Targeting and impact of measures to improve employability

Targeting and impact of measures to improve employability Anna Adamecz Ágota Scharle Budapest Institute for Policy Analysis www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Outline § Selecting programmes for the study § Data sources § Access and targeting § Raw reemployment rates § Impact analysis § Lessons § Recommendations www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Selecting programmes § HU vs EU 15 employment gap: largely due to low emp of uneducated § most long term unemployed are uneducated § NLO admin data are accessible à 5 programmes targeting the uneducated, administered by NLO, between 2007 and 2010 à covering 56 % of total expenditure in SROP www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Design of selected programmes § complex: mentoring, training, wage subsidy srop 111 – disabled jobseekers srop 112 – primary ed, long term unemployed srop 113 – long term unemployed (SA) § targeted wage subsidy srop 121 – long term unemployed (low ed/older) § training and adult education srop 211 – jobseekers with primary education www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Data sources § Official progress reports § NLO unemployment register (individuals) stock of 20 Jan 2009 inflow bween 20 Jan 2009 – 20 Jan 2010 § NLO program participants (individuals) entering before 31 Dec 2010 § Tax registry data on start of work contract for control and treated, until Oct 2012 www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Access and targeting srop 111 Relevant target group Other target groups participants (thnds) p/t (%) srop 112 srop 113 primary ed SA long term + Roma, unemp primary ed new disab. school benefit leaver + DA <25 ys >50 ys maternity <35 ys school leaver disabled lone parent srop 121 srop 211 primary ed long term unemp + SA School leaver >50 ys maternity vocation 11. 0 50. 3 5. 8 (13. 0) 18. 5 23 27 2 n. a. 3 www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Share of uneducated (%) www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Raw reemployment indicators Official progress reports (OPR) § during/straight after program or on day 180 § excludes public works § only those completing the programme NLO § within 180 days or any time until Oct 2012 § or did not reregister within 180 days § includes public works § all those entering the programme www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Raw reemployment rates % 1. 1. 1. 2. 1. 1. 3 OPR indicators Exit to employment 16 48 60 Employed on day 180 26 34 10 Exit to job within 180 days 30 61 55 Exit to job any time until Oct 2012 68 87 84 Did not return to NLO register 76 76 65 NLO indicators www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Impact analysis: the method § Impact of programme participation on probability of reemployment § Compare observed outcome to „What if? ” § Compare to counterfactual § Select control group by matching (propensity score) § Control group with same observed characteristics (age, sex, education, employment history, location) www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Impact of SROP 113 (men) www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Impact of SROP 1. 1. 1. and 1. 1. 3. § Reemployment rate much higher for participants § srop 1. 1. 1: higher by 53 -51 %points § srop 1. 1. 3: higher by 57 -50 %points § Upper bound: large, positive w upward bias § Much larger than international evidence § Possible selection bias in unobserved characteristics (e. g. motivation, ethnicity) § No data on unregistered employment § Includes deadweight loss and substitution effects www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Impact of short w. subsidy fades out www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

SROP 1. 1. 1. w/wout wage subsidy control men N treat % N treat, no wage subsidy % N % reemployed 1. 11 2% 275 53% 134 26% reemployed 2. 6 1% 152 30% 101 20% reemployed 3. 13 3% 356 69% 214 42% control women N treat % N treat, no wage subsidy % N % reemployed 1. 17 2% 531 55% 240 25% reemployed 2. 11 1% 280 29% 183 19% reemployed 3. 25 3% 694 71% 402 41%

SROP 1. 1. 1. for long term unemp control men N treat % N treat, no wage subsidy % N % reemployed 1. 6 2% 144 46% 68 22% reemployed 2. 2 1% 88 28% 60 19% reemployed 3. 8 3% 196 63% 120 38% control women N treat % N treat, no wage subsidy % N % reemployed 1. 7 1% 217 46% 99 21% reemployed 2. 6 1% 118 25% 81 17% reemployed 3. 10 2% 296 62% 178 37%

Lessons § limited resources for programmes for the uneducated § reemployment rates are high and increase in time § participants are better educated (except srop 211) § srop 111 and 113: large positive impact § training and mentoring improves reemployment even without wage subsidy § impact of short term wage subsidy fades out fast § srop 111: significant impact for long term unemployed § mentoring has stronger impact on women § NLO register suitable for monitoring www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

Recommendations § increase funding for training and mentoring for uneducated jobseekers § adjust programme design based on impacts § improve targeting: target group, sub-indicators, profiling § unify indicators across programmes § add indicators on long term (1 -2 years) impact § accompany new programmes with detailed longitudinal survey of participants and control www. ujszechenyiterv. gov. hu | Budapest, 30 April 2013

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