 200, in ISKUR contracts with private and public providers to provide training courses in a range of occupations. Courses free to participants + they get small stipend ISKUR wants to know do these work in getting people employed?

32 Details Individuals id only allowed to take one course in a 5 year period Courses are frequently over subscribed (many more people p apply for them than the courses can take) Thisoversubscription provides a goodbasis for randomized evaluation just randomly choose who gets in the course from among all the qualified individuals who apply.

33 Design features Evaluation sample of 5,700 individuals applying for 130 courses in 23 provinces Training courses began Oct Dec Median course is 320 hours in length

34 The Sample: Oversubscribed but Diverse Training i Courses Computer /Computer programming Accounting professionalist/computerized Accounting Babysitter Cashier Foreign Trade and Customs Professional Fitter(natural gas)/plumbery Old and Sick People Nurse 4 Welder, Gas Arc Retailing and Merchandising/Salesperson 5 Cook Weaver, carpet ehram 7 Modelist/Stilist Coiffeur and Hair Hi care/skin care and beauty Operators (forklift/sewing machine) Medical Secretary Human resources Management 6 Manufacturer, furniture Applied Basic Electronics/Electronic technicians 9 6 Finalcut Waiter, service Moulder, grouting Mechanic, maintenance

35 83% of participants think course will raise their probability of employment Expected increase in probability of employement from course Density Expected Change in prob. employed

36 But 1 year after courses ended Treatment Control Employed Formally Employed

37 Modest impact Training i increases likelihood lih of bi being employed or formally employed by 1 2 percentage points, relative lti to mean of 36% (employed) or 26% (formally employed). Likewise see very little in the way of impact on earnings conditional on being employed. Impacts are much lower than participants expected (suggesting revealed preference argument may be misleading) and than ISKUR staff expected.

38 Looking beyond overall impact Evaluation can help us understand which types of courses seem to have most effect and types of people course has most impact for.

39 Proportion Formally Employed by Subgroup Treatment t Control Men Women High School + <High School Private Provider Public Provider Accounting

40 Proportion Formally Employed by Subgroup Treatment t Control Men Women High School + <High School Private Provider Public Provider Accounting

41 Illustration 3: Using experiments to test not just whether program works, but which components of program work best in the Dominican Republic Target Population: years old Not completed secondary school Unemployed, under employed employed or inactive From poorest 40% of households Objective: improve employment opportunities of at risk youth by building: technicalskills (TS) life skills (LS) work experience (WE) Training provided by private institutes contracted by Ministry of Labor

42 Program Components Technical/vocational skills (VS) 150 hours $160 USD per student Heterogeneous curriculum: Beauty, sales, tourism & hospitality, carpentry, electricity, etc Life skills (LS) 75 hours $80 USD per student t Standardized curriculum: Self esteem and self realization, communication, conflict resolution, life planning, time management, team work, decision making, hygiene and health, etc Work Experience (WE) Apprenticeship p in private company 240 hours Daily stipend of US$2

43 Questions: Opening the Black Box Should youth employment programs emphasize hard or soft skills? Are all components needed? dd? Are employment outcomes the main area we should expect to see impacts?

44 Experimental Evaluation 18,270 eligible applicants for 10,400 slots in 520 courses Random Assignment of 35+ applicants per course to: Random Assignment VS +LS+WE LS+WE Control Wait List (20) (5) 341 courses (5) (5+) Random Sample T1 = 1560 youth T2 = 1560 youth C = 1560 youth balanced

45 Impacts after 1.5 years: Women Men Employment + (VS) 0 (LS) Active job search 0 + Work hours 0 0 Wages + 0 Job Satisfaction + + Future Expectations + + Pregnancy reduction + NA Cost of LS+WE = 2/3 VT

46 Lessons for Youth Employment Policies in New Zealand Randomized dexperiments provide a feasible and credible way of telling whether policies are having the desired impacts Impacts of youth employment programs often less than policymakers and youth themselves expect Many youth will find jobs anyway Impactscan can be short lasting, disappearing soon after program ends Underlying issue may be lack of demand for labor so policies which try and find youth jobs without increasing private sector demand for workers will struggle.

47 Not just work/not work Policy side Should think of these experiments as way of testing Which components work best, whether you need multiple components or just some of them For whom program works best so can better target program and think about constraints/alternatives for those who program not working Enabling cost benefit comparisons among competing policies Youth side: employment is only one of the impacts we should care about, may be other important benefits we should measure E.g. improved mental health hfrom soft skills kll in Jordan Lower risk of pregnancies among youth in DR.

48 Other key issues to think about in evaluating these programs Displacement? Are you creating more jobs, or just changing who gets them? Timing of effects Need measurement over longer term horizons if youth move in and out of labor market a lot, and it takes a while for effects to occur. Learn from what you are doing Policymakers always say they have no time to wait, want to do something now so instead of massive large scale program where results uncertain, why not a range of pilots, which you rigorously evaluate. May be easier to implement in NZ than developing countries More administrative data available from companies, tax records, unemployment records, etc. so can in principle track outcomes over long periods at relatively low cost.