Presentation is loading. Please wait.

Presentation is loading. Please wait.

Data collection for CLTRI on improved labour market situation using administrative data: Latvian approach ESF Evaluation Partnership meeting, 6 June 2019,

Similar presentations


Presentation on theme: "Data collection for CLTRI on improved labour market situation using administrative data: Latvian approach ESF Evaluation Partnership meeting, 6 June 2019,"— Presentation transcript:

1 Data collection for CLTRI on improved labour market situation using administrative data: Latvian approach ESF Evaluation Partnership meeting, 6 June 2019, Dublin, Ireland NORMUNDS STRAUTMANIS Evaluation Unit

2 GUIDANCE LTRI Participants with an improved labour market situation six months after leaving Persons who are employed when entering ESF support and who, following the support transited from precarious to stable employment, and/or from underemployment to full employment, and/or have moved to a job requiring higher competences/skills/qualifications, entailing more responsibilities, and/or received a promotion 6 months after leaving the ESF operation. (ESF Monitoring and Evaluation Guidance Document, June 2015) Shall be based on a representative sample of all participation records within each investment priority (ESF Monitoring and Evaluation Guidance Document, June 2015) Does not preclude the collection of data for all participants should Member States choose to do so (Annex D)

3 Improved labour market situation?

4 WHAT TO OBSERVE? IMPROVED LM SITUATION WHAT TO OBSERVE?
transition from precarious to stable employment, Type of contract, Hours worked and/or from underemployment to full employment, Hours worked movement to a job requiring higher competences/skills/qualifications, Hourly wage, Monthly wage (income), Position entailing more responsibilities and promotion.

5 Management Information System
STEP 1. MERGING OF ADMINISTRATIVE DATA PARTICIPANT DATA ID number Job situation PARTICIPATION DATA Start / end date Investment priority / operation LABOUR MARKET SITUATION Income (monthly wage, net) Hours worked (monthly) Job position (based on job classification) Management Information System State Revenue Service

6 6 months after leaving (2)
STEP 2. CALCULATIONS Start date (1) 6 months after leaving (2) Criterion Method for calculations Example (real person) Hours worked Part time h=>80; Full time h=<81-160; Overtime h=>161+ Hours worked. H1 (start date) is compared to H2 (6 months after leaving). If H1=<H2, than =1, otherwise 0. H1 = 176h ( ), H2 = 24h ( ) H1>H2, thus H = 0 (LM situation not improved) Job position 4-digit profession code. P1 (start date) is compared to P2 (6 months after leaving) If P1 =<P2, than =1, otherwise 0. P1 ( ) = 2142, P2 ( ) = 1323. P1 =<P2, thus P = 1 (LM situation improved) Income (monthly wage, net) Income (monthly wage, net) A1 (start date) is compared to A2 (6 months after leaving). Average monthluy income nationwide Avid mēn 1 and Avid mēn 2. It is tested if (A2/A1) > ((A vid mēn 2 /A vid mēn 2)/2), if yes =1, otherwise = 0. (50% increase is taken into account). A1=534 ( ) A2=228 ( ) A vid mēn 1 = 758 A vid mēn 2 = 913 A = 0, because (228/534) < ((913/758)/2) (LM situation not improved)

7 Definition 2021 - 2027 (proposal)
RESULTS Definition IP Gender Not improved Improved Improved (percentage) 3.4. Female 1151 2826 71% Public administration Male 360 1046 74% 7.2. 72 877 92% YEI 93 848 90% 8.3. 212 875 80% Early school leaving 11 66 86% 8.5. 380 1158 75% Vocational education 280 679 9.1. 42 120 Active labour market inclusion 22 96 81% 9.2. 1462 4968 77% Access to healthtcare 298 815 73% Total 4383 14374 76,6% Definition by factor Not improved Improved one factor Improved two factors Improved three factors 1151 2667 158 1 360 983 63 72 664 183 30 93 636 197 15 212 832 41 2 11 60 6 380 1089 66 3 280 627 49 42 113 22 91 4 1462 4667 295 298 760 52 23,4% 70,3% 6,0% 0,3% Definition (proposal) Not improved Improved Improved (percentage) 3213 764 19% 1125 281 20% 272 677 71% 382 559 59% 888 199 18% 58 19 25% 1184 354 23% 756 203 21% 141 21 13% 106 12 10% 4816 1614 867 246 22% 13808 4949 26%

8 ADMINISTRATIVE DATA VS. SURVEY OF PARTICIPANTS
SOME ISSUES TO BE CONSIDERED Data to be cleaned before calculation More than one participation? More than one job? Working overtime? Monthly income or 3-months average? ADMINISTRATIVE DATA VS. SURVEY OF PARTICIPANTS … AND NOT ONLY LATVIANS …

9


Download ppt "Data collection for CLTRI on improved labour market situation using administrative data: Latvian approach ESF Evaluation Partnership meeting, 6 June 2019,"

Similar presentations


Ads by Google