the effects of life-long learning on earnings and employment richard dorsett, silvia lui and martin...
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The Effects of Life-long Learning on Earnings and
Employment
Richard Dorsett, Silvia Lui and Martin Weale
The Role of Life-long Learning
• Educational attainment is strongly dependent on socio-economic background.
• It is unlikely that capacity to benefit from education is as dependent on background as is attainment
• It follows that there is plenty of scope for making up for lost time
The Spread of Life-long Learning
• 1994. 31% of 451,000 UK students starting undergraduate courses aged twenty-five or over.
• 2007, 43% of 706,000 UK students A similar pattern elsewhere–Forty per cent of those starting university in Sweden were had left school at least five years earlier
–Thirty-five per cent of male school leavers in the United States between 1979 and 1988 resumed their education by 1989.
• What are the benefits of qualifications gained through life-long learning
Doubts about the Benefits
• Jenkins et al. (2002). Wage growth after life-long learning was not significantly faster than for those who did not do it.
• Egerton and Parry (2001). Substantial penalties for late learners.• Purcell et al (2007). Case studies suggest mature graduates have difficulty
finding appropriate employment.• Blanden et al. (2008). Little benefit for men; some for women aged thirty-
five to forty-nine
A Mover-stayer Framework
• People have to take a wage from a stationary distribution (Movers)
OR
• The wage rate is closely related to the wage in the previous period (Stayers)
• Expected earnings depend on
– i) the nature of the stationary distribution
– ii) the speed with which people move up the ladder
– iii) the chance of falling off
Employment Prospects
• People have to be employed to have earnings.
• Previous unemployment may damage earnings potential at least in the short run.
• These effects need to be allowed for along with earnings dynamics.
Life-long Learning
• Consider qualifications acquired when age 25 or older.
• BHPS provides information on qualification level (NVQ) from 1991 or when subject joins survey.
• And each year on i)whether qualifications have been obtained and ii) whether educational status has been upgraded.
• Separate effects of qualifications in each of last five years from ever acquiring qualifications.
Average Transitions (Men)
Qualification in Previous Year
0 1 2 3 4
Qualification 0 0.9845 0 0 0 0Level 1 0.0029 0.9837 0 0 0in Current 2 0.0072 0.0083 0.9832 0 0Year 3 0.004 0.0052 0.0089 0.9903 0
4 0.0014 0.0029 0.0079 0.0097 1
Upgrading 0.0155 0.0163 0.0168 0.0097 0Life-long Learning 0.0441 0.0745 0.1189 0.0993 0.0969
Average Transitions (Women)
Qualification in Previous Year
0 1 2 3 4
Qualification 0 0.9885 0 0 0 0Level 1 0.0059 0.9824 0 0 0in Current 2 0.0031 0.0094 0.9854 0 0Year 3 0.0022 0.0047 0.0109 0.9809 0
4 0.0003 0.0036 0.0036 0.0191 1Upgrading 0.0115 0.0176 0.0146 0.0191 0Life-long Learning 0.0299 0.0678 0.1087 0.1108 0.1285
Non-employment Rates
Life-long Learning
Qual Never Not in last year In last year
Men Women Men Women Men Women
0 40.1% 55.7% 11.2% 21.6% 2.7% 13.1%
1 18.3% 32.4% 8.5% 18.3% 7.7% 18.0%
2 14.4% 41.1% 14.2% 16.2% 8.6% 15.2%
3 9.6% 28.2% 11.1% 19.5% 11.3% 17.5%
4 9.4% 28.3% 9.1% 15.3% 7.8% 15.3%
Earnings
Life-long Learning
Qual Never Not in last year In last year
Men Women Men Women Men Women
0 £8.17 £6.47 £9.49 £6.78 £9.56 £6.55
1 £9.82 £7.94 £10.48 £8.09 £10.33 £7.87
2 £10.14 £7.72 £10.17 £7.76 £9.72 £7.63
3 £12.27 £9.72 £11.78 £8.90 £11.66 £8.17
4 £15.79 £13.17 £15.15 £13.04 £13.52 £11.94
Sample structure
• Consider only people aged 25-60.
• Leave out self-employed (who may have negative earnings) and drop from sample if people become self-employed.
Equation Structure
if upgradeion with Qualificat
if upgradet ion withouQualificat
0 if Employed
0 ifstayer ,0 ifMover
2*
1*
2*
**
***
22
11
it
itititit
itititit
ititititit
ititit
ititit
K
KVKLearning
JWJEmployment
IIZISwitching
uXyStayer
uXyMover
Estimation Strategy
• Consider covariance structure of residuals
• Note that
for identification
1
1
1
0
2222
2
11121
012
Estimation Strategy
• Apply a Cholesky decomposition to the co-variance matrix with the life-long learning equation at the top of the diagonal.
• Estimate the life-long learning equation as an ordered probit• Compute the generalised residuals from this and introduce these as extra
variables into the other four equations estimated as a system.
Movers: Men: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Ever Acquired 25-34 0.007 0.11
Ever Acquired 35-49 -0.001 -0.02
Ever Acquired 50-60 0.034 0.38
Ever Upgraded 25-34 0.087 0.88 0.09 2.21
Ever Upgraded 35-49 0.121 1.36 0.09 2.21
Ever Upgraded 50-60 0.125 0.96 0.09 2.21
Orig Qual 1 0.124 2.72 0.12 2.65
Orig Qual 2 0.234 4.67 0.23 4.64
Orig Qual 3 0.258 4.27 0.256 4.23
Orig Qual 4 0.463 6.59 0.469 6.88
Stayers: Men: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Upgraded (t-1) 0.059 2.26 0.064 2.85
Orig Qual 1 0.003 0.49 0.001 0.29
Orig Qual 2 -0.005 -0.88 -0.006 -1.03
Orig Qual 3 0.007 1.45 0.006 1.24
Orig Qual 4 0.015 2.88 0.014 2.75
High Qual Academic 0.005 1.54 0.005 1.57
Switching: Men: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Ever Upgraded 25-34 -0.623 -2.19 -0.348 -1.78
Ever Upgraded 35-49 0.268 1.05
Ever Upgraded 50-60 -0.491 -1.9
Orig Qual 1 0.194 1.56 0.188 1.54
Orig Qual 2 0.414 3.16 0.423 3.27
Orig Qual 3 0.592 4.8 0.598 4.86
Orig Qual 4 0.983 6.83 0.985 7.26
Employment: Men: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Upgraded(t) -0.565 -2 -0.542 -2.91
Upgraded(t-1) -0.585 -2.37 -0.427 -2.8
Upgraded(t-2) -0.327 -1.41 -0.275 -1.84
Ever Acquired 25-34 0.112 0.67
Ever Acquired 35-49 0.26 1.88 0.278 2.64
Ever Acquired 50-60 0.447 2.4 0.404 3.1
Orig Qual 1 0.111 0.92 0.106 0.88
Orig Qual 2 0.293 1.94 0.285 1.91
Orig Qual 3 0.379 3.1 0.373 3.09
Orig Qual 4 0.327 2.55 0.312 2.45
Movers: Women: Selected CoefficientsUnrestricted Restricted
Coeff z-stat Coeff z-stat
Acquired(t-2) -0.176 -3.2 -0.171 -3.77
Acquired(t-3) -0.129 -2.47 -0.122 -2.99
Ever Acquired 25-34 0.049 1.04 0.079 2.72
Ever Acquired 35-49 0.094 2.21 0.079 2.72
Ever Acquired 50-60 0.127 1.86 0.079 2.72
Ever Upgraded 25-34 0.268 3.09 0.113 2.99
Ever Upgraded 35-49 0.12 1.87 0.113 2.99
Ever Upgraded 50-60 0.076 0.81 0.113 2.99
Orig Qual 1 0.031 0.78 0.034 0.87
Orig Qual 2 0.093 1.94 0.094 1.98
Orig Qual 3 0.185 3.42 0.186 3.45
Orig Qual 4 0.457 10.01 0.456 10.11
Stayers: Women: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Acquired(t-2) 0.013 1.4 0.007 1.65
Orig Qual 1 0.001 0.18 0 -0.03
Orig Qual 2 0 -0.04 -0.001 -0.2
Orig Qual 3 0.008 1.08 0.007 1.03
Orig Qual 4 0.01 1.74 0.009 1.65
Switching: Women: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Orig Qual 1 0.046 0.44 0.044 0.42
Orig Qual 2 0.009 0.06 -0.003 -0.02
Orig Qual 3 0.408 2.79 0.406 2.82
Orig Qual 4 0.515 4.36 0.495 4.44
Employment: Women: Selected Coefficients
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Upgraded(t) -0.577 -3.16 -0.404 -3.05
Ever Acquired 25-34 0.228 1.86 0.274 3.05
Ever Acquired 35-49 0.432 4.07 0.461 5.8
Ever Acquired 50-60 0.529 4.28 0.521 5.38
Ever Upgraded 25-34 0.258 1.1
Ever Upgraded 35-49 0.142 0.84
Ever Upgraded 50-60 -0.005 -0.02
Orig Qual 1 0.272 3 0.272 3.01
Orig Qual 2 0.155 1.21 0.154 1.21
Orig Qual 3 0.132 1.18 0.133 1.19
Orig Qual 4 0.174 1.81 0.171 1.84
Employment Effects in the Model
Unrestricted Restricted
Coeff z-stat Coeff z-stat
Movers
Men: Newly Employed -0.306 -2.14 -0.307 -2.36
Women: Newly Employed -0.214 -3.78 -0.206 -3.69
Employment
Employed 1991 1.836 20.59 1.823 20.68
Employed 1991 1.341 22.79 1.337 22.75
Wage Rate Profiles: Men
0
5
10
15
20
25
30
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Age
£ p
er h
our
2005
pri
ces
Qual 0 Qual 0 L Qual 0 U Qual1 Qual 1 L Qual 1 U Qual 2 Qual 2 L
Qual 2 U Qual 3 Qual 3 L Qual 3 U Qual 4 Qual 4 L
Wage Rate Profiles: Women
0
2
4
6
8
10
12
14
16
18
20
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Age
£ p
er h
our
2005
pri
ces
Qual 0 Qual 0 L Qual 0 U Qual1 Qual 1 L Qual 1 U Qual 2 Qual 2 L
Qual 2 U Qual 3 Qual 3 L Qual 3 U Qual 4 Qual 4 L
Average Returns to Life-long Learning: Men
Man Aged 25 Man Aged 40
Prior Education Level Full Effect Wages only Full Effect Wages only
No upgrading 0 8.74% 1.73% 17.47% 2.87%
1 5.73% 1.88% 11.98% 3.60%
2 4.37% 1.59% 9.31% 3.06%
3 4.65% 2.16% 9.73% 4.21%
4 6.62% 4.34% 11.99% 7.06%
Upgrading 0 16.68% 11.06% 23.52% 11.35%
1 12.92% 9.97% 18.57% 11.26%
2 11.62% 9.45% 16.17% 10.54%
3 10.12% 8.25% 15.90% 11.02%
Average Returns to Life-Long Learning: Women
Woman aged 25 Woman aged 40
Education Levels Full Effect Wages only Full Effect Wages only
No upgrading 0 37.46% 7.81% 45.67% 6.87%
1 20.36% 8.12% 23.32% 6.71%
2 20.11% 7.73% 23.22% 6.34%
3 20.67% 9.43% 23.14% 7.65%
4 20.29% 10.19% 22.47% 8.38%
Upgrading 0 51.62% 20.21% 58.99% 18.71%
1 32.03% 19.41% 33.66% 16.58%
2 32.29% 19.38% 34.24% 16.76%
3 31.26% 19.78% 31.76% 16.08%
Conclusions
• We find significant average impacts of life-long learning on the wage rates of both men and women, with the effects larger for women.
• However people with life-long qualifications are more likely to be employed than those without. This effect sharply increases the returns to life-long education.
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