LOOKING BACK: ARE CAREER TALKS WITH OUTSIDE SPEAKERS ASSOCIATED WITH HIGHER WAGES? AN ANALYSIS OF THE BRITISH COHORT STUDY

Gathered by: Elnaz T. Kashefpakdel, Christian Percy

We’re testing a principle from the literature, that there should be a link from employer contacts to labour market outcomes

School-mediated employer contact …• Employer mentoring• Enterprise education• Career talks from

external speakers• Work experience /

shadowing• Work-place visits

… through several possible channels• Better understanding

o Which career you might want to do

o Career pathways; how to succeed

o What you are well-suited to

• Better networks to aid labour market entry + signalling

• More work-focused attitude

… can support labourmarket outcomes …• Less time

unemployed• Higher wage

outcomes• More job satisfaction• Making the right

career choices earlier (balancing achievability, ambition, flexibility etc.)

Two studies quantify this theorised link to wage outcomes, but with uncertainties for the broader UK policy context

Study• Mann & Percy, 2013, Journal of

Education and Work• 169 full-time 19–24-year-old

UK workers on annual salaries• YouGov survey in 2010 of

1,002 respondents

Result• 4.5% wage increase link to

each additional school-mediated employer contact from 0 to “4 or more”

• Controls used: Highest academic qualification achieved, gender, ethnicity, school type and region

Limitations in the UK context• Small-scale limited

analytical options, limited control variables

• Relies on recall of school days

• Student choice to participate in some activities means wage premium may be driven by proactive personality type not added-value of activity

• Career Academies programme evaluation (Kemple 2008)

• 1,764 of 15-18 years olds young people in 2008

• 11% potential wage uplift for the alumni

• Experimental design used enabling robust controls

• US context • Highly specialized, intense,

curriculum-linked employer contact programmes is not current UK policy

The 1970 British Cohort Study provides a large, robust longitudinal dataset to explore pathways to labour market

Survey background

• Follows ~17,000 people born in England, Scotland and Wales in a single week of 1970

• Data is available at Birth, age 5, 10, 16, 26, 30, 34, 38 and 42 - most recent data from 2012

• We gather data for background variables at birth to age 16

• Survey attrition means ~48% loss of respondents from birth to age 26

Birth 5 10 16 26

16,571

12,98114,350

11,206

8,654

Survey attrition rate

Longitudinal observed sample

Exploring Variables of Interest

Full-time weekly income in 1996 (age 26) [nominal £]

0 - 50 50 - 100

100 - 150

150 - 200

200 - 300

300 - 400

400 - 500

500 - 600

600 - 700

700 - 800

800+0

500

1000

1500

2000

2500

210432

1232

19192066

544

136 50 30 5 18

Weekly income at age 26

• Following Mann & Percy part-time wage earners were excluded (n=710) in order to identify a more internally comparable set of labour market participants

• Approximately 38% of full time employed individuals reported a weekly income between £200 and £300; Male earns more than female on average (£238 vs. £192 per week)

• Academic ability at age 16 is strongly associated with earning at age 26; the high achievers on average earn more. (on average 7%)

• Young people ‘s wage from more privileged families is higher than families with lower social classes ( on average 4.3%)

Career talks were the most common employer activity and afford the best opportunity to add to the UK research base# Career talks with outside speakers aged 15-16

• 66% did at least one, with many doing two or more, allowing us to test the idea: “more is more”

• Typically held during school day, decided by school – less individual agency

None

1 2 3 4 5 6 plus

951 921

423

17991 70

190

# Work experience placements

• 33% participated but few did 2+. Limited variation is a restriction on detailed regression analysis

• Prior to policy decisions widening work experience participation, so individuals had more choice about participation

None 1 2 3 or more

4218

1832

173 56

Workplace visits with school

• Simplistic binary variable• BCS questions do not allow us

to unpack different types of visit, e.g. vocational course-linked, careers linked or research field trips, which could obscure the theorised link between employer contact and income

No Yes

4092

1842

Empl

oyer

eng

agem

ent a

ctiv

ities

m

easu

red

in B

CS

Exploring career talks at year 10 & 11

• On average young people attended more talks at year 10 comparing to year 11

• The most frequent number of talks is 1 and 2 but in year 10 an 11 there are participants who did more than 6 talks

0 1 2 3 4 5 6 plus0

5

10

15

20

25

30

35

18.3

31.8

23.7

10.3

5.53.2

7.1

33.7 32.6

15.0

6.3 6.7

Year 10Year11

Each extra career talk in Year 10 is associated, on average, with a 0.8% increase in wage at age 26 - no controls in placeDirect relationship – Career talks in Year 10 vs weekly income age 26

On average, benefits associated with careers talks begin to manifest at 5 talks or more

Regression analysis on log wage (ln)

Co-eff: 0.008Stnd-error:0.003P-value: 0.004R^2 0.6%N: 1,409Bubble size indicates sample size at that point. Linear trendline applied by Excel bubble chart algorithm

With control variables, the average effect associated with an extra career talk increases to 1.2%, significant at 5% levelControl variables reviews (Bold = Included in final analysis)

Results

Academic attainment

Socio-economic status

Early home learning environment

Demo-graphics

• Teacher assessment of academic ability at 16• Maths - CSE/O-level results• Highest level of qualification at 26

• Frequency of parents reading to child age 5• Mother’s interest in child’s education age 5• Cognitive assessment age 5 (human fig. drawing)• Amount of TV watched age 10

• Father socio-economic status• Mother socio-economic status• In receipt of council housing (or benefits)

• Gender• Whether has a UK parent

Regression : Number of talks at year 10 vs. Ln(wage) at age 26

Co-eff: 0.012Stnd-error: 0.003P-value: 0.000

R^2 20.6%N 740

At year 11, the direct relationship is still present at 0.3% on average, but much weaker and less statistically significantDirect relationship – Career talks in Year 11 vs weekly income age 26

Regression: Analysis on log wage (ln)

Co-eff: 0.003Stnd-error: 0.002P-value: 0.145R^2 0.1%N: 2,854

With control variables, the average effect associated with an extra career talk at increases to 0.5%, significant at 10% level

Control variables reviews (Bold = Included in final analysis1))

Results

Academic attainment

Socio-economic status

Early home learning environment

Demo-graphics

• Teacher assessment of academic ability at 16• Maths - CSE/O-level results• Highest level of qualification at 26

• Frequency of parents reading to child age 5• Mother’s interest in child’s education age 5• Cognitive assessment age 5 (human fig. drawing)• Amount of TV watched age 10

• Father socio-economic status• Mother socio-economic status• In receipt of council housing (or benefits)

• Gender• Ethnicity

Regression : Number of talks at year 11 vs. Ln(wage) at age 26

Co-eff: 0.005Stnd-error: 0.002P-value: 0.054

R^2 20.6%N 740

Individuals who found the career talks very useful display a stronger wage premium, but sample sizes are small

Did you find the careers talks useful?Regression output, Co eff 1)

Not helpful at all

Not very helpful

Quite helpful

Very helpful

0200400600800

1000120014001600

79

446

1521

598

Model Did not find helpful

Found very helpful

Yr 10 – No controls 1.7%** N = 144

1.1% *N = 231

Yr 10 – With Controls 1.0% N = 85

1.5%** N = 117

Yr 11 – No controls 0.4% N = 423

0.6% N=501

Yr 11 – With Controls 0.3% N = 234

1.1% **N=243

1) If we include Quite Helpful alongside Very Helpful answers as positive experiences, the slight difference between the two cohorts shown in this table disappears. Both analyses are indicative only due to the small sample sizes. * significant at 10% and ** significant at 5%

Concluding remarks We used the large-scale, British longitudinal dataset (BCS70) to explore whether careers

talks with outside speakers in the mid 1980s have a positive association with the wages of full-time employees in 1996

We found a strong association between the number of career talks and wage premium. Results are statistically significant at the 5% or 10% level

Earlier is better, with a 1.2% wage premium for each talk in Year 10 vs 0.5% for each talk in Year 11

Analysis of the direct relationship suggests that the beneficial association begins to manifest from around 5 or more career talks on average. This may relate to the general need for repetition in education for learning and attitudinal shift or the need to hear about several pathways before one happens to gel

Concluding remarks

Individuals who found the career talks ‘very helpful‘ overall were more likely to earn more than those who did not find them useful, given the decreased sample size

Comparison with the literature adds weight to the intepretation via social capital and via weak ties, in particular the value of trusted, non-redundant information that can be obtained through multiple, diverse channels, even in brief encounters: If done right, a lot of a little can make a big difference.

Given how careers talks with outside speakers, particularly in significant numbers, are coordinated within schools, our findings are likely to reflect the influence of talks taking place in the context of overall school-based and professional careers provision.

What Next...

Test the role of careers lessons/meetings directly, in order to better isolate the potential added value of outside speakers (using BCS)

Extend the analysis with new control variables such as region and local education authority to account for differences in employment by area

Conduct the analysis with a more recent dataset such as Longitudinal Survey of Young People in England, when the new cohort data are released

How does the combination of these engagement activities affect young people‘s position in labour market in terms of wage premium, both at 26 and at later stages

Other labour market outcomes to be tested include longest period unemployed, job satisfaction and job status

We welcome your comments and suggestions

• Control variables descriptiveAppendix

Control variable descriptive

Score PercentageO level A 11O level B 14.6O level C/ CSE 1 22O level D/ CSE 2 15.5O level E/ CSE 3 17.7CSE 4 12.8CSE 5 5.8Fail 0.5

Academic ability assessed by teacher at 16 Standardised Math Score age 16

Assessment PercentageTop 5% 4.8Well above average

12.7

Above average 26.9Average 34.6Bellow average 13.5Well below average

5.4

Bottom 5% 1.7*N=3716 *N=5428

Control variable descriptive

Score PercentageI 7.6II 28III non-manual 9.7III manual 38.1IV 8.8V 2.3Student 2Dead 3.5

Highest level of qualification at age 26 Father social class

*N=6735No Qualification

CSE 2-5/NVQ1

O Level/NVQ2

A Level/NVQ3

Higher Qual/NVQ4

Degree +/NVQ5 OR 6

0 5 10 15 20 25 30 35 40 45

6

17

41

11

4

21

Percent...*N=8399

Control variable descriptive

Sex PercentageFemale 49.9Male 50.1

In receipt of government benefit? Gender

*N=11615

Yes

No

0 10 20 30 40 50 60 70 80

25

75

*N=9358