1. Explaining exits from unemployment in the UK, 2006-09 Labour Force User Meeting - 2 nd December 2010 Peter Stam Household Labour Market and Developments Branch

2. Background Previous work Long (2009) Interest and development Objectives Data

3. LFS – Characteristics of individuals Methodology – Heckman modelling 1.Modelling the probability of being unemployed 2.Modelling the length of unemployment 3.Modelling the probability of finding employment

4. LFS – Reference group Female Aged 35 through 49 Living in West Midlands Metropolitan County Not classified as an ethnic minority Unmarried with no dependant children Qualified to Below GCSE Renting privately Previous occupation Elementary

5. Modelling the probability of being unemployed Marginal effect Statistical Significance Age 18 through 244.5*** Age 25 through 34 - 1.1*** Age 50 through 59 - 2.0*** Age 60 plus - 4.5*** Male3.2*** Ethnic minority4.6*** Married - 5.5*** Dependent child and female2.2*** GCSE0.9** LFS - Results

6. Modelling probability of having a spell of unemployment – Housing -5% -4% -3% -2% -1% 0% 1% 2% 3% 4% Rent-freeMortgageOwn homeHousing Association

7. LFS - Results Modelling the length of unemployment Coefficient Statistical Significance Constant3.7 months** Age 18 through 24 - 1.3 months* Age 50 through 59 + 2.1 months** Male - 1.6 months*** Dependent child and male + 1.6 months*** Job Seekers Allowance + 3.8 months*** Administrative and Secretarial + 1.9 months* Skilled Trades + 2.3 months** Sales and Customer Service + 2.9 months** Process, Plant and Machine + 2.6 months**

8. LFS – Results Modelling the probability of finding employment Marginal Effects Statistical Significance Male-3.7 * Married9.1 *** Dependent child and male-1.7 * Dependent child and female-10.7 *** Job Seekers Allowance19.2 * GCSE5.3 *** Further Education13.6 *** Degree12.1 ***

9. LFS - Results -25% -20% -15% -10% -5% 0% 5% 10% 15% Age 18 through 24Age 25 through 34Age 35 through 49Age 50 through 59Age 60 plus Modelling the probability of finding employment – Age

10. LFS - Results Spell length (months)Marginal effect 6 or less Base 7 - 12- 17.7 13 - 18- 27.2 19 - 24- 11.3 25 - 30- 21.0 37 - 42- 12.1 49 - 54- 24.3 60+- 10.5

11. BHPS – Exit destinations Motivation Economic states Data Methodology Inactive ? Employed Unemployed

12. BHPS - Results Into employment 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 1357911131517192123252729313335373941434547 Elapsed Duration (Months) Hazard

13. BHPS - Results Into inactivity 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 1357911131517192123252729313335373941434547 Elapsed Duration (Months) Hazard

14. Conclusions - Methods Modelling on the LFS provides consistent results with BHPS As duration of unemployment lengthens… so chance of re-employment decreases (LFS / BHPS) As duration of unemployment lengthens… so chance of inactivity increases (BHPS)

15. Conclusions - Messages Men more likely to become unemployed… but for a shorter time JSA increases the length of time unemployed… but increases the chance of finding employment Education has positive effect on finding employment (peaks at A-level) Housing association tenants more likely to be unemployed Mortgage holders increases chance of finding re-employment Older people have longer spells and are less likely to find re- employment

16. This work contains statistical data from ONS which is Crown copyright and reproduced with the permission of the controller of HMSO and Queen's Printer for Scotland. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates. Peter Stam Household Labour Market and Developments Telephone ext. 5982 peter.stam@ons.gov.uk