Local Skills Report Evidence Base – Skills Supply Analysis

Jobs by Industry, Emsi

Emsi employment data contrast the proportion of employment in different industries in the West Midlands to the UK average. The figures are based on the Location Quotient, which simply takes the former and divides it by the latter as a ratio:

Description	UK	Black Country LEP	GBSLEP	CWLEP
Administrative and support service activities	1	0.79	1.59	1.01
Transport and storage	1	1.32	1.18	1.40
Manufacturing	1	1.82	1.16	1.43
Accommodation and food service activities	1	0.80	1.01	1.06
financial and insurance activities	1	0.64	0.99	0.67
wholesale and retail trade; repair of motor vehicles and motor cycles	1	1.25	0.99	1.07
education	1	1.11	0.98	1.09
real estate activities	1	1.19	0.96	0.71
human health and social work activities	1	1.18	0.95	0.81
other service activities	1	0.90	0.94	1.03
professional, scientific and technical activities	1	0.42	0.84	0.95
public administration and defence, compulsory social security	1	0.73	0.84	0.70
arts, entertainment and recreation	1	0.90	0.83	1.05
construction	1	0.94	0.83	0.71
water supply	1	1.32	0.8	1.47
electric, gas, steam and air supply	1	0.34	0.38	0.66
agriculture, forestry and fishing	1	0.10	0.36	0.61
mining and quarrying	1	0.03	0.25	0.46

Table 6: Comparison of each Local Enterprise Partnership to the UK in terms of concentration of employment by industry. Sourced from Emsi, 2021.

By this measure the Black Country is as different to the rest of the region as it is from the UK average as a whole, being considerably ahead in retail trade and motor vehicles, real estate activities, transportation and storage, but most of all manufacturing, which as an 82% larger share of employment than the UK average. CWLEP and GBSLEP also outperform the UK mean by 43% and 16% respectively.

The region as a whole considerably outstrips the UK average on administrative and support services owing to the strength of GBSLEP. Within the region, CWLEP is greatly over- represented in electricity, gas, steam, and air conditioning supply (332% of UK) and water and waste management (47%.)

Early Years Education

Comparison of early years education in regions on the basis of the IDACI (Income Deprivation Affecting Children, an metric which forms part of the Index of Multiple Deprivation) makes clear the extent of the disparity between the advantaged and disadvantaged. In the West Midlands, in the most disadvantaged decile

62% of young pupils reach the ‘expected level of development’ (a metric which includes written and verbal communication and numeracy), while 79% in the least deprived decile reach this level. This gap is wider than in London and the East of England, but narrower than in all other regions.

Row labels	0-10%	90-100%	Attainment gap
North east	62	83	21
North west	59	80	21
Yorkshire and the hunter	59	80	21
East Midlands	60	78	18
West Midlands	62	79	17
East of England	63	78	15
London	69	82	13
South East	62	81	19
South West	61	79	18

Table 7: English regions are compared by
the gap in the number of young pupils reaching ‘an expected level of development’ by age five, between the lowest and highest deciles on the metric of Income Deprivation Affecting Children (IDACI.) DfE, 2018/19

A Level Attainment

Looking at the proportion of level 3 students who attain at least two A Level qualifications, West Midlands slightly underperforms (at 78.2%) the England mean of 79.5%. There is a very high degree of variance between Local Authorities in the region, with only 69.7% of students in Wolverhampton reaching this level, but 88.3% in Solihull.

There is also a significant disparity within Local Authorities between students eligible for Free School Meals and ineligible. This gap is biggest in Coventry, where 88.3% of non-FSM eligible pupils attain two A Level qualifications , but only 73.6% of those eligible.

Row labels	% two a levels (FSM)	% two a levels (average)	Disparity	Average score (FSM)
Birmigham	83.9%	88.5%	4.6%	B-
Coventry	73.6%	88.3%	14.7%	C+
Dudley	92.0%	96.2%	4.2%	B-
Sandwell	66.8%	75.7%	8.8%	C+
Solihull	86.5%	92.5%	6.0%	C+
Walsall	75.2%	84.0%	8.8%	C+
Wolverhampton	74.1%	82.9%	8.7%	B-

Table 8: Comparison between West Midlands Local Authorities by the proportion of pupils who attain at least two A Levels, by Free School Meal eligibility, and average scores. DfE, 2020/21.

Dudley is by far the best-performing Local Authority by this measure, with the equivalent figures being 92% and 96.2%. Note that FSM-eligible students in Dudley have higher attainment by this metric than even the student average in the other Local Authorities. However, the average grade of B- in Dudley

is lower than the B reported for all Local Authorities other than Dudley and Sandwell. This suggests that grades awarded in Dudley were more tightly clustered around the middle than in other Local Authorities. Future years of data will reveal how much of this difference can be attributed to the unique situation for assessment during the pandemic.

Trends in FE and Apprenticeship Supply As a result of the pandemic, recruitment into apprenticeships and Further Education in 2020 was significantly below 2019 levels, with August-October, the busiest period for new starts, seeing 171,269 new FE course enrolments and 20,329 apprenticeship starts, declines of 17.5% and 21.1% respectively on 2019. These declines would likely have been more severe if the busiest period of recruitment had not, fortunately, been between the two periods of winter lockdown.

Analysis by Prior Attainment

By comparing the level of study of our new
FE students and apprentices to the level of qualification they held before, we can get a sense of the value added to individual students’ prospects, and who is reached or not reached by provision.

The grid below compares the qualification being completed by an FE student to their previous level of study. As one might expect, most students had a prior attainment which was either one level below their current course, or at the same level:

Prior attainment	Entry level	Level 1	Level 2
No qualifications	12,524	5,593	8,765
Entry level	6,689	3,102	3,402
Other qualifications below level 1	2,096	706	984
level 1	2,902	7,314	21,115
full level 2	1,288	5,109	19,313
full level 3	491	1,395	4,909
level 4	105	324	903
level 5	86	222	775
level 6	261	481	1,477
level 7 and above	99	184	535

Level 3	Level 4	Level 5	Total
2,191	209	30	29,312
763	38	-	13,994
140	7	1	3,934
4,788	206	11	36,336
23,987	970	68	50,735
3,551	2,247	182	12,755
269	332	41	1,974
271	251	84	1,689
720	597	590	4,126
332	202	272	1,624

Table 9: Before-and-after analysis of prior attainment in the FE system, where rows correspond to the prior attainment and columns to the level of the course they are not enrolled in. Note the diagonal trend implying most students are studying at an equivalent or higher level, except at Level 5.

However, there is one notable point of departure: The limited amount of Level 5 provision is almost entirely taken up by students who have already studied to a higher level (6 or 7.) This discontinuity suggests an area in which further work is needed to ensure that there are no rungs of improvement missing in the Further Education ladder, and that high- level courses are deployed to full effect.

For FE students in general, the most common prior skill levels are Level 2, Level 1, and No Qualifications, with there being a low number of highly skilled students first because they are less likely to require training, and second because little capacity for advanced vocational training currently exists in the FE system.

The situation for apprenticeships is not greatly different, however it should be noted that there are more students educated to Level 6 starting apprenticeships (1539) than No Qualifications and Entry Level put together (1105) or Level 1 alone (1201).

This indicates that while the system does a relatively good job of reaching people currently educated to levels 2 and 3, people below this level have relatively little prospect of getting on an apprenticeship, especially when overall numbers are down this year. Meanwhile, a significant number of highly educated students are making use of higher apprenticeships.

This fact may be part of the puzzle of why apprenticeships do fairly well at reaching different ethnic groups but are less effective at reaching low income and low skill groups.

Prior attainment	intermediate	advanced	higher	total
no qualifications	428	386	138	952
entry level	42	104	7	153
level 1	672	453	76	1201
full level 2	786	1822	592	3200
full level 3	317	997	1629	2943
level 4	15	63	284	362
level 5	23	57	237	317
level 6	48	238	1253	1539
level 7 and above	10	52	473	535

Table 10: Prior attainment grid for apprenticeships, showing a somewhat weaker relation between the level of prior attainment and the level of the course now studied. Note the large number of Higher Apprenticeship starts by people already educated to Level 6. Note that intermediate, advanced, and higher apprenticeships are equivalent to NVQ levels 2, 3, and 4.

Detailed Ethnic Groups and Further Education Attainment by Level

The detailed crosstab Figure shows the breakdown of age and ethnicity by level of study, averaged over the last three years and suggesting that both factors have a significant effect on level of study:

Female Asian/Asian British	Entry(%)	1	2	3	4
other	45.5	16.7	18.5	9.0	0.5
Bangladeshi	41.7	13.2	16.5	16.8	1.3
Chinese	38.6	13.9	16.7	13.2	0.5
Indian	23.6	15.7	26.3	15.0	0.6
Pakistani	25.3	14.5	25.8	19.9	0.4

Female Black	Entry	1	2	3	4
african	39.3	17.1	22.8	11.8	0.8
other	21.5	19.1	30.0	16.0	1.2
Caribbean	10.1	19.4	34.9	18.6	1.3
mixed	13.9	17.5	33.1	21.2	0.8
unknown	27.6	16.7	24.0	15.1	0.6

Female

other ethnic group

Entry

1

2

3

4

other

45.8

15.5

18.6

9.9

0.4

Female White	Entry	1	2	3	4
other	30.3	16.3	26.4	12.5	1.6
British	8.0	16.0	33.7	20.3	1.0
Gypsy or Irish traveller	23.6	23.9	26.2	10.0	0.5
Irish	6.4	14.1	33.5	13.4	1.7

Male Asian/Asian British	Entry	1	2	3	4
other	39.4	16.6	23.4	10.8	0.7
Bangladeshi	23.0	15.5	27.0	21.4	2.8
Chinese	28.7	12.9	17.9	23.9	1.3
Indian	16.1	17.2	32.6	18.5	0.8
Pakistani	12.4	17.2	34.5	23.2	0.8

Male Black	Entry	1	2	3	4
african	30.7	18.1	27.2	13.8	0.9
other	18.9	20.9	32.4	13.7	1.0
Caribbean	11.2	24.6	36.8	12.7	1.1
mixed	13.6	21.7	34.3	15.6	0.8
unknown	23.5	15.9	24.2	24.7	1.5

Male other ethnic groups	Entry	1	2	3	4
other	41.2	15.8	22.8	10.8	0.5

Male White	Entry	1	2	3	4
other	23.2	16.8	30.1	13.5	2.4
British	10.1	20.8	34.3	14.8	1.0
Gypsy or Irish Traveller	23.7	25.1	32.8	3.6	0.2
Irish	8.8	23.0	33.9	10.8	0.5

Table 11: Summary of gender, ethnicity, and level of FE course the student has started. Note the dividing line between female and male students. Percentages are totalled by row, and do not reach 100% due to a small proportion of unclassified and missing data. Data references the first half of the 2020/2021 academic year, running from August 2020 through 2021. Most FE students enrol during this period.

For female students, 45.5% of students registered as ‘any other Asian Background’ (which includes those who are Asian but not Bangladeshi, Chinese, Indian, or Pakistani) and 45.8% ‘Other Ethnic Group’ (which includes students of Arab descent and others not classified) were studying at Entry Level, these two intersections of gender and ethnicity being the most concentrated at the lowest level of study of all groups. For men, the same two ethnicities were concentrated at the lowest level of provision, but the share of each was lower (39.4% and 41.2% respectively.)

In general, women are more likely to be studying at entry level than men, with the gap particularly large for students of Asian descent (for instance, 25.3% of female Pakistani students were at entry level, versus 12.4% of male Pakistani students.) The gap is also observed for students of Any Other White Background (30.3% and 23.1%) and Black African students (39.3% and 30.7%) but not other white and black ethnicities.

This gender gap at the top levels of provision is also marked. Male Bangladeshi students are the most concentrated of all groups in Level 4 provision (2.8%). Female Bangladeshi students were well behind their male counterparts at Level 4 (1.2%) but still ahead of most other groups. Students of Any Other White Background were the next most concentrated in Level 4, with 1.6% of women in this group at Level 4 and 2.4% of men. The gap between female and male students of Irish background at Level 4 was very pronounced (1.7% and 0.5%, suggesting women in this group do a
lot better.) The groups least represented at this highest level of study were those from Pakistani, Gypsy or Irish Traveller, or other unclassified ethnicity.

Students of Black/African/Caribbean/Black British ethnicities are the most represented in Level 2 provision, known to be in greater demand in the region than Levels 1 and 3, indicating that the FE system is making a significant contribution to employability for this group.

In summary, Female students of Asian descent, and Black African, Arab, and Gypsy or Irish Traveller groups in general, were the most concentrated at the lowest end of provision, and in this sense the most disadvantaged. Male Asian students, particularly Male Bangladeshi students, are more likely to study at higher levels, and this gender gap within Asian students is perhaps the most salient fact observed in the data. Both white and black students are generally more likely to be on Level 2 courses, while Asian students as mentioned are more dispersed across levels based on their gender. However, within all these general statements is a great deal of variability.

Enrolment by Age Group

The age distribution is notably different between FE and apprenticeships, with under-25s comprising 73.4% of new FE students but only 44.8% of apprentice starts:

Age	Apprenticeships	Further Education
Under 16	0	1256
16	1,334	61,432
17	1,895	41,215
18	2,830	21,284
19-23	7,327	22,097
24	972	2,167
25-30	4,944	12,300
31-49	10,804	33,518
50-64	1,926	7,508
65+	10	931
Total	32,042	203,708

Table 12: Age distribution of new starts on Further Education and Apprenticeship courses.

	<16	16	17	18	19-23
Agriculture, Horticulture, and Animal care	1.3	0.7	0.8	0.8	0.5
Arts, media and publishing business, administration and law	4.9	5.3	3.9	3.8	2.8
construction, planning and the built environment	0.2	6.8	5.2	3.9	6.4
education and training	1.2	3.1	3.2	3.3	4.4
engineering and manufacturing technologies	0.0	0.2	0.2	0.3	1.0
health, public services and care history,	4.5	3.3	3.3	3.4	3.6
philosophy and theology	2.1	8.2	8.7	8.5	7.0
Information and communication technology	0.1	1.8	0.9	0.3	0.2
languages, literature and culture	6.2	4.2	3.6	3.1	4.5
leisure, travel and tourism	12.1	8.7	8.7	9.0	5.2
preparation for life and work	3.7	2.9	2.7	2.3	1.7
retail and commercial	38.5	28.6	38.0	41.5	45.8
enterprise	0.1	2.7	3.0	3.1	4.1
science and mathematics	22.5	18.2	14.8	14.6	8.3
Social Sciences	2.5	4.8	2.9	1.3	1.6

24	25-30	31-49	50-64	65+	Total
1.0	0.5	0.4	1.0	1.0	0.7
2.1	1.7	2.5	5.6	21.5	4.0
8.3	7.0	6.1	7.9	1.5	6.0
7.0	8.0	5.4	4.0	1.2	4.0
1.9	2.1	2.2	1.9	0.8	0.8
3.6	3.5	2.2	3.7	1.1	3.2
8.1	9.1	9.3	9.8	2.3	8.4
0.1	0.2	0.3	0.5	1.4	0.9
5.9	5.5	6.9	9.4	10.2	4.8
3.0	3.5	2.7	4.3	23.5	6.9
1.8	1.1	0.8	1.9	13.5	2.2
43.1	45.5	50.3	39.1	17.6	38.9
5.2	5.0	4.3	4.6	1.1	3.4
4.3	3.7	2.8	0.9	0.3	11.8
1.1	1.5	1.1	1.2	0.2	2.7

Table 13: Further Education and apprenticeship courses are shown together in this table, which gives the proportion of each age group which study each course. August 2020 to January 2021.

There are some significant differences by subject of study:

Preparation for Life and Work, including language and employability skills, is by far the most common course taken within all age groups except the over-65s. Arts, - Media, and Publishing as well as Languages, Literature, and Culture follow a bimodal distribution, where students aged either 16-23 or 65+ are the most likely to be taking these courses.

The high concentration of over-65s taking these subjects are likely doing so more for general enrichment and interest rather than for employability reasons.

The greater concentration of science and mathematics in younger age groups reflects the fact that this subject area is dominated by GCSE retakes.

ICT provision is more concentrated in 50+ age groups, and is likely to benefit these groups

in terms of general quality of life and access to services as well as improving employability, where the industry the student has previously worked in is becoming more digitised.

Engineering, Construction, and Business and Administration provision is split fairly evenly across age groups without any real notable differences.

FE Subject by Gender

Within FE, the discrepancies between female and male students are in some cases very large. An almost negligible (0.3%) proportion of female students study Construction, while 8.2% of men do. The gap is almost as large in Engineering and Manufacturing at 0.9% and 5.7% respectively. A larger proportion of male students are in travel and tourism also (3.1% vs 1.4%.) Female students are much more concentrated than men in health, public services and care (12.4% vs 4.0%) and retail (4.4% vs 2.3%) courses.

	female	male	difference
agriculture, horticulture and animal care	0.9	0.6	0.4
arts media and publishing	4.6	3.2	1.4
business, administration and law	5.8	6.3	0.5
construction, planning and the built environment	0.3	8.2	7.9
education and training	1.2	0.3	0.9
engineering and manufacturing technologies	0.9	5.7	4.7
health, public services and care	12.4	4.0	8.4
history, philosophy and theology	1.0	0.7	0.3
infomation and communication technology	4.0	5.6	1.6
languages, literature and culture	6.4	7.4	1.0
leisure, travel and tourism	1.4	3.1	1.6
not applicable	1.3	1.4	0.0
preparation for life and work	39.5	38.1	1.4
retail and commercial enterprise	4.4	2.3	2.1
science and mathematics	12.2	11.3	0.9
social sciences	3.3	2.0	1.3

Table 14: Percentage of students of each gender studying each subject area, with differences. August 2020 – January 2021.

Graduate Retention

There are marked differences in the attraction and retention of both students and recent graduates between UK regions. In the typology set out below, the West Midlands fits into the mild brain drain category, due to its successful attraction of students to its university system but subsequent loss of many young graduates to other parts of the UK:

Typology	Regions	Description
1	North East, Yorkshire and the humber	Regions that attract and retain students but export new graduate workers - brain drain
2	East Midlands, West Midlands	attractors of students but exporters of new graduate workers - brain drain
3	London	Regions that attract and retain students but export new graduate workers - brain drain
4	East of England, south east, south west	Regions with low retention and high attraction of both students and graduate workers - high mobility
5	North west, Wales, Scotland, northern island	Regions with high retention and low attraction of both students and graduate workers - low mobility

Table 15: Summary of the five situations for graduate retention and attraction. Note that only London truly gains.

The centralisation of opportunity in the UK is reflected in the fact that only London is truly a brain gain region, and in this sense the West Midlands is doing no worse than most other regions, and better than some (the North East, Yorkshire and the Humber.) The pathway to brain gain for the West Midlands would be to continue to attract the large number of students it does, but hang on to more of them, particularly graduates in STEM.

Findings of Graduate Retention Analysis

Inter-regional mobility is higher for students than for new graduate workers, as regions retain, on average, more new graduate workers after their studies (61.1%) than residents making the transition to becoming university students (56.3%).
There are remarkable regional differences in terms of both student attraction and graduate employment. For instance, there is a clear North-South divide in the graduate attraction figures. In particular, of the total 2018/19 university graduates who moved to a different region for work, 65.3% moved to London, the East of England, the South East and the South West, whereas only 15.9% migrated to the northern English regions.
Graduate retention rates are higher for women than for men. Specifically, the rates for women in the English regions range from 44.1% in the East Midlands to 75.3% in London, while the corresponding rates for men vary between 34.6% and 72.8% in the same regions (based on the 2018/19 cohort of graduates who were interviewed fifteen months after finishing their studies).
Similarly, the likelihood of staying local is higher for new graduate workers who attended a postgraduate taught course (standing at 63.4% on average in the UK) than those who hold only a first degree (54.4%), whereas the attraction rates are more potent among the first-degree graduates (45.6%).
Graduates with a qualification in Arts, Humanities, and Education are, by far, more likely than STEM and LEM graduates to stay in the same region of study for work. Conversely, regional attraction rates are generally higher among STEM graduates (standing at 46.6% on average in the UK) than those with higher education qualifications in other subject areas.

This picture is partially associated with the increasing demand for particular high- level skills across regions.

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West Midlands Local Skills Report Annex B - Evidence Base 2022