Table 11 (along with the corresponding matrices for Med STEM, non-STEM, all QCF4+ graduates, and non-graduates) is used to project net flows among the nations and regions for 2020. Table 12 shows the net flows by region in 2002, 2007, 2011, 2020 and 2025. In order to translate the flows into numbers, the baseline, 2007 activity rates have been assumed. The net commute was calculated by taking the difference between the total number of Core STEM graduates working in the region and the total number of employed Core STEM graduates residing in the region. The data for 2002, 2007 and 2011 is based on historical LFS data. The data for 2020 and 2025 was projected using the population of QCF4+ graduates predicted by the UKCES Qualifications Model, assuming that a third of QCF4+ degree holders have a STEM degree (in line with the data from 2001-2011) and that the employment rate returns to 2007 pre-recession levels.
Table 12 Net Commuting of Core STEM graduates 2002 to 2025
6 Historical Forecast 2002 2007 2011 2020 2025 London 57,967 67,330 87,503 137,313 166,043 South East -25,346 -38,139 -52,140 -105,641 -142,558 East of England -13,014 -18,355 -23,005 -36,227 -38,729 South West -3,285 2,983 3,033 6,464 9,059 West Midlands 7,422 5,635 -1,433 -15,553 -22,986 East Midlands -16,004 -18,708 -22,250 -22,572 -21,406 Yorkshire and the Humber -3,262 2 2,501 13,434 18,356 North West 172 -4,612 -743 2,923 2,207 North East -3,012 -2,965 -8,792 -5,607 -7,172 Wales -7,904 -584 1,306 21,351 32,633 Scotland 4,123 6,913 -2,424 4,446 4,967 Northern Ireland -276 0 -1,043 -332 -415 England 1,639 -6,828 -15,325 -25,466 -37,185
Sources:LFS; 20CurrentResidencebyCurrentWork.xls and STEM Time Series Model
(national and regional).xls
Using the net flows at least allows the present study to examine the effects of commuting on the market outcome in different regions and explore, in particular, the effects of London on other regions.
5
Market Supply, Demand and Imbalances
Chapter Summary
There is some evidence of a link between vacancy rates and Core STEM densities, however this depends upon the method of analysis used.
Estimates of vacancy ratios rates generally do not suggest a higher vacancy rate for Core STEM vacancies (in all occupations) or for vacancies in STEM occupations only.
Supply and demand calculations for 2020 under both the “2007” and “2011” scenarios do not suggest an overall shortage of STEM graduates (in terms of numbers) in most regions or nations of the UK.
Vacancies for Core STEM degree holders are more likely to be hard-to-fill than other vacancies.
Mismatches between supply and demand for Core STEM appear to be more about lack of suitably qualified candidates rather than a numerical shortage of STEM degree holders.
5.1
Introduction
The main underpinnings for the present projections are the qualification projections of the main Qualifications Model developed for the UKCES, which have been up-dated annually over a number of years (see, for example, Ambition, 2020 – 2009 Report and Ambition 2020 – 2010 Report, UKCES 2010 and UKCES 2011).
The latest version of the model, produced in June 2013, provides qualification proportions and numbers by the levels of the Qualifications and Credit Framework for 2020 (and 2025) (see Bosworth 2013a, Bosworth 2013b and Bosworth 2013c). For the present study, these numbers are broken into three degree and above (QCF4 and higher) groups using the trends in Med STEM, Core STEM and non-STEM groups, as well as a non-degree group (see Figure 5). Section 5.2 discusses the historical evidence of shortages amongst these four groups, based upon an analysis of the NESS / ESS surveys carried out by UKCES.
Before briefly outlining the modelling of supply and demand (Sections 5.3 and 5.4), it is worth saying something about the role played by the economy. The prolonged recession that has occurred at the end of the data period means that any projections made on trend data will almost certainly produce a bleak view of the future. For this reason, the baseline projection in the present study simply assumes that a recovery is made from the economic activity and vacancy rates of 2011 to those of 2007. While this seems a modest improvement, at the time of writing there is still some uncertainty that this will be achieved. In addition, however, the model explores a number of more and less ambitious scenarios.
The demand side of the equation is formed by employment and vacancies. Baseline overall employment at the UK level is fixed by applying the 2007 employment rate to the ONS (2010 based) population estimates (see Figure 5). Vacancy ratios, which are an important element in determining demand are significantly higher for 2007 than 2011. The growth in population and the restoration of the 2007 employment and vacancy rates combine to produce a significant rise in demand. While there are no published vacancy rates for different degree holders or different levels of qualification, these are estimated using econometric techniques and by a proportional allocation method. While the results of both methods are interesting, they should be treated with caution for the reasons discussed below.
The supply side of the equation is formed by employment plus the unemployed (again, see Figure 5). While the recession appears to have shifted a proportion of newly qualified graduates into inactivity (see Section 3.3.1), overall inactivity rates for all individuals aged 16 to 64 increased more modestly between 2007 and 2011. The overall population projections are the ONS (2010 based) population estimates for the UK, nation states and regions. These have already been translated into supplies of individuals at different qualification levels in a series of modelling activities undertaken for the UKCES, which gives a projected breakdown of the proportions and numbers of individuals holding QCF level four and higher.
Using this baseline scenario, a variety of trends are fitted to the data on both the demand and supply sides at the UK, national and regional levels, that allow a picture of the market for Core STEM to emerge. As supply is measured using place of residence and demand is measured using place of work, commuting patterns play an important role in resolving potential mismatches in supply and demand. Commuting is insignificant at the UK level, but of considerable importance at the regional level. By dealing with commuting patterns directly, it is possible to see how some regions appear to be advantaged and others disadvantaged by net migration.
Section 5.2 examines the vacancy rates for STEM and non-STEM groups, using econometric techniques and a proportional method. Section 5.3 outlines the modelling of future supply and Section 5.4 discusses demand. Section 5.5 brings the supply and demand estimates together and discusses the magnitude and nature of the market imbalances suggested by the model. Section 5.6 looks at supply and demand for Core STEM occupations in England.