New trends in active labour market policy

1. New trends in active labour market policy Giuliano Bonoli

2. New tools • Employment retention and advancement schemes • Profiling: early detection of jobless people at risk of long term unemployment • Statistical Matching/targeting: statistical tools to improve the matching between individual features and programmes

3. ERAs • Paradox: ALMPs focus their efforts on the jobless, and then « forget » about them when they are back in employment • Several studies have shown that first jobs are often unstable and badly paid • Since the early 2000 in the US and UK, developemnt of « Employment retention and advancement  (ERA)»

4. The US ERAs • Started in 1999, for a ten-year period • 15 demonstration programmes, 45,000 persons are involved • Services on offer vary • In general: • Career advice • Access to vocational training • Incentives to keep employment

5. ERA in Texas • Open to both TANF recipients and people in employment • Incentive of USD 200/month for those who: • Work at least 30 h/week(15h+15h training) • Take part in « advancement » activities • Limited to 12 months • Counselling, help in case of problems • Career advice Source: Martison, K. and Hendra, R. (2006) Results from the Texas ERA site, Washington D.C., MDRC.

6. Intermediary results: positive but weak effects

7. Quality of emplyoment after 12 months

8. Results are not particualrly encouraging • Other interim evaluations produce similar results • Implementation problems (e.g. « Enhanced job clubs in Los Angeles) • Final evaluations will be available early 2010s • For additional info, see http://www.mdrc.org/project_publications_25_9.html

9. Profiling / matching • Jobless people may have very different needs: • Some, do not need any help. They are perfectly able to find a job on their own • Some may be highly employable, but may benefit from some form activation • Some may need training/work experience • Some hard to employ jobless may need extensive assistance • It is important to match the type of assistance provided to the characteristics of the unemployed person

10. Profiling and matching • Profiling: identify as early as possible those unemployed people who are at risk of long term unemployment • Matching: Identify the type of assistance that is most likely to produce positive outcomes given recipients' individual characteristics

11. The « Job seekers classification instrument » (Australia) • Tool helps identifying those at risk of long term unemployment at a very early stage • Introduced ion 1994 and adapted since • Statistical analyses identifies factors that increase the risk of long term unemployment (>12 months) • A questionnaire is used to estimate the risk for each new recipient • Those who are identified as « at risk » are transferred to a scheme providing more extensive assistance

12. Some factors used by the JSCI • Age and gender • Language • Health problems • Education • Work experience • Family situation • Points are assigned for each factor representing disadvantage • The score varies between 0 (= highly employable) et 50 (=extremely hard to employ)

13. Distribution of recipients according to JSCI score Source: Robert Lipp, Job Seeker Profiling.The Australian Experience. EU-Profiling seminar IAB Nuremberg, 12-14th January 2005

14. A rather precise tool … Source: Robert Lipp, Job Seeker Profiling.The Australian Experience .EU-Profiling seminar IAB Nuremberg, 12-14th January 2005

15. Other types of profiling • Denmark: combination of statistical analysis and subjective perception of case workers • Austria: system based more on the subjective evaluation of the case worker

16. Can profiling shorten the duration of the unemployment spell? • The impact of JSCI has not be evaluated in a randomized controlled trial. However, the tool is considered to be helpful • Other profiling systems have been evaluated (US, Germany). No celar effect has been found.

17. Profiling + matching • Identify different categories of jobless people • On the basis of statistical analysis, identify the measures that are most likely to be successful for each category of jobless people. • Assign to each jobless person the measure that is most likely to be successful (matching).

18. Study by Lechner et Smith, 2003 • Comparison of decisions made by case workers with the results of statistical modeling. • Statistical modeling identifies the measure most likely to lead to employment given individual characteristics • Result: case workers get it « right » about 50% of times Source: Lechner, M. and Smith, J. (2003) What is the value added by case workers?, University of St Gallen, Department of Economic, Discusion paper 2003-05

19. Statistical Assistance for Programme Selection (SAPS) • Computer-based statistical program that indicates the measure most likely to be successful given individual characteristics of the jobseekers • Pilot project by the Swiss government in 2005 • Some 300 case workers in 21 employment offices were involved. Five cantons BS, BE, GE, SG, ZH. • 50% used SAPS, 50% are the control group • Random allocation of case workers (to SAPS or control group)

20. How does SAPS work? • On the basis of individual measurable characteristics, for each jobless person SAPS estimates the number of likely months in employment during the next 12 months, depending on the measure selected. • It is meant to assist and not to substitute the case worker in assigning jobless persons to measures. • Categories of measures are rather broad Source: Behnke, S., Frölich, M. and Lechner, M. and (2006) Statistical assistence for programme selection, University of St Gallen, Department of Economic, Discusion paper 2006-09

21. Categories of mesures • No measure • Computing course • Language course • Vocational training • Employment search course • Work experience scheme

22. View of the SAPS program

23. SAPS: result of the evaluation (2007) • The performance of case workers using SAPS was not significantly better than that of those without it • In some cantons case workers showed strong resistance against the tool • Programme was abandoned as a result of the evaluation

24. Can statistical analysis help ? • Australian-style profiling seems amore realistic goal than the more ambitious matching approach of SAPS • Remember that many factors the affect the chances of finding a job may not be measurable, but may be visible to an experienced case worker