Insights
In this guest blog, Aadya Bahl talks about the analysis done for the CEP report Hive of talent: what would it take to raise skills and productivity in Greater Manchester? published last week. For more information on available skills data, see our how-to guide Understanding local economic performance: Skills.
Skills gaps are often analysed through vacancy data, where shortages are estimated from hard-to-fill roles. What this misses is a more fundamental question: where do skilled workers come from, how are these sources changing and what can policy do if it wants more of a particular kind of worker?
Our recent report on Greater Manchester takes this pathway approach. This post sets out how we combined different data sources to produce a picture of local skills supply.
Starting with a demand target
We began by anchoring the analysis to a concrete objective. The Economy 2030 Inquiry estimated that Greater Manchester would need around 180,000 additional workers with level 4 and above qualifications to reduce its productivity gap with London (from 35 per cent to 20 per cent). This was our starting point. If this is the scale of change required, how much is GM already doing and what are the opportunities and threats it faces?
We split the 180,000 into degree-level and sub-degree components using qualification shares from the Labour Force Survey, giving three scenarios: lower bound, upper bound and average. The lower bound uses Greater Manchester’s qualification shares to split the two, the upper bound uses London shares, and the final scenario takes an average of the lower and upper bounds.
Mapping the pathways
Our analysis focuses on several supply pathways: people who grow up in Greater Manchester, people who move to the city-region for higher education and stay, adults who gain qualifications through further education later in life, and people who migrate for work or other non-education reasons. We considered all four of these for sub-degree level skilled workforce (ie., levels 4 and 5), and three, excluding adult education, for degree-level (ie., levels 6+).
For the first three pathways, the steps are the same. We need to know the size of the relevant cohort, the proportion who obtain the relevant qualification (i.e. degree-level or sub-degree level) and the share who are in Greater Manchester after qualifying. Using the number of people who stay in GM post-qualification, we calculate the annual flows for each pathway. The final channel is slightly harder to estimate given data availability, but we will come to that in the next section.
Once we have that data, we create baseline scenarios across the four pathways and update them (wherever possible) using recent data. We also undertake a reconciliation exercise by
matching our supply side inflows and outflows to the Annual Population Survey data on higher-skilled employment.
Estimating each pathway
No single dataset captures all channels, so we need to combine multiple sources.
The Longitudinal Education Outcomes (LEO) dataset is used to track locally educated cohorts from GCSEs through to later outcomes, allowing us to estimate both attainment and retention rates. This data then needs to be compared against other datasets to make sure it works for our purposes. As this data relates to older cohorts, we update headline figures using more recent Department for Education (DfE) data on GCSE entries and national participation trends. We also consider the contribution of those independently educated in Greater Manchester. We further use the DfE Progression to Higher Education dataset to split the LEO data into A-levels and sub-degrees.
For those moving to Greater Manchester for higher education, we use Higher Education Statistics Agency enrolment data. The key methodological decision here is how to treat international students: during the baseline period most had limited ability to remain in the UK post-graduation, whereas the introduction of the graduate visa route in 2021 substantially changed that. We apply different visa conversion rates for the two periods accordingly. We then apply the graduate retention rate to calculate how many stay in Greater Manchester post-qualification.
Adult further education is captured through DfE data on the number of learners aged 25+ in Greater Manchester each year, focusing on those achieving level 4+. This pathway is currently small, with provision skewed towards level 3.
As stated above, migration for non-education reasons is particularly challenging due to the discontinuation of Local Area Migration Indicators. We estimate qualification breakdowns using Labour Force Survey shares and treat post-2020 figures as indicative.
Assessing the opportunities and threats
The final stage of our analysis is to stress-test each channel against plausible policy changes and structural shifts, using the baseline estimates as the starting point.
For the local education and higher education pathways, we discuss what would happen if Greater Manchester matched London on attainment and retention. For the higher education pathway, things are complicated by changes to immigration which impact international students. We model a return to pre-2021 visa conversion rates as a downside scenario and show that improving the overall graduate retention rate in Greater Manchester, for example, would more than offset that loss.
Migration is harder to stress-test because the data is weaker. We model a halving of net international migration as a sensitivity exercise, which reduces the contribution of this pathway substantially.
For sub-degree qualifications, the opportunities and threats look quite different. Migration flows are small and declining further. The local and higher education pathways for sub-degree qualifications are also modest in scale. The main opportunity lies in the large pool of
people who hold level 3 qualifications but do not currently progress further – and is something the city-region can have direct influence over.
Why this matters for local policy
The value of building the analysis channel by channel, rather than treating the graduate workforce as a single aggregate, is that it separates questions that require very different answers. Raising attainment for local school leavers is a widening participation question. Improving graduate retention after university is primarily a labour market, housing, and transport question. Reorienting adult FE provision is a funding and curriculum question that Greater Manchester’s Combined Authority can act on directly through its devolved Adult Education Budget. Headwinds caused by changes in immigration policy are outside of the city-region’s control and are decisions taken nationally. Each requires different actors, different timescales, and different evidence bases.
The datasets the report draws on are all publicly available. Our report explains how to combine them into a coherent picture of local skills supply. The methodology adopted can be applied to other places and adapted to fit local contexts. The channels will be the same; the relative importance of each will differ. Places with smaller GCSE cohorts, weaker HE institutions, or greater dependence on international migration will face the same challenges in a sharper form. Understanding which channel is the limiting constraint, and which policy lever can realistically move it, is the starting point for any credible local skills strategy.
