02Hotspots matter to the national economy

Using the methodology set out above, this section sets out how many hotspots there are, discusses their characteristics, and highlights their contribution to the national economy.

There are many hotspots of innovative activity across the country

There are 344 hotspots across the UK. Within these hotspots there were 18,468 new economy firms. In absolute terms, this is a small number, accounting for just 0.6 per cent of the UK’s businesses, but there are several things to note. The first is that their small size follows from their definition – this approach examines a nascent part of the economy where growth is most likely to come from in the future. The second is that they punch above their weight. According to Centre for Cities’ broad estimates, these 0.6 per cent of all businesses, in hotspots covering just 0.1 per cent of land, already account for around one per cent of national output – £18.5 billion in 2019 – and 200,000 jobs.14

Places with hotspots are more productive and have grown faster than the rest of their region

Data limitations mean that it is not possible to observe the impact of firms in hotspots precisely. However, by linking hotspots to small geographies (see Box 2) it is possible to get a sense of the economic performance of places in which hotspots exist over the medium term. Because the GVA data used in this analysis are experimental, the neighbourhoods with hotspots are aggregated together at a regional level to improve reliability.15

Box 2: Linking hotspots to other geographies

The tight distance thresholds used in the identification of hotspots makes it possible to align hotspots with Lower Super Output Areas (LSOAs) and their closest equivalents in Scotland and Northern Ireland.16 LSOAs are neighbourhood sized geographical units with an average population of 1500 spread across 650 households. Linkages with LSOAs facilitate estimation of the productivity and output growth of the places in which hotspots are located. They also enable logistic regression analysis to explore why hotspots exist in particular neighbourhoods.

In order to reduce the chances of erroneous linking, LSOAs were only considered to be part of a hotspot if they contained a large enough share of that hotspot’s firms. Because hotspots vary significantly in size, a static threshold (such as 25 per cent of the hotspot’s firms) is inappropriate. Instead, a dynamic threshold inspired by Droop’s quota for the single transferable vote electoral system is used.17 The formula, displayed below, establishes a quota number of firms that an LSOA must have in order to be linked to a hotspot. While the methodology may exclude some LSOAs unnecessarily, it ensures that only neighbourhoods with a concrete link to a new economy hotspot are included.

E.g. for a hotspot comprised of 16 firms spread over three LSOAs:

If the firms were divided among the three LSOAs on a 7 firm, 6 firm, and 3 firm basis, only the first two would be included.

Considered as a whole, places with hotspots appear to be both more productive and faster growing than those without them. This relationship holds in most regions, as Figure 2 shows. Outside London, areas with hotspots are 7 per cent more productive than those without on average. Exceptions to this trend can be seen in Wales and the North East, where places with hotspots have lower productivity than those without them.

Figure 2: Regional productivity estimates, 2019

Source: ONS, The Data City, and Centre for Cities calculations

Box 3: Local services and productivity premiums

While the premiums seem modest, there is a limit to the extent to which large productivity gaps are beneficial. One of the most important roles that productive ‘exporting’ firms (in that their outputs are sold beyond the immediate vicinity) play in local economies is the generation of income to be spent on local services such as hospitality and retail.18 This multiplier effect is one of the principle means through which a place benefits from dynamic businesses and skilled workers.

Local services firms tend to be less productive than exporting firms. As a result, their appearance in places with hotspots will likely lower the average productivity of the area. This means that locations with enormous productivity differences between places with hotspots and their surroundings could easily be a sign of weak multiplier effects (innovative firms which do not support local services) as much as an indication of dynamism and innovation.

As Figure 3 shows, the gulf between places with hotspots and those without in relation to growth is much larger. In more than half of Britain’s regions, areas with hotspots have grown at an annualised rate of above 2.5 per cent per year – a figure well in excess of the average national growth rate for the same period. Scotland is the sole outlier in this post-recession trend, although even here areas with hotspots outperform the rest when the period 1998-2019 is considered instead.

Areas with hotspots in all regions of the UK outperform places without hotspots across the 1998-2019 period. It is not possible to draw an indisputable causal link between the appearance of hotspots and outcomes in relation to growth and productivity. Nevertheless, it is likely that the new economy plays some role. At the very least, innovative firms opt to locate in areas in which output has been expanding rapidly despite sluggish growth in the rest of the economy.

Figure 3: Annualised GVA growth estimates

Source: ONS, The Data City, and Centre for Cities calculations

Hotspots vary in size and so in national importance

Not all hotspots are the same, however. Although hotspots have a minimum size limit (see Box 1), there is no ceiling on how many firms can be present. The average (median) number of firms in a hotspot is 21, and 95 per cent have 100 firms or less (see Table 1). There are a number of very large hotspots which are a lot bigger. Confined mostly to city centres (discussed in more detail below), these hotspots are much more important than their peers to the national economy.

Table 1: Distribution of hotspot sizes

Hotspot size Frequency Minimum size Maximum size
15 to 34 276 15 34
35 to 54 31 35 54
55 to 74 9 55 74
75 to 94 8 76 94
95+ 20 99 6,295

Source: The Data City and Centre for Cities calculations

Hotspots are melting pots rather than monoclusters

Much of the conversation about clustering in the past has centred in on the clustering of specific industries. Despite this, the approach used here shows that hotspots are best thought of as melting pots of new economy activity rather than ‘monoclusters’ centred on a single industry (such as advanced manufacturing). When measured using relative or absolute specialisation indices, few hotspots display concentration of any kind.19 Only 24 hotspots can be described as specialised around particular industries. This sectoral diversity also holds at both a labour market (travel-to-work area or ‘TTWA’) and regional levels; only five per cent of TTWAs possess specialised clustered new economies.

Despite the diversity within hotspots, there is a divide between new economy industries which tend to appear in hotspots and those which do not. For example, whereas nearly half of all firms in AdTech are in hotspots, only five per cent of those in modular construction are. The difference tends to fall along a service versus non-service divide. Hotspots are generally comprised of businesses engaged in service-orientated activities, such as FinTech and streaming, and tend to contain fewer firms in energy generation, electronics manufacturing, and advanced materials. Across the country, 61 per cent of new economy companies are engaged primarily in service activities. The equivalent figure for hotspots is 72 per cent.

Therefore, while their exact composition varies between places, innovative service companies have a presence in almost all hotspots. The core ‘ingredients’ from which hotspots are composed are actually remarkably similar across the country, as Figure 4 shows. Although there is some variation – activities such as FinTech are play a bigger role in London than the North West, for example – the ten most common clustered new economy industries account for 60 per cent of the activities present in hotspots in all regions.

Figure 4: The frequency of the 10 most common new economy industries among clustered firms by region, 2022

Source: The Data City and Centre for Cities calculations

Two factors explain these trends. First, service and non-service firms generally have different floorspace requirements. While service-orientated activities are generally based in offices, non-service firms often require industrial spaces and laboratories which tend not to be located in dense urban areas. This means non-service firms are more likely to fall foul of the 250m distance threshold than their service-orientated cousins.

Second, whereas innovative firms of all kinds have the potential to benefit from ‘matching’ (shared access to workers with the right skills) and ‘sharing’ (joint use of infrastructure and supply chains) agglomeration, intellectual property protectionism means that companies specialising in some non-service ventures (such as pharmaceuticals) have less to gain from inter-firm knowledge spillovers.20 This again reduces the relative attractiveness of hotspots for non-service firms.

Service firms, by contrast, are not overly constrained by sector and can share inputs and benefit from agglomeration economies within relatively diverse ecosystems. Recent research has shown that this diversity can be an asset in innovation, as the clustering of firms in different fields over a short distance supports the emergence of unconventional approaches and ideas.21


  • 14 These estimates were calculated from public data on firms, GVA, and jobs at small geographies
  • 15 ONS (2023), UK small area gross value added (GVA) estimates 1998-2020
  • 16 ‘Data Zones’ and ‘Super Output Areas’ respectively. Because the analysis in which they are used most heavily depends on location rather than other attributes (such as size) the fact that these geographies are not perfect equivalents of LSOAs has very little impact
  • 17 Droop H (1881), On methods of electing representatives, Journal of the Statistical Society of London, 44 (2): 141–196
  • 18 Moretti E (2010), Local Multipliers, American Economic Review, 100 (2): 373-77
  • 19 Palan N (2010), Measurement of Specialization – The Choice of Indices, FIW Working Paper 62
  • 20 The three main types of agglomeration are described in Duranton G and Puga D (2004), Micro-foundations of urban agglomeration economies, NBER Working Paper 9931
  • 21 Berkes E and Gaetani R (2021), The Geography of Unconventional Innovation, Rotman School of Management Working Paper No. 3423143