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Unemployment and its scarring effect on post-unemployment career in UK

Unemployment and its scarring effect on post-unemployment career in UK. Paul Schmelzer, Boubaker Hlaimi 24.07.2007 QMSS Conference, Prague, Check Republic. Outline. Introduction Theoretical Background Main Hypotheses Data, Variables, Methods Main Results Summary.

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Unemployment and its scarring effect on post-unemployment career in UK

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  1. Unemployment and its scarring effect on post-unemployment career in UK Paul Schmelzer, Boubaker Hlaimi 24.07.2007 QMSS Conference, Prague, Check Republic Schmelzer, Hlaimi

  2. Outline • Introduction • Theoretical Background • Main Hypotheses • Data, Variables, Methods • Main Results • Summary Schmelzer, Hlaimi

  3. Introduction – Research Question Analytical Focus: • Has unemployment a scarring effect on the re-enter status and the growth for different educational groups in UK • Specific questions: • Re-entering the labor market after unemployment do employment career take a different future profile compared to those who have not been unemployed? • Does prolonged unemployment duration has a scarring effect on re-enter opportunities and subsequent growth of unemployment career? Schmelzer, Hlaimi

  4. TheoreticalBackground • Many studies strongly suggest a scarring effect of unemployment (for UK Arulampalam 2001, Gregory an Jukes 2001, Gregg 2001) • There have been a shift towards unemployment benefits and positive effects on duration of unemployment (for USA and Germany: Gangl 2004, for Canada Belzil: 2001) unemployment benefits => longer job search => better match • However they do not differentiate between educational groups • Many studies compare only pre- and post-unemployment wages and have not control group (lacking unemployment spells) • Researchers mainly focus on income for gains/losses and not on status Schmelzer, Hlaimi

  5. Main Hypotheses • Human capital theory: unemployment devaluates firm-specific skills and thus has a scarring effect on post-unemployment career • But we analyze early careers with 1. few employment experience and 2. high rate of mismatches (unstandardized educational system) • unemployment can be used to find a better match position • However, we believe that impact of unemployment is different for different educational groups Schmelzer, Hlaimi

  6. Main Hypotheses (Re-entry into the labor market) • High productivity workers (tertiary education) might use unemployment phase to find a better match • Higher educated do not take the first available job they get • They have got higher previous income • Return wages are higher (employment insurance) • Partner usually also have high wages supporting them by the work search • There is no competition for tertiary education by other educational groups • Higher educated have got an option to decide for an adequate job • They are pulled into the labor market • They perform better re-entering labor market than lower qualified • They do not loose in status by re-entering labor market compared to the end of the last job • Prolonged searching phase might even improve the re-entry status and growth Schmelzer, Hlaimi

  7. Main Hypotheses (Re-entry into the labor market) • Low productivity workers (primary education) are in competition with more qualified workers • Lower educated are forced to take the first available job • Low previous income • Return wages are low (employment insurance) • Low or no support by partners • Sanctions by job agencies when not taking an offer => They are pushed into the labor market => They perform worse re-entering the labor market than higher educated => They loose in status compared to the end of the last job => Prolonged unemployment phase does not improve re-entry status and growth (no offers before) Schmelzer, Hlaimi

  8. Data • British Household Panel Survey (BHPS) from 1980 to 2003 (including retrospective data from 1980 to 1990), Northern Ireland and the North and West Highlands are excluded • Sample definition: • Persons who left the educational system between 1980 and 2004, excluding persons older than 30 • Gaps of less than 8 months between two educational episodes are closed • Starting sample: 2900 young men and women Schmelzer, Hlaimi

  9. Variables • Educational cohorts • 1980-1984, 1985-1989, 1990-1994, 1995-1999, 2000-2004 • Gender • Type of contract and mismatches • fixed-term vs. permanent contract • full-time, part-time contract, self-employment • Educational classification • Modified CASMIN classification: 1. primary without 2. primary with qualification 3. O-Level 4. A-Level 5. lower tertiary 6. higher tertiary • Region • Middle, South, North, Scotland • Regional unemployment rate • Industry • modified Singelmann classification Schmelzer, Hlaimi

  10. Methods • Statistical methods: • Linear Mixed-effects models • Research window is 10 years when people left their education • Unbalanced data with 6.6 measurement points on average • Dataset covers on average 7 years • Time: starting time “0” • Subjects total 2928 • Subjects with at least one unemployment spell 909 • Dependent variable: • Occupational status measured in ISEI-Score Schmelzer, Hlaimi

  11. Methods (random effect models) • Closure of inactivity (unemployment) gaps but using this information for random effects models (gaps are not missings) • Modeling two phases: pre-unemployment phase and post-unemployment phase Schmelzer, Hlaimi

  12. Methods Schmelzer, Hlaimi

  13. Post-unemployment slope Pre-unemployment slope Pre-unemployment intercept Post-unemployment intercept Inactivity spell (unemployment, full-time education, something else)

  14. Pre-unemployment phase Schmelzer, Hlaimi

  15. Results: pre- and post-unemployment phase Schmelzer, Hlaimi

  16. Schmelzer, Hlaimi

  17. Results: pre- and post-unemployment phase Schmelzer & Skopek

  18. Schmelzer, Hlaimi

  19. Post-unemployment slope Pre-unemployment slope Pre-unemployment intercept Post-unemployment intercept Inactivity spell (unemployment, full-time education, something else) Schmelzer & Skopek

  20. Wald test statistics Schmelzer, Hlaimi

  21. Schmelzer

  22. 1 Primary without qualification Primary without qualification .24 Primary with qualification Primary with qualification O-Level O-Level .9 .22 A-Level A-Level Lower tertiary Lower tertiary .2 .8 Higher tertiary Higher tertiary .18 Survival probability .7 .16 Hazard rate .6 .14 .12 .5 .1 .4 .08 .3 .06 .04 .2 .02 .1 0 0 2 4 6 8 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 time analysis: months time analysis: months Hazard rate and survaval probability for leaving first unemployment Schmelzer

  23. Pre-unemployment phase 4.5 4 5 6 6.8 8.8 Schmelzer & Skopek

  24. Schmelzer & Skopek

  25. Schmelzer & Skopek

  26. Schmelzer & Skopek

  27. Summary Schmelzer

  28. Thank you for your attention. Schmelzer, Hlaimi

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