Sustainable growth in developed economies is brought on by the application of ideas and innovation in new areas of the economy. During the Industrial Revolution, this included the production of machine tools and locomotives. In the 1930s, it was chemicals and automobiles. Then, post-war, it was aerospace activities and electronics. The new economy, however it is defined at different stages of history, is important for the performance and development of the economy overall.

Often, policy has been focused on encouraging the growth of the new economy of its day. For example, both national and local governments have been very explicit about identifying specific sectors to support, for example in the industrial strategy set out under the May Government, or through a plethora of local economic strategies.1 And policies that encourage research and development (R&D) have been popular in the UK in recent decades, with the hope being that this will lead to new breakthroughs that, when commercialised, can grow the economy.

In recent years R&D investment has been at the centre of discussions and policy developments, with the geographical dispersal of public money being a particular bone of contention. In particular, the concentration of these monies in the so-called golden triangle between London, Oxford and Cambridge has been blamed for the poor economic performance of other parts of the UK.2

The Government has recognised this. Not only has it set out its intention to raise R&D spending to 2.4 per cent of GDP by 2027, it has committed in the Levelling Up White Paper to increase domestic public investment in R&D outside the Greater South East by at least 40 per cent.

What is less clear is where this money should be spent to have maximum impact. And without this, it becomes very difficult to guide how exactly the Government should go about spending it.

International evidence suggests that innovation – a spur of new economic activity – disproportionately occurs in cities.3 For example, in the USA patents and research papers are more likely to be produced in cities, while in Germany work has shown that innovative firms are much more likely to be based in cities than elsewhere.45 However, to date, there is very little to show how this plays out in the UK.

This paper focuses on the UK, showing what the geography of today’s new economy looks like using a novel dataset that identifies businesses operating in emerging sectors.

It considers where the new economy firms are located in different types of places, sets out variations across cities, analyses the drivers behind location decisions, and looks at past and current policies designed to foster new economic activity. Finally, it makes policy recommendations to increase the size of the new economy across the country.

Box 1: Methodology

Definition of a city

Centre for Cities’ research focuses on the UK’s 63 largest towns and cities. Unless otherwise stated, cities and large towns are defined as Primary Urban Areas (PUAs), using a measure of the built-up area of a large city or town, which sometimes spans beyond the core local authority. Full methodology is available at centreforcities.org/puas

Defining city centres, suburbs, hinterlands and rural areas

The analysis in this report splits the UK into four areas. Cities are divided into two areas – city centres and suburbs – as are non-urban areas (hinterlands and deep rural).

City centres are defined based on all the postcodes within a circle from the pre-determined city centre point. The radius depends on the size of the residential population:

  • London: radius of 2 miles;
  • Large cities (more than 550,000 residents): radius of 0.8 miles;
  • Medium and small cities (less than 550,000 residents): radius of 0.5 miles.

Suburbs are determined based on the postcodes that fall within the rest of a city (defined as PUAs above).

Hinterlands are non-urban areas that are considered to be within the travel-to-work area of cities. This varies from place to place and is determined by the average distance that a worker living outside of a city travels to their job within it, defined using Census 2011 data. For example, the travel catchment for London is 63km, but for Worthing it is 20km.

The deep rural areas make up the remaining part of the physical landmass of Britain and fall outside of the travel catchment of cities.

To identify business parks, the research uses the 2011 workplace-based area classification from the Office for National Statistics (ONS), defining them as the sub-categories of regional business centres, industrial units, science and business parks and business parks.

Defining new economy activities

New economy firms, and their activities, are identified by the Data City, which uses ‘web-scraping’ of words from company websites. This data is then matched with Companies House records to verify businesses and their registered addresses.6

This enables emerging sectors to be identified in a way that is impossible to do thorough Standard Industrial Codes (how statistics agencies define sectors). The Data City has developed Real Time Industrial Classifications (RTICs) as an alternative to the standard measure and, to date, has identified 48 upper level RTICS, such as FinTech and wearables.7

Centre for Cities uses 47 RTICS to define the new economy (dropping business support services – see Appendix 1 for more information). This provides a dataset of 88,162 new economy businesses, which is around 3.2 per cent of all those reported by the ONS in 2021.

The RTICS are grouped into three categories:

  • New economy services: businesses where the majority of RTICs (in cases where a firm is allocated more than one) are in services activities such as FinTech, AdTech, or both.
  • New economy non-services: businesses where most activities are defined as non-services, such as AgriTech, modular construction or both.
  • New economy hybrid businesses: those with an equal number of services and non-services RTICs. For example, a business that is classified as both AgriTech and digital creative.

Within this dataset, 60.6 per cent of businesses are classified as services and 34.5 are non-services. The remaining 4.9 per cent are hybrid businesses but given the small number, these are excluded from the analysis.

These firms are then allocated to places depending on the location of their registered address.

Potential limitations

There are two principal limitations with this dataset. The first is that by using registered addresses, it assumes that all innovative activity happens at that site. Sixty per cent of the businesses in the dataset have only one address. Given the absence of an identifiable second address, this assumption seems reasonable. It is more of a problem where a registered address is not where the business operates (because it is registered at an accountancy firm, for example) or where there are activities that occur in other branches. In cases where more than 500 businesses were registered to one address, this was manually checked to see whether it was the location of an accountant and, if so, a secondary address was used instead.

To test the sensitivity of the results to this limitation, two steps were taken. The first was to cross check business counts in the Data City dataset to those in the ONS data across the four geographies set out above. This test suggested the Data City data may be underplaying the role of cities, which means the results presented in this report are conservative estimates. The second was to run the analysis using single address businesses only. The key findings presented in this report did not change during this sensitivity testing.

A second issue is that counting firms rather than employees does not factor in business size. Previous work by Centre for Cities has shown that larger companies tend to locate in cities and city centres.8 Again, this means this dataset is likely to offer a conservative estimate of the trends shown in this report.

It is important to note that while the dataset is not perfect, it is the best that is currently available to understand and provide valuable insight into the geography of the new economy in the UK.

Other data used for this research

This paper uses the Data City data with several publicly available datasets from the ONS. These include the total number of companies from UK Business Counts, the number of workers within a commutable distance according to the 2011 Census, productivity data at the local authority level from the sub-regional productivity in the UK, the number of jobs from the Business Register and Employment Survey, and data on skills from the Annual Population Survey.


  • 1 Swinney P (2010), Cities, Private Sector Jobs & the Coalition, London: Centre for Cities
  • 2 See, for example, Forth T and Jones RAL (2020), The Missing £4 billion: Making R&D work for the whole UK, London: Nesta
  • 3 Andrews MJ and Whaley A (2022), 150 years of the geography of innovation, Regional Science and Urban Economics vol. 94 (C)
  • 4 Balland PA, Jara-Figueroa C, Petraliac S, Steijna M, Rigbye D and Hidalgo CA (2018), Complex Economic Activities Concentrate in Large Cities, Rochester: SSRN
  • 5 Kinne J and Lenz D (2019), Predicting innovative firms using web mining and deep learning, Mannheim: ZEW
  • 6 This approach follows the methods used in papers such as Nathan, M. and A. Rosso (2015). “Mapping digital businesses with Big Data: some early findings from the UK ” Research Policy 44(9): 1714-1733, Kinne and Lenz (2019), Predicting innovative firms using web mining and deep learning, Mannheim: ZEW and Bishop A, Mateos-Garcia J and Richardson G (2022), Using Text Data to Improve Industrial Statistics in the UK, London: ESCoE
  • 7 There are more than 300 sub-sectors under the 48 upper level RTICS. For further details, visit https://thedatacity.com/real-time-industrial-classifications/
  • 8 Swinney P and Serwicka I (2016), Trading Places: Why firms locate where they do, London: Centre for Cities