Advanced Profiling of Unemployed in Public Employment Services A Critical Review of OECD Experiences and Applications for Western Balkans Vienna, March 4, 2014 Artan Loxha Social Protection Unit Europe and Central Asia Region Outline 1. Profiling in the context of activation 2. Best practice profiling methods in OECD 3. Statistical profiling and applications 4. Relevance for Western Balkans Outline 1. Profiling in the context of activation 2. Best practice profiling methods in OECD 3. Statistical profiling and applications 4. Relevance for Western Balkans
Key elements of activation Mutual obligations principle Activation models Liberal model Social democratic model Continental corporatist model Restricted ALMPs to incentivize jobseeker Extensive services and high benefit levels and coverage Individual responsibility to mobilize own assets, with key state role
PR O Key elements of effective activation FI LI N Enhanced responsibilities of the unemployed - Active job search and availability for work in return for income support Provision of income support - Access to income support and to public employment services G
- Individualized action-planning - Focus on high risk prioritization Operationalizing legislation through 4 main elements of activation - Service integration between PES and SA - Enhanced performancebased subcontracting 4 The traditional role of the PES Interventions Intensive counseling and special ALMPs Vocational training Traditional
PES client: the unemployed Self-service and job matching Level of prioritization by caseworker HIGH LOW 1 Income support/Job matching Time 5 Reinventing the role of PES in the context activation Early interventions FI LI
N Interventions G 2 Work-able vulnerable population Traditional PES client: the unemployed 1 Distance from labor market HIGH
High risk group HIGH Intensive counseling and special ALMPs Middle risk group Vocational training Low risk group Self-service and job matching Level of prioritization by caseworker PR O LOW
LOW 1 Income support/Job matching Time 6 Main uses of profiling 1 2 High risk group Middle risk group Low risk group LOW
HIGH Level of prioritization by caseworker Vulnerable work-able population Distance from labor market HIGH LOW 3 Referral Intensive counseling and special ALMPs Vocational training Self-service
and job matching $ Redistributing resources based on severity of profile Interventions Caseworker Client segmentation Targeting Resource planning 7 Profiling involves certain information asymmetries Caseworker 1
LOW 2 High risk group Middle risk group Low risk group HIGH Level of prioritization by caseworker Vulnerable work-able population Distance from labor market HIGH Interventions 3 Referral
Intensive counseling and special ALMPs Vocational training Self-service and job matching LOW Information asymmetries 8 Outline 1. Profiling in the context of activation 2. Best practice profiling methods in OECD 3. Statistical profiling and applications 4. Relevance for Western Balkans Approach for studying OECD best practices 1: Stock-taking Partner with Public Employment Services (PES) in OECD countries to capture best practices on jobseeker profiling 2: Adaptation
Identify models that could be applicable to Europe and Central Asia (ECA) PES, and test them through analysis of administrative data 3: Sharing with clients Share knowledge with PES in ECA region and explore possible pilots 4: Dissemination Enhance knowledge of all stakeholders through a Knowledge Brief, analytical paper, and conference 10 Methodology
Countries Desk research Australia Canada Denmark Finland Germany Ireland Netherlands Slovenia South Korea USA Sweden Switzerland OECD activation country notes EU PES-to-PES dialogue papers Country-specific papers on profiling
Selected academic papers Methodological notes on statistical profiling PES material Study tour (selected examples) Ireland, Department of Social Protection Technical description of JSCI (AUS) Employeefocused Integration concept (GE) The Dutch Work Profiler (NL) Slovenian
profiling system (SL) Denmark, National Labor Authority Sweden, Public Employment Service 11 Key approaches to profiling in OECD Approaches Description Pros/Cons Country examples Caseworker-based segmentation Profiling and referral done primarily by the caseworker Pros: individual needs
German 4-phase model Time-based segmentation Segmentation based on threshold in length of unemployment spell Pros: straightforward Demographic segmentation Segmentation based on eligibility criteria Pros: straightforward Segmentation based on statistical analysis using MIS data Pros: ex-ante equal treatment, early interv., resource rationing USAs Worker Profiling and Reemployment Services Cons: misidentification
Irish profiling system Pros: greater private information German Kompetenzdiagnostik (competence diagnostics) Statistical segmentation Behavioral segmentation Evaluation using behavioral assessment tools Cons: subjective assessment Cons: resource waste, ignores heterogeneity. Irelands wait-and-see approach prior to the crisis Swedish Youth Job Program Cons: ignores heterogeneity
Cons: subjective 12 Degree of caseworker discretion Classifying profiling systems Complexity of data flow and processing 13 1. Data availability and processing Basic demographics - Personal ID Age Gender Children Education level Labor market data - Employment status
Duration Special needs Qualifications Complexity of data and processing Complex data - Soft and hard skills Motivation Behavior Health 14 2. Degree of caseworker discretion Degree of caseworker discretion HIGH - More likely to rely on caseworker-based diagnostics for segmenting jobseekers Caseworker resistance to automation may be higher More time-intensive and resource intensive Requires higher capacity
However, caseworkers discretion can be curtailed depending on how binding data processing is to their decision-making - More likely to rely on administrative rules and regulations for segmenting jobseekers - Less caseworker resistance to introducing other analytical tools may help address different constraints LOW 15 Classifying profiling systems Degree of caseworker discretion HIGH Caseworker-based profiling Data-assisted profiling Rules-based
profiling Data-only profiling Complexity of data flow and processing LOW LOW HIGH 16 Key trade-offs Invest in more caseworkers Caseworker-based profiling Rules-based profiling Data-assisted profiling Higher
caseworker resistance to automation Degree of caseworker discretion HIGH in st kers e Inv wor ata se d ca and Invest in data acquisition Data-only profiling Complexity of data flow and processing LOW LOW HIGH 17
Profiling systems in OECD 18 Outline 1. Profiling in the context of activation 2. Best practice profiling methods in OECD 3. Statistical profiling and applications 4. Relevance for Western Balkans Statistical profiling: segmenting clients based on likelihood of work-resumption work-resumption Outcomes Profiling model: Data input: - MIS Ad-hoc extra data -
Binary or duration models Risk of remaining long-term unemployed HIGH 100 2 1 LOW Little chance of reemployment Better chance of reemployment Improved chance of reemployment Best chance of reemployment Intervention strategies by client profile and support intensity
Near Missed opportunities Better chance of reemployment Improved chance of reemployment Frequency of Intervention Client Distance from Labour Market Far Directive Guidance Reference to Personal Development Job Search Best chance of reemployment Wasted resources Self-Serve
Low Intensity of Support High 21 Ireland: statistical profiling for case management intensity Sweden: statistical profiling for ALMP prioritization Registration and initial interview Segmentation based on risk groups Statistical profiling model Final caseworker decision GROUP 1 Very good employment prospects GROUP 2 Good employment
prospects Registration 1 Assessment Support Tool 2 GROUP 3 Weak employment prospects GROUP 4 At high risk of LTU; early ALMP measures needed 3 Caseworker likely to override regular procedures and provide early ALMP interventions 23 Assessment Support Tool
24 Australia: statistical profiling for steering private contractors 25 Australia: statistical profiling for steering private contractors 26 Outline 1. Profiling in the context of activation 2. Best practice profiling methods in OECD 3. Statistical profiling and applications 4. Relevance for Western Balkans Relevance to the Western Balkans New focus on activation Descriptive profiling revealed high heterogeneity of clients in PES Need to manage and focus scarce resources Already have a functioning (little exploited) MIS Can be integrated as part of a larger reform
Main challenge: define specific ALMPs for each client segment (taking heterogeneity into account) 28 Key implementation lessons Data availability and nature of unemployment determine accuracy and feasibilty of profiling tool Apply to critical spot in process management where profiling adds value, not just another tool Pilot a lot on the ground, prepare clear guidelines to manage implications of tool on day to day case management Reduce/manage perceptions of de professionalization of case workers, find where it adds value to their work 29 Contacts Artan Loxha Labor Market Consultant, World Bank [email protected] Matteo Morgandi Economist, World Bank [email protected] 30
