Presentation is loading. Please wait.

Presentation is loading. Please wait.

Representative sampling Overview of the questions received by the ESF Data Support Centre Alphametrics Ltd. & Applica Sprl. Brussels, 13 March 2015.

Similar presentations


Presentation on theme: "Representative sampling Overview of the questions received by the ESF Data Support Centre Alphametrics Ltd. & Applica Sprl. Brussels, 13 March 2015."— Presentation transcript:

1 Representative sampling Overview of the questions received by the ESF Data Support Centre
Alphametrics Ltd. & Applica Sprl. Brussels, 13 March 2015

2 Questions on dimensions
Representative samples have to provide estimations per IP, category of region (except YEI) and gender. Sampling is not required at the level of the specific objective. Representativeness in terms of characteristics of participants: gender, age, employment status, education level and household situation. IP 1 Less developed Transition More developed Men Women It is good practice to ensure representativeness at the sub-regional level within each category of region (to ensure for instance that the sample is not biased towards participants from the capital in comparison to those from other areas within the same region). Regional representativeness could be achieved by establishing the sample one NUTS level lower than the level of the programme area (e.g. for an OP at NUTS 2 level, the sample should have the same distribution by NUTS 3 level as observed amongst all participants).

3 Questions on methods Stratified sampling Completeness requirement
No obligation to use a stratified sampling method. But if this is not used, it will be necessary to have separate samples per gender and category of region. Completeness requirement In order to be considered in the reference population, records have to be complete for all non-sensitive personal data (excl. homeless/rural areas).

4 Questions on reference population
Indicator Reference population Representativeness in terms of: Participants in employment 6m after leaving Unemployed Inactive - Unemployed/Inactive - Age - ISCED - Household situation Homeless All participants (up to end-2016) - Employment status - Age - ISCED YEI longer-term indicators All participants (each year) - Unemployed/Inactive not in education or training - Age if 25-29  Not possible to exclude specific groups from the reference population (e.g. students/children). Fields recording irrelevant data can be completed with 0. Each indicator requires a representative sample at the level of the IP reflecting the relevant population of participants. See Annex B of the EC guidance. For instance for ‘Participants with an improved labour market situation 6 months after leaving’ which refers only to participants who were employed on entry, fields can be completed with 0 for participants who were unemployed/inactive on entry.

5 Questions in relation to YEI
7 Longer-term result indicators (6m after leaving) Representative samples - Participants in employment 1 sample (unemployed, inactive not in education/training, ISCED, HH, age if 25-29) - Disadvantaged participants in employment 1 sample (unemployed, inactive not in education/training, ISCED, age if 25-29) - Participants with an improved labour market situation - Participants >54 in employment Not applicable (0) - Participants in continued education, training programme leading to a qualification, an apprenticeship/ traineeship - Participants in employment - Participants in self-employment 1 single sample (unemployed, inactive not in education/training, ISCED, HH, age if 25-29)  YEI indicators to be reported annually: 1 sample for each year. Annex I Annex II YEI targeted at participants <25 who are unemployed or inactive not in education/training. All the 7 longer-term result indicators should be reported. 0 values will be reported for the 2 common longer-term result indicators ‘Participants with an improved labour market situation’ and ‘Participants above 54 in employment’ as the reference population does not match the YEI target groups (young aged under 25 either unemployed or inactive not in education/training). One sample for ‘Participants in employment 6m after leaving’. One sample for ‘Disadvantaged participants in employment 6m after leaving’. One single sample for all the 3 YEI longer-term result indicators. For common longer-term result indicators (Annex I): sample should be representative in terms of the number of participants who are unemployed and those who are inactive not in education/training. For YEI longer-term result indicators (Annex II): sample should be representative in terms of the number of participants who are unemployed and those who are inactive not in education/training. YEI longer-term result indicators have to be reported annually. The sample should include participants that left operations 6 months before the end of the reported years (e.g. for AIR 2016, the sample should include participants leaving between mid-2015 and mid-2016).

6 Questions on the schedule
Annex I common longer-term result indicators to be reported only twice (incl. for YEI) AIR 2018 (exits up to mid-2018) Final report (exits between mid-2018 and end-2023). Full sampling not possible until end-2018/mid-2024 (6m after last exit)  recommended to collect data more frequently (e.g. a sample per year) to ensure samples are not skewed towards a particular year and to help increasing response rates. Annex II YEI longer-term result indicators to be reported annually starting in April 2015. Homeless/rural areas to be reported only once in AIR 2016. Longer-term result indicators: there should be two waves of reporting and distinct samples with non-overlapping participants should be drawn: 1st wave (AIR 2018) covering participants leaving operations up to mid-2018; 2nd wave (Final report 2025) covering participants leaving between mid-2018 and end-2023. For the 1st wave, full sampling might not be possible until end-2018 (i.e. 6m after the last exits in mid-2018), for the 2nd wave until mid-2024 (i.e. 6m after the last exits in end-2023). The EC guidance however recommends that data are collected more frequently (for instance a sample for each year) to ensure that samples are not skewed towards a particular reporting year. This would also possibly help increasing the response rate as participants will be contacted shortly after leaving the operations.

7 ESF data support centre
Advice and guidance on: Methodological support on monitoring information systems Clarification regarding data collection, recording, validation and storage Guidance regarding transmission of structured data to the EC using SFC2014 (technical queries > SFC support team) 9.00 a.m. – 5.00 p.m. Monday-Friday Phone:


Download ppt "Representative sampling Overview of the questions received by the ESF Data Support Centre Alphametrics Ltd. & Applica Sprl. Brussels, 13 March 2015."

Similar presentations


Ads by Google