Rural Scotland has an economic structure that is distinct from those of other areas of Scotland, United Kingdom. This chapter sets the scene by providing information on the structure of the rural economy in Scotland, considers how to explore equal opportunities for innovation in rural areas and what firm characteristics are associated with innovation. It finds that, although rural areas often have smaller and older firms, larger and younger firms are more likely to report having engaged in innovative activities.
Enhancing Rural Innovation in Scotland, United Kingdom
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2. Understanding innovation in rural Scotland
Abstract
Key messages
Innovation within the context of rural areas
Scotland is a strong and growing performer in regional innovation, with strengths in skills development and university-firm linkages, and a high capacity to increase productivity through innovation adoption.
Demographic change is not as strong in Scotland as in other OECD countries; nevertheless, the decline is still observable, in particular in remote rural areas. Accessible rural areas, on the other hand, have observed notable growth.
Among some of its strengths, Scotland is an early and fast adopter of renewable energy innovations, only narrowly missing its 100% renewable energies target in 2020 and with a reduction in greenhouse gas (GHG) emissions over the past 2 decades. Despite this progress, non-metropolitan regions are lagging in progress in emissions reductions in metropolitan regions.
Rural Scotland occupies 98% of the country’s land mass and is home to a third of firms but less than a fifth (15%) of workers in 2022. Between 2013 and 2018, productivity continued to grow in rural areas (0.08%), despite slowing down in the rest of Scotland (-0.005%).
Between 2015 and 2018, rural areas experienced a growth in firms and workers. Despite losses in terms of jobs in remote rural areas in the following period, from 2018 to 2022, rural areas did not suffer as large an impact as other urban areas and small towns.
More largely, rural regions have benefitted from innovation adoption and have the potential to continue to contribute to national productivity growth. In fact, from 2013 to 2018, most of the growth in productivity was attributed to increases in rural areas including accessible (25%) and remote rural areas (81.6%).
Within rural areas, close to two-thirds of overall productivity growth was due to more efficient use of resources (closely associated with innovation adoption) and about one-third due to the reallocation of resources in accessible and remote regions. There is still a large margin of opportunity for increased productivity growth through place-based policies that target both the reallocation of capital and resources to rural regions as well as the upgrading of activities and upskilling of labour within firms in rural regions.
As innovation is creating opportunities, there will be winners and losers. Productivity in rural Scotland is becoming more unequal. Over time, the disparity between the high- and low-productive firms grew threefold. In 2010, the top 10% of firms were 10 times more productive than the bottom 10% of firms. In 2018, this ratio climbed to 30, suggesting that the dissemination of productivity gains across the entire ecosystem of firms could still be a target to bring broader benefits to regions.
Increasingly, the trade and services sector is taking a stronger role in rural economies. Using OECD definitions of Scottish territories, non-metropolitan regions, like those across other regions in Scotland, have a strong trade and services component, which is still growing. In 2022, 40% of firms in remote rural areas and 47% of firms in accessible rural areas were in the trade and services sector, accounting for 47% and 46% of jobs respectively. The agricultural and fisheries sector remains a strong contributor to the rural economy, whereas it employs more than a third of firms in remote areas and a quarter of firms in accessible rural areas, despite only accounting for 18% and 15% of jobs respectively. The manufacturing sector is a small share of rural areas but is a growing sector that continued to observe growth in remote rural areas during the years of the COVID-19 crisis. Last, public services and works hold a relatively small share of workers in rural areas. This is relatively challenging for workers who may need social support mechanisms to remain fully engaged in employment or entrepreneurship, in particular for women and older workers.
Younger and larger firms tend to innovate more than older and smaller firms, regardless of location and industry, and this is still reflected in productivity in the region. A firm that is more than 30 years old is 5% less likely to innovate than younger firms. Yet, it is small and old firms that dominate rural areas, accounting for the near totality of all firms in rural regions.
In rural areas across OECD countries, labour pools tend to be smaller and older. Rural areas of Scotland can further increase access to more labour and skills through actively promoting age, gender and migration status diversity in the labour force in rural areas. For example, encouraging employers to recruit older workers (45-64 year-olds) while retaining younger workers can help alleviate the pressure on tight labour markets; building opportunities for women and promoting wage equality may also help reduce the disparity between male and female participation rates; and last, although rural Scotland is good at attracting individuals from other parts of the United Kingdom (UK), there is still room for engaging with UK authorities on attracting new skills from outside the United Kingdom.
Well-being is also an important factor for firms across Scotland. Measures such as the real living wage, flexible work hours, diversity and inclusion and measuring the gender pay gap are used as important mechanisms across all areas to ensure equal opportunities. However, the share of firms participating in such measures tends to be slightly lower in remote rural and accessible rural areas.
Accessibility as a defining characteristic of rural innovation
Accessible rural areas have distinct needs in comparison to rural remote areas. They are characterised as areas that have relative proximity to dense urban areas (a 30-minute drive from a settlement with a population of 10 000 inhabitants or more) and rural characteristics that remain distinct according to the national classifications of territories. Notably, while more rural areas are characterised by a small labour pool and fewer firms, accessible rural areas tend to follow the labour trends of urban areas more closely. This can create challenges and opportunities, notably:
From 2001 to 2020, accessible rural areas grew in terms of population shares, while rural remote areas shrunk.
Between 2015 and 2018, accessible rural areas observed an increase in the relative and absolute number of firms in the economy, while the number of firms increased to a lower extent in remote areas. Labour also increased to a larger extent in accessible rural areas than in remote rural areas. During the following period, from 2018 to 2022, accessible rural areas did not record a large net loss nor a large net gain in either the number of firms or labour, whereas remote rural areas observed a significant drop in jobs and a marginal increase in the number of firms.
In contrast to rural remote areas, accessible towns and rural areas tend to have a larger share of larger and younger firms.
In addition to a different firm size and age structure of the economy of accessible rural areas as compared to remote rural areas, accessible rural areas observe similar sectoral shifts, age demographics and shares of foreign-owned firms as urban areas in the rest of Scotland.
However, there is also evidence of growing inequality of productivity between firms in accessible rural areas, which can have an impact on competition and innovation. The relative level of productivity for the most productive firms is higher than all other territories. The top 10% of firm performers based on productivity were 37 times more productive than the bottom 10% in accessible rural areas. This ratio was lower in urban areas in the rest of Scotland (35 times) and in rural remote areas (30 times).
A long history of innovation is prevalent in Scotland, where the proactive nature of social innovators and entrepreneurs has shaped the landscape for well-being in Scotland today. Firm-based innovation is growing in Scotland, as is social innovation and entrepreneurs that fundamentally contribute to the well‑being of rural places and people. In addition to social innovation and entrepreneurship, Scotland has a strong tradition of university-industry collaborations. It is a hub for applied research and problem-based innovation and can bring foresight on how to apply and adapt innovations to tackle some of the critical challenges for OECD economies, such as climate change.
Rural areas are experiencing fundamental changes to the way people, places and firms work and interact with each other. This is in part due to megatrends in digitalisation, innovation, demographics and the environment. When crises, such as the COVID-19 pandemic, require heavy support in public service delivery and tailored approaches for recovery, rural regions often do not have the same opportunities as more densely populated regions closer to metropolitan areas (OECD, 2020[1]; 2021[2]). Despite these challenges, there are some very innovative approaches that individuals in rural areas have taken to build resilience1 and several steps towards implementing innovations to address megatrend challenges such as climate change and demographic change.
Introduction to the landscape of innovation and geography in Scotland
Creation, destruction and the proliferation of advances in innovation shape how our societies respond to challenges today and in the future. Subnational governments and regional agencies across OECD countries count on innovation and the diffusion of innovation advances to spread prosperity and opportunities to all places.
With a land mass of 78 000 km2, or close to 60% of the land mass of neighbouring England, Scotland provides: a support system for innovators with 19 universities and its extension services; 7 innovation centres; Interface, a government programme to link innovative entrepreneurs to university researchers; Business Gateway, a national start-up initiative that helps budding entrepreneurs get their ideas off the ground; a strong commitment from 3 regional development agencies looking to provide support to entrepreneurs and innovators across all regions of Scotland; and additional sector-specific innovation programmes such as in the manufacturing sector.
As compared to European countries, Scotland is classified as a strong innovator, considered among the top 20% of regions and has strengths in skills, scientific publications and collaborations with small and medium-sized enterprises (SMEs). Despite this strong performance, firms still face challenges in business product and process innovation, design and trademark applications as well as bringing the sale of innovative products to markets (EC, 2021[3]).
Firms are increasingly innovating in Scotland but to a lesser extent than other countries in the United Kingdom, suggesting room for improvement. According to statistics from the 2021 UK Innovation Survey (UK BEIS, 2022[4]), the share of firms innovating in Scotland increased between the periods of 2016-18 and 2018-20 by 6.8%. However, the share of firms reporting innovation across the United Kingdom as a whole increased by 7.3%. In 2020, the share of firms in Scotland having reported innovating was 39%, as compared to England at 46%, Wales at 44% and Northern Ireland at 38% (UK BEIS, 2022[4]).
Demographic challenges in non-metropolitan areas
While there is ongoing progress in innovation in Scotland at large, non-metropolitan regions and rural areas still face substantially different challenges from those in metropolitan areas. Trends in population dynamics and age-based demographics across different types of regions create different challenges and opportunities for rural areas of Scotland than for urban areas.
OECD countries in general are observing demographic change across geographies. Yet, the trend in Scotland is more mitigated and nuanced. In OECD countries, there was clear evidence of depopulation. Between 2000 and 2015, the share of the population in rural areas fell by 1.5 percentage points, while it grew by close to double that amount, 2.9 percentage points, in cities in OECD countries (Figure 2.1). In the United Kingdom, the geographical dispersion is more mitigated than on average across all OECD countries. Close to 2.9 percentage points more of the total share of the population lived in cities in 2015 as compared to 2000, while 0.7 percentage points less of the total share of the population lived in rural areas in the United Kingdom. However, Scotland, over the same period of time, observed a growth of 0.37 percentage points in rural areas (aggregate of accessible rural and remote rural areas) and a fall of 0.22 percentage points in cities and urban areas.
The mitigated demographic change in Scottish rural areas is due to increases in accessible rural areas and a fall in remote rural areas. Recent estimates from 2020 suggest that rural areas continued to grow with a 0.66 percentage point increase from 2001 to 2020; nevertheless, on the whole, they account for between 16% to 17% of the population of Scotland (NRS, 2021[5]). This growth in rural areas is primarily due to increases in accessible rural areas (0.84 percentage points), despite a fall in remote rural areas (‑0.18 percentage points). The growth in accessible rural areas is substantial. In comparison, in the same period of time, large urban areas grew at a slower pace (0.54 percentage points), despite having higher increases in the overall number of individuals. Demographic change in Scotland is focused in remote and island areas, where depopulation is still a major concern for rural policy makers (see Chapter 3).
Figure 2.1. Change in the share of the population, by degree of urbanisation, 2000-15
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Note: Data from Scotland sourced from National Records of Scotland (NRS). Categories are aggregations of the sixfold Scottish Government Urban Rural national classification system. Rural areas refer to accessible rural and remote rural areas. Towns and semi-dense areas refer to remote small towns and accessible small towns. Cities refer to large urban areas and other urban areas. Data for Scotland are from 2001 rather than 2000.
Source: OECD analysis adapted from OECD (2022[6]), OECD Regions and Cities at a Glance 2022, https://doi.org/10.1787/14108660-en and NRS (2021[5]), Population Estimates by 6-fold Urban Rural Classification, 2001-2020, https://www.nrscotland.gov.uk/files//statistics/population-estimates/special-area-2011-dz/urban-rural/urban-rural-20-tab-1.xlsx.
Scotland has less of a population in metropolitan areas than on average in OECD countries (Figure 2.2, Panel A). On average between 2010 and 2020, there is a lower share of individuals in metropolitan regions and a higher share in non-metropolitan regions. The difference between the share of population in metropolitan regions is 3% less in Scotland than in OECD countries. In non-metropolitan regions, the share of the population is 6% higher in Scotland than in OECD countries.
There is evidence of demographic change in rural areas, with the share of the population in non‑metropolitan regions falling over the last decade. From 2010 to 2020, the share of population in non‑metropolitan regions of Scotland fell from 36.1% to 35.7%. The decline is relatively small as compared to other OECD countries; however, it nevertheless falls in line with trends in other OECD countries. In comparison, in OECD non-metropolitan regions, the share of population in non-metropolitan regions fell from 31.2% in 2010 to 30.3% (Figure 2.2, Panel B).
Age-based demographic change is also occurring in Scotland. In 2020, the share of working-age individuals in non-metropolitan regions of Scotland is older than in metropolitan regions and grew since 2010. In non-metropolitan regions, the average share of young working-age (15-29 year-old) individuals was 16%, while it was 22% among older working-aged (50-64 year-old) individuals in 2020 (Figure 2.2, Panel C). In comparison, the share of young individuals on average in OECD countries is 18.6% in non-metropolitan regions, while it is 19% in non-metropolitan regions. The share of older individuals on average in OECD countries is close to 19% in both metropolitan and non-metropolitan areas.
Figure 2.2. Population declines among working-age individuals in non-metropolitan areas
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Note: Panels A and B use the OECD classification of small (TL3) regions into two large categories, metropolitan regions (MR-L and MR-M) and non-metropolitan regions (NMR-M, NMR-S and NMR-R). The classification is further described in Box 2.2. The share of young individuals includes those aged 15 to 29 years of age. The share of older individuals includes those aged 50 to 64.
Source: OECD (n.d.[7]), OECD Regional Database, https://doi.org/10.1787/region-data-en.
The disparity between age-based demographics is growing over time in both Scotland and OECD countries. In 2020, the share of young individuals fell across all areas of Scotland as compared to 2010, with the largest decline in medium-sized metropolitan regions, where the share fell from 21.4% to 19.4% (Figure 2.2, Panel C). In non-metropolitan regions, the greatest fall in the share of young working-age individuals in non-metropolitan regions close to medium-sized cities where the share of younger workers fell from 17.8% to 17.0%. At the same time, the share of older working-aged individuals increased in Scotland from 20% to 22% on average, with the largest growth in non-metropolitan regions close to medium-sized cities, where the shares grew from 21.1% to 22.1% from 2010 to 2020. In comparison, the older OECD population grew similarly in terms of percentage points but from a lower starting point. In OECD countries, the average share of older individuals in non-metropolitan regions grew from 17% to 19%. The growth was the strongest in non-metropolitan regions close to small cities, where the share of older individuals grew from 15.4% to 19.5%.
Leading by example in innovation for climate change
Innovation for climate change is particularly latent across rural areas of Scotland where the strategy to adapt business models to the circular economy, promote research and development (R&D) that harnesses rural environmentally responsible advantages and develop responsible tourism has long been common practice, in line with the OECD Rural Agenda for Climate Action (2021[8]).
Among some of its strengths, Scotland is an early and quick adopter of renewable energy-linked innovations. In the current context of climate change today, the early focus on renewable energy innovations is notable and strongly tied to rural opportunities. Scotland only narrowly missed its 100% renewable energies target, with 98.8% of gross electricity consumption from renewable energy sources in 2020 (Scottish Government, 2020[9]), with its position strongly contributing to the United Kingdom’s current renewable energy usage of 50%, serving as a main asset for overall UK renewable energy targets.
Scotland is also a leader among countries and regions in reducing production-based GHG emissions. It has consistently reduced its production-based GHG emissions, faster than the average across OECD regions. Since 2000, total GHG emissions have fallen relatively consistently, with overall emissions falling from 97.513 metric tons of CO2 equivalent (MtCO2e) emissions to 71.009 (Figure 2.3).
Nevertheless, progress in the reduction of production-based emissions is slower in non-metropolitan regions of Scotland (Figure 2.3), based on the MtCO2e classification of metropolitan areas as described in Box 2.1. The share of emissions in non-metropolitan areas of Scotland is almost double that of metropolitan areas, with 38% from metropolitan regions and 62% from non‑metropolitan regions (44.22 MtCO2e in non-metropolitan regions, and 26.789 MtCO2e in metropolitan regions), with the fall in non-metropolitan regions slower than those in metropolitan regions. On average across OECD countries and in the United Kingdom, the majority of emissions tend to come from metropolitan regions, rather than non-metropolitan regions, with close to two-thirds of GHG emissions from metropolitan areas and one-third from non-metropolitan areas. However, much of this challenge is due to relatively higher GHG emissions in non-metropolitan areas from the transport, industry (manufacturing) and agricultural sectors, which are similar drivers of high emissions in other OECD countries (see Annex Figure 2.A.1 and Annex Figure 2.A.2 for more figures on average and total emissions by sector).2 While there are limitations to what innovation can do, it can help to reduce emissions in both Scotland and other OECD countries and regions.
Figure 2.3. Average GHG emissions
Approaching rural innovation in Scotland through case studies and rural data
Innovation occurs differently across territories of Scotland, where resources vary based on natural attributes and labour supplies. There is also a strong role for rural social entrepreneurs that are able to deliver many of the social and business services that are not currently available otherwise. These entrepreneurs will be further explored in Chapter 4. Understanding how firm-based innovation occurs in these areas is also critical to supporting a place-based approach to regional innovation policies. The OECD (2022[10]) takes a place-based approach to understanding and measuring rural innovation and emphasises a “capacity approach” to policies used to advise rural and regional policy makers as described in Box 2.1.
This analysis is drawn from a series of virtual and physical missions (fieldwork) and statistical analysis. The fieldwork that built the framework around which the chapter was elaborated took place in four case study areas (Caithness and Sutherland, Galloway Glens, Garnock Valley and Outer Hebrides) in the spring of 2022. Examples from the different case study areas are further elaborated in Chapter 3. The statistical analysis, which is the focus of this chapter, came from three main data sets from the Office for National Statistics (ONS), namely the UK Innovation Survey (UKIS)3 and the Business Structure Database (BSD)4 for regression analysis, and the Inter-Departmental Business Register (IDBR) for updated summary statistics on territorial, sector and size distributions. A final bi-annual dataset, the Rural Scotland Business Panel Survey, was used to provide additional information on the firm’s approach to promoting diversity and equality.
Most of this analysis in this chapter focuses on firm-related characteristics or characteristics of companies at the level of each firm location (branch offices), rather than using the location of the headquarter as a basis for analysis. Data from the two waves from UKIS – Waves 7 and 10 – are used for regression analysis. Moreover, these two waves are merged into the BSD 2010 and BSD 20185 respectively, as the BSD provides additional information about firms’ profiles, including legal status, birth date and rural-urban classification. Using these two primary sources of microdata for the regression analysis, this report sets the scene for understanding innovation in rural regions (Chapter 2), providing a scene setting for analysis of policies and programmes to encourage innovation and entrepreneurship (Chapter 3) and understanding social innovation and entrepreneurship (Chapter 4). This chapter of the report explores the economic conditions of rural firms in Scotland, explores trends in the rural labour force and concludes by seeking to understand the drivers of innovation in rural Scotland.
Box 2.1. Understanding innovation capacity and measuring rural innovation
Innovation capacity
Increasing the capacity of people and places to innovate creates the conditions for innovation to occur. While significant literature on innovation capacity has developed in the United States, it has largely focused on innovations by private firms (Hall, 2008[11]). Typically, the literature emphasises the importance of agglomeration effects, the presence of specialised public and private research centres and a large share of workers with advanced science and engineering degrees, and uses patent counts as the main measure of innovation (Hamidi, Zandiatashbar and Bonakdar, 2019[12]; Ferreira, Fernandes and Raposo, 2015[13]).
Innovation capacity has two dimensions, the first being the ability to innovate and the second being the ability to successfully commercialise the innovation. Ultimately, innovation is beneficial to a region if it leads to an increase in competitiveness (Audretsch and Peña-Legazkue, 2012[14]). If innovation is to drive economic growth, commercialisation is equally essential. While only some new firms may innovate at the technological frontier, most new firms nonetheless introduce new elements to the market, even if only novel in the local context. Hall (2008[11]) found that most high-technology innovation, as measured by patents, can be attributed to education and access to federal funding.
The OECD approach to understanding drivers of rural innovation
Based on the analysis from related work (OECD, 2022[10]), when we are looking to understand and promote rural innovation, the way we measure innovation matters. Conventional definitions and measures can favour some activities over others. For the most part, several commonly used definitions and measures of innovative activities are better suited for innovations in large firms that: engage in the product rather than process innovation; are focused in the manufacturing or R&D intensive sectors; and depend on heavier capital and resource expenditures. However, a larger share of firms in rural regions are often small and focused on the service or natural resource sectors (Freshwater et al., 2019[15]) where innovation is incremental or is characterised by a strong use of social and human capital (Shearmur, Carrincazeaux and Doloreux, 2016[16]).
This report approaches innovation through the following framework that places a focus on the capacity for people to innovate in non-metropolitan areas.
Figure 2.4. Analytical framework for understanding the drivers of innovation in rural regions
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Source (box): Hall, J. (2008[11]), “Adding meaning to measurement: Evaluating trends and differences in innovation capacity among the states”, https://doi.org/10.1177/0891242408326467; Hamidi, S., A. Zandiatashbar and A. Bonakdar (2019[12]), “The relationship between regional compactness and regional innovation capacity (RIC): Empirical evidence from a national study”, https://doi.org/10.1016/J.TECHFORE.2018.07.026; Ferreira, J., C. Fernandes and M. Raposo (2015[13]), “The effects of location on firm innovation capacity”, https://doi.org/10.1007/S13132-015-0281-4; Audretsch, D. and I. Peña-Legazkue (2012[14]), “Entrepreneurial activity and regional competitiveness: An introduction to the special issue”, https://doi.org/10.1007/S11187-011-9328-5; OECD (2022[10]), Unlocking Rural Innovation, https://doi.org/10.1787/9044a961-en; Freshwater, D. et al. (2019[15]), “Business development and the growth of rural SMEs”, Paris, https://doi.org/10.1787/74256611-en; Shearmur, R., C. Carrincazeaux and D. Doloreux (2016[16]), “The geographies of innovations: Beyond one-size-fits-all”, https://doi.org/10.4337/9781784710774.00006.
Rural proofing innovation
Overcoming geographical biases when assessing strategies for enhancing innovation in rural areas should start with a clear understanding of: i) the definition of rural; and ii) the definition of innovation. As described by the OECD (2022[10]), how we define rural and how we measure innovation may create biases that do not reflect the reality of all places in Scotland.
This section defines rural areas in Scotland and follows by discussing how measuring innovation in rural areas requires a more nuanced approach. Understanding the importance of geography when seeking to better target policies for innovation and entrepreneurship is an important first step.
Defining rural in Scotland
There are multiple ways to define “rural”, including traditional definitions based on density and sectoral attributes. However, each method is associated with different challenges and opportunities. In Scotland, the Scottish national classification approach considers distance and township status as defining traits. It uses settlement patterns with a population of less than 3 000 inhabitants to define rural areas. At its most granular level, the Scottish Government has an eightfold classification as illustrated below in Table 2.1. These categories can be aggregated into different levels of analysis. For this report, and to account for legal privacy concerns when the sample size of data is too small to safely ensure anonymity, the analysis is either aggregated into a threefold definition that includes: i) remote rural; ii) accessible rural; and iii) the rest of Scotland based on the joining of the eight classification categories under the three main categories of the figure; or the sixfold definition that includes: i) very remote and remote rural areas (jointly); ii) accessible rural areas; iii) very remote and rural small towns (jointly); iv) accessible small towns; v) other urban areas; and vi) large urban areas.
Table 2.1. Scottish national classifications of rural areas
Rest of Scotland |
Accessible rural |
Remote rural |
---|---|---|
Large urban area: Settlements of 125 000 inhabitants and over |
Accessible rural: Thirty-minute drive of a settlement with a population of 10 000 inhabitants or more |
Remote rural: Areas with a drive time of between 30 and 60 minutes from a settlement with a population of 10 000 inhabitants or more |
Other urban area: Settlements of 10 000 to 124 999 inhabitants |
Very remote: Areas that are more than a 60‑minute drive from a settlement with a population of 10 000 inhabitants or more |
|
Accessible small town: Settlements of 3 000 to 9 999 inhabitants, and within a 30‑minute drive of a settlement of 10 000 inhabitants or more |
||
Remote small town: Settlements of 3 000 to 9 999 inhabitants, and with a drive time of over 30 minutes but less than or equal to 60 minutes to a settlement of 10 000 inhabitants or more |
||
Very remote town: Settlements of 3 000 to 9 999 inhabitants and with a drive time of over 60 minutes to a settlement of 10 000 inhabitants or more |
Source: Scottish Government (2018[17]), Scottish Government Urban Rural Classification 2016, https://www.gov.scot/publications/scottish-government-urban-rural-classification-2016/pages/2/#:~:text=Categories%205%20and%206%20are,(6)%20Remote%20Rural%20Areas.
By analysing the drive time to larger settlements, rural Scotland is divided into accessible rural and remote rural. The former includes areas within a 30-minute drive of a settlement with a population of 10 000 inhabitants or more, and the latter includes areas with a drive of between 30 and 60 minutes from a settlement with a population of 10 000 inhabitants or more (Scottish Government, 2018[17]). This classification system is demonstrated geographically in Table 2.1.
Access to data and use of data based on rural classifications are often a challenge for rural policy makers and entrepreneurs. Although the Scottish Government provides many avenues through which access to data is possible, increasing access to information and facilitating the interpretation of data on rural areas can increase the visibility of rural challenges. Such initiatives to increase access to rural data and incorporate its use in the policy process are observed across OECD countries. An example of this is the Rural Observatory of the European Commission (2023[18]).
This report largely follows this national classification system. However, when international comparative statistics are used, as in the previous section, it uses a harmonised OECD classification established to standardise international comparisons (Fadic et al., 2019[19]), with rural classifications based on functional urban areas (FUAs) that consider population density and proximity. The small administrative regions that populate the OECD’s definition of rural regions are built on administrative units in countries within the United Kingdom. In the United Kingdom, there are a total of 179 units, with 23 in Scotland. The categorisation of Scottish administrative units within the OECD typology based on a categorisation that prioritised access to cities, as of March 2023, is elaborated in Table 2.2. Further information on classifications in the OECD and for sectors used in this report is elaborated in Box 2.2.
Figure 2.5. Scottish Government Threefold Urban Rural Classification
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Source: Scottish Government (2022[20]), Scottish Government Urban Rural Classification 2020, https://www.gov.scot/publications/scottish-government-urban-rural-classification-2020/pages/2/.
Box 2.2. Territorial and sectoral classifications
Territorial Levels (TLs) classifications
All OECD governments have national approaches to characterising rural places and many countries have more than one approach. For the purpose of this report, national definitions take precedent; however, when national classifications cannot be used, for instance due to confidentiality or comparative purposes, the analysis reverts to the OECD standardised definitions of small administrative regions (TL3).
Regions within the 38 OECD countries are classified on two territorial levels reflecting the administrative organisation of countries. The 433 OECD large (TL2) regions represent the first administrative tier of subnational government, for example, the Ontario Province in Canada. The 2 414 OECD small (TL3) regions are contained in a TL2 region. For example, the TL2 region of Aragon in Spain encompasses three TL3 regions: Huesca, Teruel and Zaragoza. TL3 regions correspond to administrative regions, with the exception of Australia, Canada, Germany and the United States. All the regions are defined within national borders. In many European countries, this aligns with the same units as the Nomenclature of territorial units (NUTS 3) classifications that refer to small regions in eurostat statistics.
OECD territorial approach to classifying rural areas using density and driving distances
Rural is everywhere and exists as a continuum across geographies. What we commonly understand as rural is implicitly spatial and relative. In practice, governments delineate typologies of territories but there is no clear cut-off between regions or areas. Rural characteristics can exist within more urbanised regions and rural attributes are apparent across the spectrum of territorial characteristics. This continuum of rurality is delineated within the recent OECD publication on rural well-being (OECD, 2020[1]).
The term rural is often used to describe territories that have relatively low-density human settlement patterns, with relatively large distances to more densely populated areas. Often, rural regions are characterised as regions with activities closely related to natural resource industries such as mining and agriculture. However, this sectoral definition overlooks the variation across rural territories and what this means for political agenda-setting in rural regions. Indeed, a region being identified as “rural” has implications on government finance and wider regional policy making.
In consultation with OECD national governments, the OECD harmonised a set of guidelines for classifying territorial characteristics across countries that avoid the traditional, and sometimes harmful, rural-urban dichotomy. This unified definition of rural provides a basis for analysis across countries within rural economies (OECD, 2020[1]). The most recent definitions of rural regions have benefitted from a reflection on the combination of physical (“first-nature”) and human (“second-nature”) geographies. Rural regions are defined by economic remoteness, with three distinct features related to physical distance to major markets, economic connectedness and sector specialisation. Considering these features, rural regions are physically distant from major markets, with specialisation in niche markets and those linked with natural resources such as agriculture and tourism. The degree of economic connectedness with surrounding areas may vary by relative density, infrastructure availability and complementarities between and within rural regions.
In 2019, the OECD published a new classification that is based on FUAs that incorporates density and the driving estimations for the time it takes to access dense metropolitan areas. To the furthest extent possible, rural is defined according to the OECD as one of three types of small administrative regions (TL3) with less than 50% of the regional population living in metropolitan areas. This includes rural regions inside FUAs (where at least 50% of the population live within a 1-hour driving distance away from a dense urban area with a population larger than 250 000 inhabitants), rural regions close to small or medium-sized cities of populations smaller or equivalent to 250 000 inhabitants, and remote rural areas.
Figure 2.6. OECD typology for access to cities
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Note: Large metro: FUA with a population larger than 1.5 million inhabitants; Metro: FUA with a population larger than 250 000 inhabitants; Small or medium city: FUA with a population smaller or equal to 250 000 inhabitants.
The diverse types of rural regions all have different characteristics and policy needs. Three types of non-metropolitan regions are considered, to various degrees, to share more rural characteristics than urban ones. Non-metropolitan regions are defined as having less than 50% of the population living in an FUA with a population larger than 250 000 inhabitants. The three types of non-metropolitan regions include regions with access to a metropolitan region, non-metropolitan areas with access to a small or medium-sized city and a non-metropolitan region in remote areas.
Non-metropolitan regions with access to a metropolitan region: These regions have 50% or more of the regional population that live within a 60-minute drive of a metropolitan area. This is similar in part to towns and suburbs surrounding the distant periphery of major metropolitan centres. Examples of such regions include Tyrolean Oberland in Austria (AT334), Montmagny in Québec, Canada (CA2418), Jura in France (FRC22) and Nagasaki in Japan (JPJ42). The challenges of such regions are often tied to economies of metropolitan areas, while focusing on industries such as tourism, without some of the infrastructure barriers of less densely populated areas.
Non-metropolitan regions with access to small or medium-sized cities: These regions are regions with 50% or more of the regional population living within a 60-minute drive of a small or medium-sized city. Examples of these types of regions include the administrative district of Neufchâteau in Belgium (BE344), San Antonio in Chile (CL056), South Bohemia in the Czech Republic (CZ031), East Lancashire in the United Kingdom (UKD46) or Springfield in Illinois, United States (US158). These regions have a strong manufacturing base and linkages to neighbouring economies.
Non-metropolitan regions without access to cities (remote): These regions are regions with 50% or more of the regional population without access to an FUA (metropolitan) within a 60‑minute drive. Examples of such areas include West Estonia in Estonia (EE004), Lapland in Finland (FI1D7), Sonneberg in Germany (DEG0H), and Lesbos in Greece (EL411). Rural remote areas have economies with fewer interlinkages with major cities and often focus on tourism, while rural remote regions, such as those in Canada, Chile, Colombia, Finland, Mexico and the United States often also have an important share of the population with an Indigenous heritage that face distinct challenges.
The schematic breakdown is available in Figure 2.6.
Degree of Urbanisation (DEGURBA) classification
DEGURBA is a simple method of classifying areas that can be applied to every country in the world. The classification relies primarily on population size and density thresholds applied to a population grid with cells of 1 by 1 km. The types of areas classified by DEGURBA include the following:
Cities consist of contiguous grid cells that have a density of at least 1 500 inhabitants per km2 or are at least 50% built up. They must have a population of at least 50 000.
Towns and semi-dense areas consist of contiguous grid cells with a density of at least 300 inhabitants per km2 and are at least 3% built up. They must have a total population of at least 5 000.
Rural areas are cells that do not belong to a city or a town or a semi-dense area. Most of these have a density below 300 inhabitants per km2. The population grid used in this study is the Global Human Settlement Layer (GHSL) provided by the European Commission Joint Research Centre (Pesaresi et al., 2019[21]).
While useful for analysis based on areas that are at a lower unit of analysis than administrative borders, the use of the DEGURBA classification system allows for more direct comparison between attributes of areas, rather than regional or administrative boundaries that are used in the OECD classifications based on administrative units.
Sectoral classifications
The statistics gathered are harmonised with the International Standard Industrial Classification (ISIC 4th revision). For readability, the sectoral classifications are grouped into the following ten major sectoral groups during the analysis:
1. Agriculture: Agriculture, forestry and fishing (ISICr4 1-3) or Section A.
2. Mining: Mining and quarrying (ISICr4 5-9) or Sections B and D.
3. Manufacturing: Manufacturing including food, beverages and tobacco (ISICr4 10-12); Textiles and footwear (ISICr4 13-15); Wood and paper (ISICr4 16-18); Petroleum and chemicals (ISICr4 20-22); Metallics, computers, electrical and motor vehicles (ISICr4 23-30); and Other manufacturing (ISICr4 31-33) or Section C.
4. Utility and construction: Electricity, gas, water and waste management (ISICr4 34-39); and Construction (ISICr4 41-43) or Sections E and F.
5. Wholesale and retail trade, transportation and repair of motor vehicles: Wholesale and retail trade (ISICr4 45-47); and Transportation and storage (ISICr4 48-53) or Sections G and H.
6. Hospitality: Accommodation and services (ISICr4 55-56) or Section I.
7. Information and communication: Information and communication (ISICr4 58-63) or Section J.
8. Financial and real estate: Financial and insurance activities (ISICr4 64-66); Real estate (ISICr4 68) or Sections K and L.
9. Professional services: Professional, scientific and technical activities (ISICr4 69-75); and Administrative and support service activities (ISICr4 76-82, 99) or Sections M and N.
10. Public and community services: Public administration and defence (ISICr4 88); Education (ISICr4 85); Human health, residential care and social work (ISICr4 86-88); Arts and other service activities (ISICr4 90-98), or Sections P, Q, R.
For illustration purposes, some categories may be combined. In other cases, for privacy concerns, some sectoral categories had to be combined, or excluded.
Source: OECD (2020[1]), Rural Well-being: Geography of Opportunities, https://doi.org/10.1787/d25cef80-en; OECD (2018[22]) , Regions and Cities at a Glance, https://doi.org/10.1787/reg_cit_glance-2018-en
Table 2.2. Classification of Scottish administrative units in OECD 5-tier typology of small administrative units (TL3)
Classifications of Regions (TL3) into typologies as of March 2023
OECD region ID (TL3) |
Name |
Typology access to city |
---|---|---|
UKM50 |
Aberdeen City and Aberdeenshire |
MR-M |
UKM61 |
Caithness & Sutherland and Ross & Cromarty |
NMR-R |
UKM62 |
Inverness & Nairn and Moray, Badenoch & Strathspey |
NMR-R |
UKM63 |
Lochaber, Skye & Lochalsh, Arran & Cumbrae and Argyll & Bute |
NMR-R |
UKM64 |
Eilean Siar (Western Isles) |
NMR-R |
UKM65 |
Orkney Islands |
NMR-R |
UKM66 |
Shetland Islands |
NMR-R |
UKM71 |
Angus and Dundee City |
MR-L |
UKM72 |
Clackmannanshire and Fife |
NMR-M |
UKM73 |
East Lothian and Midlothian |
MR-M |
UKM75 |
Edinburgh, City of |
MR-M |
UKM76 |
Falkirk |
NMR-M |
UKM77 |
Perth & Kinross and Stirling |
NMR-M |
UKM78 |
West Lothian |
MR-M |
UKM81 |
East Dunbartonshire, West Dunbartonshire and Helensburgh & Lomond |
MR-L |
UKM82 |
Glasgow City |
MR-L |
UKM83 |
Inverclyde, East Renfrewshire and Renfrewshire |
MR-L |
UKM84 |
North Lanarkshire |
MR-L |
UKM91 |
Scottish Borders |
NMR-R |
UKM92 |
Dumfries & Galloway |
NMR-S |
UKM93 |
East Ayrshire and North Ayrshire mainland |
NMR-M |
UKM94 |
South Ayrshire |
NMR-M |
UKM95 |
South Lanarkshire |
MR-L |
Note: Explanations of regional codes, territorial classifications of small administrative units and typology based on access to cities are further explained in Box 2.2. In the case of Scotland, regional names are established within the same classification system as the rest of the United Kingdom and refer to upper tier authorities, groups of lower tier authorities, groups of unitary authorities, LECs, groups of districts of which there are 179 in the United Kingdom.
Source: OECD (2022[23]), OECD Territorial Grids, https://www.oecd.org/cfe/regionaldevelopment/territorial-grid.pdf.
Based on the Scottish rural classification system, over 5.46 million people lived in Scotland in 2019, with over 930 000 of them living in rural areas (Table 2.3). Rural Scotland accounts for 17% of the total population in Scotland (6% in remote rural and 11% in accessible rural) and has consistently done so since 2011. The population has increased in all areas of Scotland between 2011 and 2019 but only very slightly in remote rural where the increase was 0.1% or 221 people, while the greatest increase in population is seen in accessible rural, with an 8% increase between 2011 and 2019, compared to an increase of 3% in the rest of Scotland.
Although close to 1 in 6 individuals live in rural areas, 98% of the land mass is classified as rural in Scotland with 70% in remote rural and 28% in accessible rural. This rural nature of less populated and vast land area creates significant differences in population density. In comparison with the rest of Scotland, the population density of accessible rural is 102 times less and remote rural is 501 times less.
Table 2.3. Population and land share by threefold category
2011 |
2019 |
% change (2011-19) |
% of land area |
Population density (2019) |
|
---|---|---|---|---|---|
Remote rural |
315 945 |
316 166 (6%) |
0.1 |
70 |
4.06 |
Accessible rural |
573 407 |
616 536 (11%) |
8 |
28 |
28.25 |
Rest of Scotland |
4 410 548 |
4 530 598 (83%) |
3 |
2 |
2 906.7 |
Total |
5 299 900 |
5 463 300 (100%) |
3 |
100 |
Note: Population density (2019) is calculated based on the total land area of Scotland taken from the Office of National Statistics (2013[24]). Percentages in the 2019 column represent percentages of the total presented in the last row.
Source: Scottish Government (2021[25]), Rural Scotland Key Facts 2021, https://www.gov.scot/publications/rural-scotland-key-facts-2021/pages/2/; Office for National Statistics (2013[26]), Region and Country Profiles, https://www.data.gov.uk/dataset/0fb6b475-71d8-4085-b4bc-0e93f59a7d10/region-and-country-profiles.
Rural innovation
Innovation, defined by the Oslo Manual (OECD/Eurostat, 2018[27]), refers to the introduction of new or significantly improved products or processes to the firm or market (Box 2.3). It is often considered by governments as high-technology, high-investment innovations that have the possibility to fundamentally change an economy, sector or community. In this context, distance and density can be an attribute of some forms of innovation and a hindrance to others. For example, innovation based on fast interactions and high levels of competition can be driving some forms of innovation, however other forms of innovation flourish in isolation from competitive markets or are tied to local nature-based amenities.
In rural areas of Scotland, the traditional view of innovation, one with a high and fast frequency of exchanges with innovation partners, overlooks the attributes and comparative advantages of rural regions (Mayer, 2020[28]; OECD, 2022[10]). This would suggest that innovation itself, in addition to innovation diffusion and adoption, may be limited in rural regions. However, such an assumption precludes innovation as high-technology, based on quick interactions and firms that race to be first in the market. This overlooks businesses focusing on social purposes or local development, as often observed in rural areas (with social innovation in rural areas further discussed in Chapter 4). When studies have taken a territorial approach, this type of innovation is not as largely observed in rural areas as it is in dense cities. Economic geographers have started conceptualising alternatives, such as what is considered “slow innovation” (Shearmur and Doloreux, 2016[29]), which is the occurrence of innovation based on isolated development and limited but strategic interactions with partners. This leaves room for creativity based on fringe and unconventional ideas, shielded from pressures to deliver fast to markets (Mayer, 2020[28]). “Slow innovation” has the advantage of not being time-dependent, meaning it does not lose value rapidly, with a lower frequency of interactions and a strategic search for knowledge.
Box 2.3. Defining innovation from the 4th revision of the Oslo Manual (2018)
What is the Oslo Manual?
The Oslo Manual is a publication that outlines a commonly agreed-upon approach to measure and report statistics on innovations. Started in the early 1990s, the Oslo Manual was elaborated through the consensus of the OECD Working Party of National Experts on Science and Technology Indicators (NESTI) and has been adopted by over 80 countries. The guidance outlined in the manual is used by major international organisations and researchers worldwide. Its revision was conducted through consultation with both NESTI and Eurostat’s Community Innovation Survey (CIS) taskforce.
Defining innovation
The 4th edition of the Oslo Manual distinguishes between innovation as an outcome (an innovation) and the activities by which innovations come about (innovation activities). It defines innovation as “a new or improved product or process (or combination thereof) that differs significantly from the unit’s previous products or processes and that has been made available to potential users (product) or brought into use by the unit (process)” (OECD/Eurostat, 2018[27]).
The major additions to the previous versions include: measuring innovation not only from businesses but also other organisations and individuals; updates to improve harmonisation between core definitions and taxation; better accounting of globalisation, digitalisation and trends in investment in intangible assets; guidance on measuring internal and external factors influencing business innovation; prioritisation of the measurements of government policies on innovation; expansion on methodological guidelines; guidance on the use of innovation data and a new glossary.
Source: OECD/Eurostat (2018[27]), Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, https://doi.org/10.1787/9789264304604-en.
The structure of the rural economy of Scotland
To set the scene for innovation, it is important to understand the relative comparative advantage of rural areas today. The structure of the economy of rural areas is substantially different from the economy of urban areas. The section below illustrates a selection of rural firm characteristics that should be taken into consideration in the context of policy making directed towards firms for innovation in rural regions. The majority of the analysis in this section is based on analysis from three datasets, namely the UK Innovation Survey (UKIS),6 the Business Structure Database (BSD),7 with access given to the authors by the ONS, and the Inter-Departmental Business Register (IDBR), for which access to statistics for Scotland was made available through the Business in Scotland report (Scottish Government, 2022[30]). As described in the introduction, the analysis looks at each firm location (branch offices) rather than using the location of the headquarter as a basis for analysis and uses two waves of data from UKIS – Wave 7 and 10. Moreover, these two waves are merged into the BSD 2010 and BSD 2018 respectively, as the BSD provides additional information about firms’ profiles, including legal status, birth date and rural-urban classification. An analysis released that can be matched between the BSD and UKIS is released every two years, with a two-year delay. At the time of writing this report, the next year of analysis available from the BSD included data from the year 2020. Because of the substantial impact of the COVID-19 pandemic that caused a major shock to the economy, the inclusion of the year 2020 would bias many results based on a year of crisis. As such, while analysis is included for 2020, all regression results towards the end of the chapter use pre-crisis analysis.
Firms and labour in rural areas of Scotland
In OECD countries, a third of firms are in non-metropolitan areas. The share of firms in non-metropolitan regions close to small-sized cities is close to 15%, while those in non-metropolitan cities with access to metropolitan areas are 11% and those in rural remote regions are 7% (Figure 2.7 and Box 2.2 for OECD definitions). In Scotland, the share of all non-metropolitan regions is slightly higher than the OECD average at 36% but it has a larger share of remote regions (15%) and regions close to metropolitan areas (18%) than on average in OECD countries. Scotland’s share of remote rural regions is substantially larger (15%) as compared to 3% in the rest of the United Kingdom. The distribution of firms in non-metropolitan places is closer to those of France, or Austria where the shares of remote regions and those close to metropolitan areas are relatively stronger than regions with access to medium or small-sized cities.8
In 2022, there were 50 000 firms (27%) and close to 2 million workers (15%) in rural Scotland, based on the Scottish Government Urban Rural Classification.9 In 2022, Scotland’s accessible and remote rural areas had close to a third of firms and less than a fifth of the total Scottish labour force. The total non‑metropolitan (those outside of urban areas) firms and labour were higher. Close to two-fifths of firms and one-fifth of labour were in non-metropolitan areas of Scotland.
Figure 2.7. Share of enterprises in Scotland and OECD countries
![](/adobe/dynamicmedia/deliver/dm-aid--3d6c5b1f-62c7-49f6-bf6c-c35840fb14e8/image8.png?quality=80&preferwebp=true)
Note: Metropolitan regions (MR) include both large metropolitan regions (MR-L) and metropolitan regions (MR-M). The categories are further described in Box 2.2.
Source: OECD (n.d.[7]), OECD Regional Database, https://doi.org/10.1787/region-data-en.
Accessibility is an important characteristic of rural areas. In 2022, of the 27% of firms in Scotland located in rural areas, more than half (or 16% of the Scottish total) are in accessible rural areas. Likewise, while 15% (283 000 employees) of the total labour share are in non-urban areas of Scotland, two-thirds (10%) of the labour in non-urban Scotland are in accessible rural areas (Figure 2.8, Panel A).
The relatively stable share of firms and labour in accessible and remote rural areas saw a decrease in the period of 2018 to 2022. Despite this change, this relatively slowdown was not as substantial as in other areas. The aggregate changes in the shares of firms and labour in accessible and remote rural areas were outsized by the fall in the number of firms and labour from losses in other urban areas, and accessible small towns.
From 2015 to 2018, there was low growth in the number of firms in accessible and remote rural areas of Scotland but a relatively higher growth in the number of employees in accessible and remote rural areas (Figure 2.8, Panels C and D).10 While accessible rural areas and remote rural areas saw an increase in the number of firms in operation, the growth started at lower levels than in urban areas11 and grew to a lower extent (3.9% and 3.2% respectively).12
At the same time, between 2015 and 2018, firms in rural areas were beginning to show signs of scaling up. Labour in accessible and remote rural areas grew faster than those in all types of urban areas. In part, a stronger percentage growth is due to a lower number of workers in 2015;13 however, even the number of workers per firm increased from 2015 to 2018, from close to 5.68 to 5.79 workers per firm on average in rural areas, where as the number of workers per firm in urban areas fell from 13.79 to 13.46.
Figure 2.8. Territorial share of firms and labour in Scotland
![](/adobe/dynamicmedia/deliver/dm-aid--afaa8b58-b0c0-409b-b729-7d6184e23bbb/image9.png?quality=80&preferwebp=true)
Source: OECD analysis of the Business Structure Database (BSD) and the Inter-Departmental Business Register (IDBR).
Based on the aggregate analysis by geography type, rural firms were able to keep afloat during the period of the COVID-19 crisis but the same could not be said for workers. The percentage growth in the number of firms in the years of the pandemic was small, rural remote areas and accessible rural areas were not as disadvantaged during the time of the crisis as those in accessible or remote small towns. For the period of 2018-22, accessible rural areas saw only a small 0.01% fall in the number of firms, while remote rural areas observed a small (0.02%) but positive growth in firms (Figure 2.8, Panels C and D). However, total labour in remote rural areas fell relatively substantially by -2.2%. In accessible rural areas, labour grew marginally, at the same time as the share of firms fell. This suggests that they were rather insular from the large impacts observed in all other areas outside of the large urban areas. And furthermore, while the number of workers per firm fell in urban areas and on aggregate in rural areas, accessible rural areas saw marginal growth, while most of the loss of the number of workers per firm came from remote rural areas. Further analysis of the survival of firms and their employees can help understand the true impacts of the COVID‑19 crisis.
Accessible rural areas demonstrated more dynamism in growth in non-crisis years but suffered more substantially than remote rural areas during the years of the COVID-19 crisis. The differences between accessible rural areas and urban areas suggest that opportunities and challenges may also vary. Accessible rural areas are distinct from remote rural areas in both firm and labour geographical dynamics and tend to generally benefit from proximity to urban areas, where they may more easily draw upon shared resources, such as labour, capital and access to supply and goods markets. For example, while business activity and labour in accessible rural areas were growing more than those in rural remote areas prior to the crisis, during the years of the crisis, firm activity in more accessible areas was more negatively impacted than rural remote areas, while there were more substantial losses in labour in rural remote areas. Likewise, the argument is similar when comparing accessible small towns and remote small towns.
In sum, the analysis in this subsection indicated the following trends:
Scotland is less urbanised than the average OECD country. Close to a third of firms are in non‑metropolitan regions of OECD countries. Using the Scottish Government Urban Rural Classification system, in Scotland, this number is slightly larger at close to 40% of firms. In 2022, Scotland’s accessible and remote rural areas had close to a third of firms and less than a fifth of the total Scottish labour force.
Rural firms were showing signs of scaling up, prior to the 2018-22 period. However, during the COVID-19 period, there was less growth in the number of firms and a fall in the number of workers.
Accessible rural areas are distinct from rural remote areas. In 2022, there was a larger share of firms and employment in accessible rural areas. While the share of firms grew stronger in normal times, rural remote firms were more insulated. However, labour and shares of firms, in rural remote areas did not withstand the crisisand they experienced a large loss in labour over the period of 2018 to 2022.
Sectoral composition of non-metropolitan regions of Scotland
The sectoral composition of rural areas can inform policy makers of the importance of local sectors that should be taken into consideration while informing place-based policy making. In many OECD countries, rural regions are characterised by the existence of a strong manufacturing sector, a relatively high share of agricultural and fishery activities as compared to metropolitan regions and an increasing transition to the trade and services sectors (OECD, 2022[31]; forthcoming[32]). The following analysis in this section explores recent trends in sectoral composition in rural and urban areas, using the Scottish classification of areas aggregated to sixfold definitions.
Rural areas, like those across other regions in Scotland, have a strong trade and services14 component. In 2022, 40% of firms in remote rural areas and 47% of firms in accessible rural areas were in the trade and services sector (Figure 2.9). This sector accounted for 47% and 46% of jobs in remote rural and accessible rural areas. In 2015-18, jobs in trade and services saw a 72% growth in Scotland. While rural remote and accessible remote areas also observed growth in jobs in this sector (50% and 40% respectively), it was to a lesser extent than in other areas. The growth of jobs in this sector was relatively strongest in remote small towns, where it doubled. Despite this previous spell of sectoral growth, during the period of 2018-22, jobs in the trade and services sector in all areas, expect large urban areas, fell.
Figure 2.9. Sectoral distribution of firms and labour
![](/adobe/dynamicmedia/deliver/dm-aid--f168489f-6d37-4f1f-87c7-0e10cb63f6e6/image10.png?quality=80&preferwebp=true)
Note: The following categories are elaborated as the following: AgriFish includes Agriculture, forestry and fishing (A); Mining includes Mining (B) and quarrying (D), and Utilities (E); Manufacturing includes only the Manufacturing sector (C); Construction includes only construction (F); Trade and services include Wholesale, retail and repair (G), Transportation and storage (H), Information and communication (J), Accommodation and food service activities (I), Financial and insurance activities (K), Real estate activities (L), Professional, scientific and technical activities (M), Administrative and support service activities (N), Arts, entertainment and recreation (R), and Other service activities (S); Public works and services includes Education (P) and Human health and social work activities (Q). Data include private sector-only firms.
Source: Scottish Government analysis of the Office for National Statistics (ONS) and the IDBR.
The second largest sector present in rural areas is the agriculture and fisheries sector. In 2022, more than a third of firms were in the agriculture and fisheries sector in remote rural areas and a quarter of firms were in the same sector in accessible rural areas (in comparison, only 1% and 3% in large and other urban areas). However, the sector did not account for as large a share of jobs. For example, in rural remote areas, the agricultural and fisheries sector accounted for only 18% of jobs. Likewise, in accessible rural areas, while a quarter of firms were in the agricultural and fisheries sector, it only accounted for 15% of all employment. In 2015-18, the agricultural and fisheries sector observed a small growth of jobs in accessible rural areas and a small decline in rural remote areas. The largest employment growth in this sector was observed in remote small towns. However, in the following years, from 2018 to 2022, accessible rural areas saw a substantial increase in the number of individuals employed in the sector, which seems to have been the largest driving force for avoiding going into aggregate loss of employment, followed by growth in construction. On the other hand, the agricultural and fisheries sector (along with the construction sector) only grew marginally, which was a relative advantage given the strong falls in other sectors during the crisis years.
The manufacturing sector brings more jobs to non-metropolitan areas than metropolitan areas. Firms in the manufacturing sector account for between 5% to 7% of firms in all areas of Scotland. Despite the fact that firms in the sector are equally present across all areas of Scotland, it accounts for more jobs in non‑urban areas (Figure 2.9). In 2022, manufacturing firms accounted for 11% and 12% of total employment in remote rural and accessible rural areas, higher than the total share of employment in the aggregate sector in Scotland. Accessible small towns and remote small towns tend to also have relatively higher shares of employment in the sector (13% and 14% respectively).
Jobs in the manufacturing sector were growing substantially (40%) in the years 2015-18: this was second only to the growth in the trade and service sector in the same areas. The increase of jobs in this sector is relatively important for remote rural areas but not for accessible rural areas. In the years of the COVID-19 crisis, remote rural areas observed some growth in jobs in the sector, while accessible rural regions experienced a large fall.
Lastly, the public works and services sector is an important aspect of rural Scotland. The sector accounts for 18% of all jobs in Scotland in 2022; however, there is a lower percentage in accessible (13%) and remote rural areas (11%). This is particularly challenging as equitable deliveries of public services often require proportionally more resources in rural areas. It is unclear why public works and services would have experienced such a substantial fall in accessible rural areas during the period of 2018-22. It is a well-documented fact that many rural areas suffer from a lack of public services because of the difficulties in physical distances, however, in many cases, the choice of public service delivery models (public, private or through local civil society partners) impacts the way in which this statistic is observed. While the privatisation of historically publicly assured services can bring cost savings and efficiencies, this is only the case if access to services remains assured and of high quality, is appropriately managed and at the right scale for rural areas. A more equitable distribution of government services is often reflected in a larger share of public sector employees per resident in more remote regions, as argued by the OECD (2021[2]). Where there is no equitable access to public services, the role of civil society (including social enterprises and innovators) becomes increasingly important to help address market failures in the provision of public services, as will be further discussed in Chapter 4.
In sum, the analysis in this subsection indicated the following trends:
There is a strong trade and service component in rural areas. The share of trade and services is growing in rural areas in terms of numbers of firms and jobs but it is not contributing to as big a growth in jobs in rural areas as it is in urban areas. Rural remote and accessible remote areas observed a growth in jobs in this sector (50% and 40% respectively) but to a lesser extent than in other areas. It also fell substantially during the following period from 2018 to 2022, during the period of the COVID-19 crisis.
The agricultural and fisheries sector is still an important share of the rural economy but its contribution to jobs is not as sizeable as those in the trade and services sector. Despite this trend of a relatively weak contribution to new employment, the sector was critical for upholding jobs in rural areas during the period 2018-22, as it was the sector that grew most substantially in geographies across Scotland and was primarily responsible for avoiding strong aggregate losses in labour in accessible rural areas. In rural remote areas, there was neither a loss nor a gain in employment in the sector.
The manufacturing sector is a relatively small share of accessible and remote rural areas but it is increasingly growing. Its contribution to labour in remote rural areas is substantial and increasing.
There is a relatively low share of public works in rural areas of Scotland as compared to other places and it experienced a sharp fall. In most countries, because of the higher cost of delivery in rural areas, it is often the case that rural public services get left behind. However, this observation is also heavily impacted by the model of public service delivery in each country. Further information on the role of the third sector (civil society) is explored in Chapter 4.
Size-based composition of firms in Scotland
The location of firms has consequences on access to labour market resources and, therefore, their size. Where labour markets are tight, often firms operate with smaller numbers of employees or, if needs are great enough, transfer activities to accessible areas or areas with larger labour markets. The analysis in this section uses the OECD definitions of regions for comparative analysis across countries and the national Scottish definition of rurality for analysis within countries, as described in Box 2.2 and Table 2.1.
In Scotland, the quasi-totality of firms that employ individuals are small, with fewer than ten workers. In the OECD, the average share of firms with fewer than 10 workers was 98.5% of all firms (Figure 2.10). On average across OECD countries, the share is similar in metropolitan and non-metropolitan regions; however, 15 out of the 23 countries with available data had higher shares of firms with fewer than 10 workers in non-metropolitan areas.
Figure 2.10. Shares of firms with fewer than 10 workers
![](/adobe/dynamicmedia/deliver/dm-aid--3a18df9a-d659-4e36-ae83-365fed352f3d/image11.png?quality=80&preferwebp=true)
Note: Excludes Australia, Germany, Korea, Latvia, Malta, Sweden and the United Kingdom.
Source: OECD (n.d.[7]), OECD Regional Database, https://doi.org/10.1787/region-data-en.
In 2022, small non-employer or micro firms with one to ten employees were the most common type of firms in Scotland (Figure 2.11). They account for 85% of all firms15 in Scotland. In rural areas, firms with fewer than 10 employees accounted for a larger share of firms. In rural remote areas, 91% of firms had fewer than 10 employees, while in accessible areas, 90% of firms had fewer than 10 employees. In comparison, only 82% of firms had fewer than 10 employees in both types of urban areas.
Figure 2.11. Size distribution of firms, by sixfold Scottish classification
![](/adobe/dynamicmedia/deliver/dm-aid--72cda7e9-514d-460b-b5a0-df235ed9b420/image12.png?quality=80&preferwebp=true)
Source: Scottish Government analysis of the Office for National Statistics (ONS) IDBR.
While smaller firms are the most dominant form of firms in the rural economy, larger firms still employ a substantial share of workers. While firms with fewer than 10 employees represent around 90% of all firms in rural areas of Scotland, they only account for close to 45% of the total labour force in remote rural areas and 37% in accessible rural areas. When removing firms that do not employ individuals, this number goes down to 31% and 26% respectively but remains relatively high. On the other hand, despite a relatively low share of total firms, larger firms (those between 50-249 and above 250 workers) still employ a significant share of the labour force (29% in accessible rural and 20% in remote rural areas). In comparison, in urban areas, firms with fewer than 10 employees employ 15% of the workforce in large urban areas and 18% of the workforce in other urban areas.
Accessibility plays a role in the location of relatively larger firms. Accessible rural areas and towns tend to have relatively larger shares of large firms than remote towns and rural areas. Given relatively easier access to urban regions, there may be advantages to draw on in accessible rural areas and towns that are not necessarily feasible in remote areas. A specific approach to the challenges and opportunities in accessible areas should be considered separately from strategies to support innovation in other non-urban areas.
In sum, the analysis in this subsection indicated the following trends:
In the OECD, the average share of firms with fewer than 10 workers was 98.5% of all firms. In OECD countries, 15 out of the 23 countries with available data have a higher share of firms in non‑metropolitan areas.
In Scotland, small non-employer or micro firms with 1-10 employees were the most common type of firms in 2022, accounting for 85% of the share of all firms in Scotland. In accessible rural and remote rural areas, the share of small non-employer and micro firms is larger, at between 90% and 91%.
While smaller firms are the most dominant form of firms in the rural economy, they tend to employ only 45% of workers in rural remote areas and 27% in accessible rural areas. Larger firms still employ a substantial share of workers in both types of rural areas. In comparison, firms with fewer than 10 employees only account for 15% of labour in large urban areas and 18% of labour in other urban areas.
Firm age demography across rural areas of Scotland
In the innovation literature, creative destruction (the turnover of entrants and exiting firms) is an important mechanism for productivity growth and innovation (Aghion, Antonin and Bunel, 2021[33]). New firms tend to demonstrate entrepreneurial and innovative characteristics or push existing firms to become more innovative, in particular when there is a growing service sector (Bosma, Stam and Schutjens, 2009[34]). While age does not preclude firms to innovate, an environment that nurtures and encourages new endeavours can revitalise communities and rural regions (Breschi, Lassébie and Menon, 2018[35]). The analysis in this section uses the eight-tiered Scottish definition of rural areas to establish trends in the age demographic of firms across regions.
There are more new firms in urban and accessible areas of Scotland than in any type of rural area. According to Figure 2.12, the largest share of new firms (0-1 years) is in urban areas in 2018. In large urban areas, the share of young firms is 16%, while in other urban areas, it is lower at 9%. In accessible areas, the share of new firms was not too far from those in urban areas, in 2018. Accessible rural towns had 8% of all firms as start-ups, while accessible rural areas had a start-up share of 7% of all firms. Nevertheless, the places with the lowest shares of new firms are in remote rural areas (5%) and very remote rural areas (6%).
Urban areas also tend to have higher shares of young (2-5 years) firms. In large urban areas, 37% of firms are young, while the share changes only slightly for other urban areas (36%) (Figure 2.12). In very remote rural areas, the share of young firms is 20%, while it is similar in remote rural areas (21%). Young firms make up 33% of accessible small towns, while a quarter of the total firms in accessible rural areas are young.
Figure 2.12. Firms and labour, by firm age
![](/adobe/dynamicmedia/deliver/dm-aid--f45d2390-d978-42c0-91b5-474bc5da3e5c/image13.png?quality=80&preferwebp=true)
Note: All urban categories were removed from the bottom panel for depiction purposes. They are available for reference in Annex Figure 2.A.3. Data were not available for the year 2022.
Source: ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
Rural and remote regions tend to have older firms. While in urban areas, the share of older firms is between 24% to 30%, non-accessible rural areas and remote towns have substantially larger shares of mature firms ranging between 35% and 39% of firms in each area. The relationship between territories and firm demographics is similar when it comes to old firms (30 or more years old), where 5-8% of firms in urban areas are considered old, and old firms (30+) are 20-25% of rural economies (Figure 2.12).
Older firms do not employ as big of a share of workers in rural areas as they do in urban areas. While there may be a higher share of old firms in different types of rural areas than in urban areas, they do not always employ the highest shares of workers. For example, in accessible rural areas, firms that are more than 30 years old account for 20% of all firms and 38% of all workers, and likewise those in remote and very remote rural areas account for close to a quarter of all firms and around a third of all workers. However, older firms in urban areas account for 5-8% of the economy and employ between 38% and 28% of the labour force respectively.
Increasingly, start-ups (0-1 years) are employing more workers on average per firm from 2013 to 2018 (Figure 2.12). Based on shares of employees in start-ups in each geography, in very remote rural and remote rural areas, there is close to one more employee per two firms in a start-up than there was in the past. In comparison, in urban areas, the average number of employees per start-up has fallen (Annex Figure 2.A.3).
The old or traditional firm model in non-metropolitan areas is a common occurrence. However, it also poses a risk to communities that may depend on a small share of firms for jobs. Government officials should be mindful to target policies that can help bring in new entrepreneurs, and incubate and accelerate early-stage firms while providing services for upskilling and succession planning for pre-existing older firms that may need to adapt products or processes to stay competitive in the future.
In sum, the analysis in this subsection indicated the following trends:
The share of new firms (0-1 years) in various rural areas is less than half of those in urban areas. In large urban areas, the share of new firms is 16%, while it is 8% in accessible rural areas, 5% in remote rural areas and 6% in very remote rural areas.
Furthermore, there are close to 15-16% fewer young firms (2-5 years) in rural areas, as compared to urban areas. In large urban and other urban areas, between 36% and 37% of firms are young. In very remote rural areas, the share of young firms is 20%, while it is similar in remote rural areas (21%). Nevertheless, in accessible rural areas, the share of young firms is close to those in urban areas, at nearly a third of the economy (in accessible rural areas).
Increasingly, start-ups (0-1 years) are employing more workers on average per firm across all areas in Scotland. For example, in rural remote areas, there are close to twice as many workers per start‑up at the end of the period in 2018 as there were in 2015.
Rural and remote areas tend to have older firms (30 or more years old) but, unlike the older firms in urban areas, they do not tend to employ the largest shares of workers.
Trends in new firm formation and shares in the first few years of firm establishment in accessible rural areas, more closely follow trends in urban areas than in remote rural areas.
Foreign status of firms in rural areas
Access to foreign investment and international networks can encourage innovation in direct (R&D investment) and indirect (transference of knowledge) ways. Networks between individuals matter for innovation, in particular for new entrepreneurs (Diemer and Regan, 2022[37]). Foreign owners may provide a diversity of ideas and opportunities to firms that may otherwise be more difficult leading to new innovative products and processes. For example, a study on Spanish manufacturing firms found that multinational firms conduct more product and process innovation (simultaneously adopting new machines and organisational practices) and adopt foreign technologies, leading to higher productivity (Guadalupe, Kuzmina and Thomas, 2012[38]). The following section used the national Scottish classification of territories to overview trends in the ownership of firms across regions.
In 2018, foreign firms (non-UK) have a small share of the Scottish economy yet tend to employ more workers. In urban areas, they account for approximately 7% of firms in 2018. In non-urban areas, they rarely account for more than 5% of firms.16
Despite a small share, foreign firms contribute substantially to employment, as compared to national firms. The average number of employees per firm is higher among foreign firms than national firms. For example, in large urban areas, foreign firms employ on average over 100 individuals, while national firms employ on average close to 4.6 individuals per firm (Figure 2.13, Panel B, right-axis for national firms). More generally, foreign firms in urban areas (both large and other urban area categories) employ on average close to 100 individuals per firm, while foreign firms in rural areas (accessible, remote and very remote rural area categories) employ on average 45 individuals per firm. The national equivalents employ on average close to six workers per firm in urban areas and four workers per firm in rural areas. The foreign-to-national firm ratio in urban areas suggests that foreign firms employ 18 times more individuals than national firms in urban areas, while this ratio is smaller in rural areas at 10 times more employed individuals in foreign firms in rural areas.
The strong performance in employment of foreign firms is not observed to the same magnitude in rural areas as in urban areas. On average, foreign firms in urban areas employ 2.5 times more individuals per firm than in rural areas. For example, in large urban areas, foreign firms employ on average over 100 individuals per firm, while in accessible and remote rural areas, the average employment per foreign firm is between 20 to 45 employees, meaning that foreign firms in urban areas employ 2 to 5 times more individuals per firm than those in rural areas.
While it is not surprising that foreign firms, on average, employ more individuals, the agglomeration of foreign firms in urban areas seems to indicate a relative advantage that urban areas hold over rural regions, which may be due to access to labour, capital or other resources. Inviting foreign investment may be the goal of some regions. An active and targeted strategy to attract foreign investment and diversify the economy is already a strong factor of Scotland’s regional enterprise agencies, as described in Chapter 3. Access to regional foreign investment and promotion support could help bring additional opportunities for jobs and innovation through foreign investment.
Figure 2.13. Firms and labour, by foreign status, 2018
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Note: Data for 2022 were not available. In Panel B, national firms are depicted on the secondary right-hand axis.
Source: ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
In sum, the analysis in this subsection indicated the following trends:
The share of foreign firms in Scotland is small, at between 6% to 7% in rural areas and between 2% to 5% in rural areas.
Foreign firms employ 18 times more workers per firm than national firms in urban areas of Scotland, whereas they employ only 10 times more workers than national firms in rural areas of Scotland.
Foreign firms in urban areas employ 2 to 5 times more workers than foreign firms in rural areas. For example, in large urban areas, foreign firms employ on average over 100 individuals per firm, while in accessible and remote rural areas, the average employment per foreign firm is between 20 to 45 employees.
Promoting equal opportunities for innovation amid growth in rural Scotland
There has been a productivity slowdown in the UK in many major cities (OECD, 2020[39]). However, over the last 20 years, the economy of Scotland has observed stronger growth in productivity than all other regions in the United Kingdom with an average growth of real output per hour reaching up to 1.5% per annum (Tsoukalas, 2021[40]). While its levels of productivity still remain lower than the national average and below the median of OECD countries (Tsoukalas, 2021[40]), the growth in productivity relative to the rest of the United Kingdom and within Scotland has promising implications for innovation in rural areas.
Regional and territorial considerations are important factors in understanding where there are opportunities for welfare-enhancing growth through innovation and productivity. For example, in the United Kingdom, a recent study found that innovation and productivity spillovers are dependent on geographical and technological proximity to other firms and institutes undertaking research (Aitken et al., 2021[41]).
The following section focuses on three aspects of promoting welfare-enhancing productivity growth. The first section untangles whether productivity changes are due to increased productivity within regions or a reallocation of resources. The second section explores trends in competition between firms. Finally, the last section explores the importance of promoting diversity and equality for innovation. This study uses two datasets, namely UKIS and the BSD. The reasons behind choosing these two sources of data and linking them were, first, to ensure granularity for rural analysis and, second, to avoid biases in innovation measures that are better targeted for large, urban firms such as those measuring inputs (R&D investment or jobs) or outputs (patents) (OECD, 2022[10]).17
Growth in productivity across territories
Productivity is often closely linked to innovation and, in many cases, can be considered a measure of innovation adoption. An increase in productivity assumes the reduction in either costs or an increase of production within the firm that are often linked to improvements in the processes or products used in the production or business cycle, which is akin to the Oslo Manual’s definition of innovation (see Box 2.3 above).
In the past two decades, Scotland has recorded strong productivity growth (Tsoukalas, 2021[40]); however, the territorial dimension of productivity growth has not adequately been explored. Using data from UKIS matched with the Business Registrar, this analysis similarly observes growth in aggregate productivity over a period of 9 years between 2010 and 2018, reaching close to 0.07% annual productivity growth, in line with the trend that has been observed over the past 2 decades in OECD countries.
Productivity growth within Scotland is primarily attributed to productivity increases in accessible and remote rural regions (Figure 2.14). Almost all productivity growth in Scotland was due to productivity increases in remote rural regions (81.6% of total productivity growth). Likewise, another quarter (25%) of overall productivity growth was attributed to productivity increases in accessible rural regions. Finally, there is a net negative contribution to productivity growth in urban areas in the rest of Scotland (-6.6%).
Most productivity growth was attributed to the more efficient use of resources within rural remote areas (67% of total productivity growth), suggesting that innovation absorption in remote rural areas has played a substantial role in contributing to aggregate productivity increases. Furthermore, the reallocation of resources into both accessible and remote regions (between effect, 28.7% of total productivity) and the more efficient use of resources (within effect, 77.9% of total productivity) provide a net positive contribution to aggregate growth.
On the other hand, in urban areas in the rest of Scotland, the more efficient uses of resources contributed to 0.9% of aggregate productivity growth, while the reallocation of resources contributed negatively (-7.5%) to aggregate productivity growth. The effect of more efficient use of resources on aggregate productivity growth is much larger in remote rural areas. While at a lower magnitude, increases in the more efficient use of resources in accessible rural areas is lower. This may be explained by accessible rural areas’ relative ease of access to other firms at the frontier of innovation or, simply, close access to diversified services often present in accessible rural regions.
The simultaneous productivity growth in rural areas and fall in the rest of Scotland (urban areas and towns) can be characterised as a strong “catching up” effect, whereas the rest of Scotland (including all urban areas) is suffering from a loss of productivity. Importantly this joint observation suggests that there are still opportunities for growth within Scotland’s rural areas. Second, a large share of the contribution of productivity that is due to the more efficient use of resources suggests that there is still a margin of opportunity for increased productivity growth through place-based policy making focusing on improving conditions for businesses and communities in accessible and remote rural regions. This can include incentives for the reallocation of resources to rural areas and the development of programmes to support incentives to upgrade products and processes, for example through new firm products or through upskilling the rural labour supply.
Figure 2.14. Decomposition of productivity growth in Scotland, 2010-18
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Note: Productivity is calculated as value-added per full-time equivalent employee. The measure of productivity growth due to better use of sources within territorial categories is referred to as the “within” component, while the change in the difference between territorial categories is referred to as the “between” components. The decomposition is weighted by number of employees. It is further explained in Melitz and Polanec (2015[42]).
Source: OECD calculations using ONS North Ireland/DETI/BIS (2021[43]), UK Innovation Survey, 1994-2018: Secure Access, https://doi.org/10.5255/UKDA-SN-6699-7; and ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
In sum, the analysis in this subsection indicated the following trends:
Productivity was growing in Scotland prior to the years of the COVID-19 crisis.
This growth was primarily driven by growth in productivity in accessible and remote rural areas.
Much of the growth in productivity was due to the upgrading of resources in remote rural areas, suggesting that the “catching up” effect was a strong factor of productivity growth in the region.
The distribution of productivity between firms
Firms operate within a territory and have different access to resources, including labour and capital. When there are no barriers to access (or there are barriers but they are equal barriers to access for all firms), firms can operate in a competitive manner and share all profits (and by inference have the same productivity levels). This is important for innovation yet the relationship between competition, equality of access and innovation is not linear. Competition and innovation have a “U-shaped” relationship (Aghion et al., 2005[44]). Competition encourages innovation in highly competitive “neck-to-neck” markets, while it may discourage slower moving firms. In other cases, some competition can encourage growth, while too much of it can deter innovation (Hall, Graevenitz and Helmers, 2020[45]).
In rural regions, by definition, the low density of the region implies fewer firms and less direct competition within territories. Firms innovate in this space, with low competition and higher demand to innovate in order to overcome barriers to basic services (OECD, 2022[10]). While in some rural areas, industries are specialised, in many cases, the number of firms within a single industry is generally lower or may have lent themselves more easily to mergers and developing a collaborative or co-operative model to overcome challenges of scale. In a high-competition environment, we expect productivity to be equal between firms and firms to compete at the margins. At the same time, too much inequality, for example, when only very few firms are very productive, can stifle growth and productivity among the masses. The U-shaped relationship of competition and innovation still suggests that some inequality is needed for innovation but too much capture of the market by the few can hurt all other competitors.
In Scotland, firms in accessible and remote rural regions tend to be more equal productivity outcomes than firms in urban areas in the rest of Scotland. Using two common measures of inequality, the Gini index and share of top and bottom performers, rural regions of Scotland have more equality in the distribution of productivity between its firms than in urban areas in the rest of Scotland (Figure 2.15, Panels A and B). In accessible and remote rural areas, the Gini indicator for 2018 was 0.81 and 0.70 respectively. The Gini in urban areas in the rest of Scotland was 0.86.
Inequality in productivity and the distribution of productivity across firms can help explain what types of inequality exist within a place. In urban areas in the rest of Scotland, firms differ in productivity (Panel A) and simultaneously have a high level of productivity going to the top 10% of firms (Panel B). The top 10% of firms in urban areas in the rest of Scotland are 35 times more productive than the top 10% of firms. In comparison, rural remote regions have more equality of outcomes for firms than other regions (Panel A) and relatively less (although increasing) disparity between top and bottom performers (Panel B). In rural remote areas, the top 10% of firms are 30 times more productive than those in the bottom 10% of the productivity distribution. More equality in productivity outcomes between firms within each territory and a relatively low capture by the few at the top suggests a more equal share of outcomes for each firm in rural areas of Scotland.
Yet, there is evidence suggesting that productivity between firms is growing unequally. For example, productivity inequality in remote rural firms grew from 0.54 to 0.70 from 2010 to 2018 (Figure 2.15, Panel A). At the same time, the highest productive firms became more productive than those at the lower end. The top 10% of firms in rural remote areas were 10 times more productive than firms at the bottom 10% in 2010, while in 2018, that difference tripled (30 times more productive in 2018). For rural remote areas, the increase is quite substantial and may be influenced by a small share of firms in some of the dominant industries (for example, gas, oil or agriculture) making large gains.
Figure 2.15. Productivity and territorial inequality in Scotland
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Note: Productivity refers to value-added over full-time equivalent workers. The territorial Gini of productivity is the Gini indicator calculated based on the productivity of firms within each of the territories in 2010 and 2018. A Gini score of 0 demonstrates perfect equality and that productivity is driven by all firms equally contributing, while a Gini score of 1 indicates perfect inequality and that all productivity is driven by very few firms. The P90/P10 ratio refers to the ratio of the top 10th percentile share of the most productive firms over the bottom 10 share of the least productive firms in 2010 and 2018. There are 12 459 firms in the sample for the rest of Scotland, 1 896 firms in accessible rural areas and 1 412 firms in remote rural areas. Data are not available for analysis in 2022.
Source: ONS North Ireland/DETI/BIS (2021[43]), UK Innovation Survey, 1994-2018: Secure Access, https://doi.org/10.5255/UKDA-SN-6699-7; ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
In accessible rural areas, a high level of overall inequality in productivity (0.81 in Figure 2.15, Panel A) and a high level of the tail end of productivity dispersion (37 in Figure 2.15, Panel B) suggests that much of the growth inequality is driven by high and low performers. The high levels of productivity in the top 10th percentile of firms as compared to the bottom 10th percentile of firms in accessible rural areas means that while some firms in accessible rural regions may be able to make strong gains from access to urban areas, others are disproportionately disadvantaged.
In sum, the analysis in this subsection indicated the following trends:
Inequality between highly productive and less productive firms is lower in accessible and remote rural areas of Scotland.
Despite lower levels of inequality, inequality in productivity between firms grew from 2010 to 2018.
Promoting diversity and inclusion for innovation in rural Scotland
One substantial challenge to a varying degree in many rural areas of Scotland is access to labour. This hinders many firms from pursing innovation and new endeavours. While this challenge is common in many areas, rural areas increasingly suffer from demographic change, both in terms of age-based demographic change and, in some cases, population and labour market shrinkage. Labour and diversity of skills are critical levers for encouraging the development of new firms and an important resource to firms looking to upgrade and grow.
Most Scottish firms report actively working on inclusion measures such as a real living wage, flexible work measures, diversity and inclusion and measuring the gender pay gap. However, the share of firms participating in such measures tends to be slightly lower in remote rural and accessible rural areas (Figure 2.16). For example, two-thirds of all firms in Scotland report paying the real living wage18 for all staff, yet employers in accessible small towns are more likely to adhere, at 69% of firms versus the average of 65%, while only 63% of employers in accessible rural areas and 64% of those in remote rural areas adhere to the real living wage. Flexible work, diversity and inclusion and gender pay gap measures is also more likely to occur in urban areas than rural areas, although differences are all quite small at between 1% to 2% of firms. For gender diversity, despite the fact that over 30% of firms across different geographies of Scotland have committed to publishing the gender pay gap in firms, the pay gap remains across all areas of Scotland (Annex Table 2.A.1).
Older populations
Rural areas have a disproportionate share of older individuals, as identified in the first section of this chapter. In 2019, there were close to 10% more individuals over the age of 65% in remote rural areas and 4% more in accessible rural areas as compared to the rest of Scotland. The highest share of the population in accessible and remote rural areas is prime to older populations just before retirement (45 to 64 years of age). Less than 30% of those living in remote or accessible rural areas were between the ages of 16 and 44. Similarly, there is a higher share of older populations (65 and over) in remote rural areas. On the other hand, close to 2 out of 5 individuals, or 40% of individuals living in the rest of Scotland, are relatively young (16 to 44 years of age).
Figure 2.16. Share of firms reporting fair work measures, October 2022
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Note: Large urban areas and firms with more than 250 workers were not included in the original sample. Unknown responses are taken as non‑female-led firms. All estimates are weighted averages.
Source: OECD analysis of Scottish Government (2022[30]), Business in Scotland: 2022, https://www.gov.scot/publications/businesses-in-scotland-2022/.
Encouraging policies that seek to activate older workers, increase digitalisation or provide other skills upgrading incentives over the life cycle of workers is particularly important in rural areas. In addition, governments can encourage employers to increase incentives for older workers to return to work rather than take early retirement. This could help alleviate and take advantage of the local labour resources to keep the local economy alive. Likewise, supporting initiatives that encourage long-distance learning, on‑the-job learning or an early entrepreneurial connection with the local community can help encourage more young individuals to explore opportunities within rural areas. Skills and labour market resources for innovation are further discussed in Chapter 3.
Women in rural areas
In addition to age diversification, gender diversity and inclusion can help bring new ideas, skills and opportunities to regions. However, women often face challenges that are substantially different from the average native-born worker or entrepreneur.
As outlined in Figure 2.17 (Panel B), women are less likely to be employed than men in all areas across Scotland. In addition, in rural areas, women’s employment (as well as overall employment) is generally lower than in the rest of Scotland. Women in remote areas only have a 70% employment rate, as compared to males in rural areas (84%). Furthermore, when they are employed, women in remote rural regions on average have a lower median gross annual pay than men in all areas of Scotland (Annex Table 2.A.1). As described in Chapter 3, access to health services such as childcare and elderly care is also a critical factor that impacts women’s participation in the labour market.
The employment rate for women in Scotland is substantially better than the average rates in OECD countries, despite still being behind men. In 2020, 71% of women between the ages of 15 and 64 were employed, as compared to 75% of men in Scotland (Figure 2.18). This is much higher than the OECD average, where women’s employment rates are at 63% and men’s at 73% in non-metropolitan regions.
Figure 2.17. Demographic and employment distribution of rural areas, by territory, 2019
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Source: Scottish Government (2021[25]), Rural Scotland Key Facts 2021, https://www.gov.scot/publications/rural-scotland-key-facts-2021/pages/2/; Annual Population Survey, January to December 2019, ONS (Using Scottish Government Urban Rural Classification 2016).
Figure 2.18. Employment rates by gender, 2013-20
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Note: Data include AUS, AUT, CHE, CZE, DEU, ESP, GBR, HUN, IRL, ITA, KOR, LTU, LVA, SVK, SVN and SWE.
Source: OECD (n.d.[7]), OECD Regional Database, https://doi.org/10.1787/region-data-en.
There has been substantial progress for gender parity in labour force participation in Scotland.19 From 2012 to 2020, progress in gender equality in labour force participation rates in Scotland outperformed progress in other OECD countries (Figure 2.19). In 2020, the ratio of women in the active labour force as compared to men was 0.97, or close to parity. This is quite substantial as compared to the United Kingdom as a whole, where the ratio of women to men was close to 0.91, and in OECD countries, where the ratio was even lower at 0.82. This suggests that women are likely to continue to look for work or start their own firms despite the fact that employment shares may be lower.
Nevertheless, the ratio of women to men in the active labour force in non-metropolitan regions is still lagging behind those in metropolitan regions. For example, the ratio of female-to-male employment in 2019, prior to the first year of COVID-19, was 0.90 in non-metropolitan rural regions, while it was 0.99 in large metropolitan regions (Figure 2.19).20 As compared to the OECD, the lowest ratios of women to men in the active labour market were in non-metropolitan regions close to small or medium-sized cities (0.80 for both types of regions). However, this similar territorial trend is not observed in the United Kingdom where the labour force participation rate for women in non-metropolitan regions in the United Kingdom was higher than those in metropolitan regions. For example, in 2019, the ratio of women to men in the active labour market in large metropolitan regions was 0.88, while it was 0.93 in all 3 types of non-metropolitan regions. In 2020, the ratio of women to men in the active labour force in non-metropolitan regions reached 0.97 in non-metropolitan remote regions and 0.94 to 0.95 in other non-metropolitan regions.
There are relatively low levels of female entrepreneurship across all geographies of Scotland, as compared to men. In 2022, the share of female-led firms is only around 20% of firms in Scotland. Nevertheless, women tend to be more active as entrepreneurs in non-urban areas of Scotland (Figure 2.20). In accessible rural areas, close to a quarter of firms are identified as run by women. In remote small towns, the rate of female-led firms is even higher, at a third of all firms. The observation that women’s entrepreneurship is an important contributor to rural areas is persistent throughout many contexts. It is in line with findings in Canada and Switzerland (OECD, forthcoming[46]; 2022[31]). In Switzerland, the rate of female entrepreneurship outperformed all other neighbours despite a rural penalty and, in Canada, while women are more likely to start a firm in rural areas as compared to urban areas, they are less likely to apply for innovation-related tax relief programmes to support investment in formal R&D activities. Nevertheless, women face stronger challenges when it comes to attaining financial investments for scaling up (Guzman and Kacperczyk, 2019[47]), have different networking strategies (Neumeyer et al., 2018[48]) and have different risk profiles than men (Watson and Robinson, 2003[49]). Women in Scotland are more likely to have challenges in access to work-life balance (as primary caregivers), confidence in entrepreneurial capacity, lack of networks and formal support mechanisms, entrepreneurial mindset and access to finance (Stewart and Logan, 2023[50]). Because rural entrepreneurs similarly suffer from challenges in accessing networks and finance, female rural entrepreneurs face an accumulation of challenges. As such, programmes to support innovation and entrepreneurship need to think about how to better target the needs of female rural entrepreneurs.
Figure 2.19. Female-to-male labour force participation rates
Figure 2.20. Share of firms reporting being female-led, February 2022
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Note: Large urban areas and firms with more than 250 workers are not included in the original sample. Unknown responses are taken as non‑female-led firms. All estimates are weighted averages.
Source: OECD analysis of Scottish Government (2022[30]), Business in Scotland: 2022, https://www.gov.scot/publications/businesses-in-scotland-2022/.
Foreign-born individuals in rural areas
Diversity of national origin and immigrant status is often associated with the exchanging of new ideas and innovation (Akcigit, Grigsby and Nicholas, 2017[51]). Studies in the United States have shown that immigrants have higher rates of innovation and entrepreneurship than natives when comparing those with equivalent levels of education (Hunt, 2011[52]). In the United States, a quarter of high-technology innovation (patents) is attributed to high-skilled workers (Kerr, 2013[53]).Nevertheless, the location of where super-star inventors land varies more substantially based on local (country) taxation laws (Akcigit, Baslandze and Stantcheva, 2015[54]).
The share of the population in Scotland that is foreign-born (outside of Scotland and the United Kingdom) ranges between 5% to 10% of the population depending on where they are located, with the more urban ideas of Scotland having the highest shares (Table 2.4). While exact comparative data are not available for OECD countries, by geography, in 2019, the average share of the foreign-born population is close to 15% in OECD countries and 14% in the United Kingdom (OECD, 2023[55]). In remote rural areas of Scotland, there are 7% fewer international immigrants than in the rest of Scotland and 3% fewer in accessible rural areas (Table 2.4). In comparison, high-innovation cities like London (United Kingdom) are prone to having large shares of foreign-born populations. On the other hand, there is a larger share of migrants from other parts of the United Kingdom in remote rural and accessible rural regions than in urban areas in the rest of Scotland. Focusing on the needs of rural migrants, as is discussed in Chapter 3, is a critical resource of enabling innovation in rural areas.
In sum, the analysis in this subsection indicated the following trends:
Most Scottish firms report actively working on inclusion measures such as a real living wage, flexible work measures, diversity and inclusion and measuring the gender pay gap. However, the share of firms participating in such measures tends to be slightly lower in remote rural and accessible rural areas.
More can be done to encourage age diversity in rural areas.
Rural areas have a disproportionately larger share of older individuals and a smaller share of younger workers. In 2019, there were close to 10% more individuals over the age of 65% in remote rural areas and 4% more in accessible rural areas as compared to the rest of Scotland. Less than 30% of those living in remote or accessible rural areas were between the ages of 16 and 44, whereas in the rest of Scotland, the share was close to 40%.
Women are less active in employment in rural areas but are still active in the labour market in rural areas, including through entrepreneurship.
In rural areas, the overall employment level and women’s employment is generally lower than in the rest of Scotland. Women in remote areas only have a 70% participation rate as compared to males in rural areas (84%).
Nevertheless, women are still very active in the labour market in Scotland, with progress over the past decade reaching relative gender equality in labour force participation rates in Scotland. From 2012 to 2020, gender equality in labour force participation rates outperformed the progress on average in other OECD countries, suggesting that women are still looking for work or starting their own firms despite challenges in employment.
However, progress for women in labour force participation rates is not equal across regions. The ratio of female-to-male employment in 2019, prior to the first year of COVID-19, was 0.90 in non-metropolitan rural regions, while it was 0.99 in large metropolitan regions.
Despite relatively low overall levels of female entrepreneurship, there is a relatively equal rate of women-led firms in other urban and rural areas. In accessible rural areas close to a quarter of firms are identified as run by women. In remote small towns, the rate of female-led firms is even higher, at a third of all firms. The observation that women’s entrepreneurship is an important contributor to rural areas is persistent throughout many contexts.
Rural areas of Scotland are missing out on diversity that comes with a larger inflow of foreign-born individuals.
Table 2.4. Share of the population, by country of birth
By Threefold Urban Rural Classification, 2019
Remote rural (%) |
Accessible rural (%) |
Rest of Scotland (%) |
|
---|---|---|---|
Scotland |
73 |
77 |
80 |
Rest of United Kingdom |
22 |
17 |
10 |
Rest of world |
5 |
5 |
10 |
European Union |
3 |
3 |
5 |
Non-European Union |
2 |
3 |
5 |
Total |
100 |
100 |
100 |
Source: Scottish Government (2021[25]), Rural Scotland Key Facts 2021, https://www.gov.scot/publications/rural-scotland-key-facts-2021/pages/2/; Annual Population Survey, January to December 2019, ONS (Using Scottish Government Urban Rural Classification 2016).
Innovation in Scotland
Innovation is a precursor of long-term growth, productivity and, in some cases, well-being (Aghion and Howitt, 1990[56]; OECD, 2016[57]; Romer, 1990[58]). Enhancing the creation, adoption and diffusion of innovative products and processes21 is often a target of policy makers and community leaders alike. While innovation can also be destructive and vary across industries and geographies (Autor, 2014[59]; McCann, 2019[60]), creative destruction in itself is a driver of innovation and resilient economies (Aghion, Antonin and Bunel, 2021[33]). This report considers that on average, innovation occurs and affects societies differently in rural regions than in urban regions, primarily due to the underlying sectoral, occupational and territorial attributes that characterise low-density areas with longer distances from metropolitan FUAs (OECD, 2020[1]). The characteristics of firms in different geographical areas are relatively important for firm-based innovation in the United Kingdom. A recent study on UKRI support for R&D and innovation grants demonstrated that in what the authors refer to as peripheral areas, such as Northern Ireland, investing in innovation had positive impacts on employment and turnover, in particular for smaller firms (Vanino, Roper and Hewitt-Dundas, 2022[61]).
Following the literature review, our current knowledge of drivers of innovation and rural development tells us that:
Innovation is a predecessor of growth but not necessarily well-being for all territories (Aghion and Howitt, 1990[56]; OECD, 2016[57]; Romer, 1990[58]; McCann, 2019[60]).
Framework conditions, such as access to labour, capital, markets and public services, encourage innovation and innovation adoption and diffusion but can be better targeted to satisfy the structure of rural regions (Aghion et al., 2001[62]; Andersson et al., 2009[63]; Bloom, Draca and Van Reenen, 2016[64]; Goos, Manning and Salomons, 2014[65]; Grossman and Helpman, 1990[66]; OECD, 2013[67]; 2020[1]).
Innovation and its diffusion and adoption occur in networks and can be a source of growth for rural areas if barriers to physical and digital distances can be addressed (Akcigit, Grigsby and Nicholas, 2017[68]; Lengyel et al., 2020[69]; Sorenson, 2018[70]; Ahrend et al., 2017[71]).
Innovation can be driven by many of the aforementioned factors related to firm and labour characteristics. In terms of summary statistics, the rate of self-reported innovation activities in firms in Scotland fell from 2010 to 2018 in rural areas as well as in the rest of Scotland. In rural areas (accessible and remote rural), the share of firms reporting having participated in an innovative activity fell from 16.10% in 2010 to 13.73% in 2018, while a smaller fall occurred in the rest of Scotland (18.55% in 2010 to 17.18% in 2018). However, descriptive statistics are unable to jointly determine the relevance of any one characteristic in determining innovation. In the following section, the analysis uses UKIS and the Business Registrar in 2019 to jointly explore the determinants of self-reported innovation.22
Table 2.5. Share of total firms with new-to-firm or new-to-market innovations
Percentage of innovative firms in Scotland, 2010 and 2018
Year |
Geography |
Innovative firms (new-to-firm or -market) (%) |
---|---|---|
2010 |
Urban (rest of Scotland) |
18.55 |
Rural (accessible and remote rural) |
16.10 |
|
2018 |
Urban (rest of Scotland) |
17.18 |
Rural (accessible and remote rural) |
13.73 |
Note: Percentages are the shares of each category that report having introduced a new innovation to the firm or to the market. For confidentiality purposes, the summary statistics were aggregated into a dichotomous rural-urban category. The urban category refers to the previously identified “rest of Scotland”, whereas the rural category is an agglomeration of the accessible and remote rural categories.
Source: ONS North Ireland/DETI/BIS (2021[43]), UK Innovation Survey, 1994-2018: Secure Access, https://doi.org/10.5255/UKDA-SN-6699-7; ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
Taking into account firm characteristics that vary in different places in Scotland, there is no clear evidence that the location of the firm alone matters for innovation in Scotland. No matter how territories were categorised, no territorial characteristic in itself was associated with a direct penalty on self-reported innovation but rather characteristics of rural areas that created challenges. For example, as compared to accessible rural areas, both the remote rural and rest of Scotland tend to have higher innovation rates, but the difference is not significant (Table 2.6, column 3).23 The only time that location mattered for innovation was if the firm was located in Edinburgh: indeed, firms in the university capital are more likely to innovate but not those in the industrial capital of Glasgow. Likewise, while we know that the international literature suggests that the manufacturing sector is relatively innovative in high-technology innovation, in Scotland, the sector of the firm does not have an impact on self-reported innovation.
The size and age of firms have a significant impact on innovation. According to Table 2.6, Column 3, large firms innovate, regardless of where they are located, while the oldest firms are the least likely to innovate.
Large firms (250 or more employees) have a 0.077 higher probability of innovation than small firms. Medium-large-sized firms (100-250 employees) are 5% more likely to innovate than small firms.
Younger firms are more likely to innovate than older firms. The oldest firms (30 or more years of age) are 0.05 less likely to innovate than younger firms.
In the first section of this report, the descriptive statistics demonstrated that, in rural regions, firms tend to be smaller, older, more often in trade and services or agriculture and less often have foreign ownership. However, taken together, it is the structure of rural economies that is hindering more innovation and absorption, rather than the region itself. Some of the challenges are specifically related to being able to scale up and better understand the market.
Table 2.6. Marginal probability of innovating, 2018
Linear regression model
(1) |
(2) |
(3) |
(4) |
|
---|---|---|---|---|
Urban |
0.00528 (0.0231) |
|||
Remote rural |
0.0231 (0.0466) |
|||
Rest of Scotland |
0.0128 (0.0258) |
|||
Non-metropolitan |
-0.0252 (0.0205) |
|||
Medium |
0.00531 (0.0224) |
0.00528 (0.0224) |
0.00582 (0.0224) |
0.00379 (0.0223) |
Medium-large |
0.0481* (0.0263) |
0.0477* (0.0263) |
0.0484* (0.0263) |
0.0462* (0.0262) |
Large |
0.0763** (0.0319) |
0.0759** (0.0319) |
0.0769** (0.0319) |
0.0729** (0.0318) |
Mature |
-0.00222 (0.0224) |
-0.00223 (0.0224) |
-0.00242 (0.0224) |
-0.00208 (0.0224) |
Old |
-0.0471** (0.0232) |
-0.0472** (0.0232) |
-0.0472** (0.0232) |
-0.0467** (0.0232) |
Food and beverage |
0.155 (0.122) |
0.155 (0.122) |
0.155 (0.121) |
0.163 (0.124) |
Textiles |
0.0381 (0.122) |
0.0383 (0.122) |
0.0358 (0.121) |
0.0473 (0.126) |
Other manufacturing |
0.102 (0.0895) |
0.101 (0.0894) |
0.103 (0.0892) |
0.109 (0.0919) |
Wholesale retail |
-0.0326 (0.0659) |
-0.0328 (0.0658) |
-0.0322 (0.0657) |
-0.0267 (0.068) |
Transportation |
-0.0833 (0.0622) |
-0.0832 (0.0622) |
-0.0836 (0.0619) |
-0.0774 (0.0638) |
Information and communication technology |
0.0429 (0.0805) |
0.0421 (0.0803) |
0.0425 (0.0801) |
0.0495 (0.0828) |
Financial and insurance |
-0.0631 (0.06) |
-0.0631 (0.06) |
-0.0632 (0.0598) |
-0.0589 (0.0622) |
Public works and services |
-0.0606 (0.0591) |
-0.0607 (0.059) |
-0.0605 (0.0589) |
-0.0563 (0.0609) |
Foreign ownership |
0.0446 (0.0402) |
0.0445 (0.0401) |
0.0454 (0.0403) |
0.0424 (0.0397) |
Edinburgh |
0.0961*** (0.0347) |
0.0947*** (0.0351) |
0.0952*** (0.0352) |
0.0797** (0.0361) |
Glasgow |
-0.0082 (0.0272) |
-0.00948 (0.0275) |
-0.00926 (0.0275) |
-0.0209 (0.028) |
Observations |
2 493 |
2 493 |
2 493 |
2 493 |
Year dummies |
Yes |
Yes |
Yes |
Yes |
Note: Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1.
Source: ONS North Ireland/DETI/BIS (2021[43]), UK Innovation Survey, 1994-2018: Secure Access, https://doi.org/10.5255/UKDA-SN-6699-7; ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
Annex 2.A. Additional statistics and analysis
Annex Figure 2.A.1. Average GHG emissions, 2018
Annex Figure 2.A.2. Total GHG emissions, by typology and sector, 2018
Annex Figure 2.A.3. Additional firm age demographics graphs by eight-tier Scottish classification
![](/adobe/dynamicmedia/deliver/dm-aid--a108cd5f-3d86-423a-8ee9-ecc40bba8129/image24.png?quality=80&preferwebp=true)
Note: Geographical categories are available for reference in Table 2.1.
Source: ONS (2021[36]), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, https://doi.org/10.5255/UKDA-SN-6697-12.
Annex Table 2.A.1. Residence-based median gross annual pay for full-time employees by threefold category, 2020
Remote rural (GBP) |
Accessible rural (GBP) |
Rest of Scotland (GBP) |
|
---|---|---|---|
Female |
27 231 |
31 678 |
28 405 |
Male |
32 021 |
35 556 |
34 044 |
All |
29 652 |
34 311 |
31 531 |
Note: Payment is the calculation before taxation and other deductions.
Source: Scottish Government (2021[25]), Rural Scotland Key Facts 2021, https://www.gov.scot/publications/rural-scotland-key-facts-2021/pages/2/; Annual Survey of Hours and Earnings, 2016, ONS (Using Scottish Government Urban Rural Classification 2013-14).
References
[33] Aghion, P., C. Antonin and S. Bunel (2021), The Power of Creative Destruction, Harvard University Press, https://doi.org/10.4159/9780674258686.
[44] Aghion, P. et al. (2005), “Competition and innovation: An inverted-U Relationship”, The Quarterly Journal of Economics, Vol. 120/2, pp. 701-728, https://doi.org/10.1093/qje/120.2.701.
[62] Aghion, P. et al. (2001), “Competition, imitation and growth with step-by-step innovation”, Review of Economic Studies, Vol. 68/3, pp. 467-492, https://doi.org/10.1111/1467-937x.00177.
[56] Aghion, P. and P. Howitt (1990), “A model of growth through creative destruction”, No. 3223, National Bureau of Economic Research.
[71] Ahrend, R. et al. (2017), “What makes cities more productive? Evidence from five OECD countries on the role of urban governance”, Journal of Regional Science, Vol. 57/3, pp. 385-410, https://doi.org/10.1111/jors.12334.
[41] Aitken, A. et al. (2021), “From ideas to growth: Understanding the drivers of innovation and productivity across firms, regions and industries in the UK”, https://www.niesr.ac.uk/wp-content/uploads/2021/12/Understanding-the-Drivers-of-Innovation-and-Growth.pdf.
[54] Akcigit, U., S. Baslandze and S. Stantcheva (2015), “Taxation and the international mobility of inventors”, No. 21024, National Bureau of Economic Research.
[51] Akcigit, U., J. Grigsby and T. Nicholas (2017), “Immigration and the rise of American ingenuity”, American Economic Review, Vol. 107/5, pp. 327-331, https://doi.org/10.1257/aer.p20171021.
[68] Akcigit, U., J. Grigsby and T. Nicholas (2017), “The rise of american ingenuity: Innovation and inventors of the golden age”, No. 23047, National Bureau of Economic Research.
[63] Andersson, F. et al. (2009), “Reaching for the stars: Who pays for talent in innovative industries?”, The Economic Journal, Vol. 119/538, pp. F308-F332, https://doi.org/10.1111/j.1468-0297.2009.02277.x.
[14] Audretsch, D. and I. Peña-Legazkue (2012), “Entrepreneurial activity and regional competitiveness: An introduction to the special issue”, Small Business Economics, Vol. 39/3, pp. 531-537, https://doi.org/10.1007/S11187-011-9328-5.
[59] Autor, D. (2014), “Polanyi’s paradox and the shape of employment growth”, No. 20485, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w20485.
[64] Bloom, N., M. Draca and J. Van Reenen (2016), “Trade induced technical change? The impact of Chinese imports on innovation, IT and productivity”, The Review of Economic Studies, Vol. 83/1, pp. 87-117.
[34] Bosma, N., E. Stam and V. Schutjens (2009), “Creative destruction and regional productivity growth: Evidence from the Dutch manufacturing and services industries”, Small Business Economics, Vol. 36/4, pp. 401-418, https://doi.org/10.1007/s11187-009-9257-8.
[35] Breschi, S., J. Lassébie and C. Menon (2018), “A portrait of innovative start-ups across countries”, OECD Science, Technology and Industry Working Papers, No. 2018/2, OECD Publishing, Paris, https://doi.org/10.1787/f9ff02f4-en.
[37] Diemer, A. and T. Regan (2022), “No inventor is an island: Social connectedness and the geography of knowledge flows in the US”, Research Policy, Vol. 51/2, p. 104416, https://doi.org/10.1016/j.respol.2021.104416.
[18] EC (2023), “Getting to know EU’s regions: The European Commission launches the rural observatory”, European Commission, https://agriculture.ec.europa.eu/news/getting-know-eus-regions-european-commission-launches-rural-observatory-2023-01-26_en.
[3] EC (2021), Regional Innovation Scoreboard 2021, European Commission, https://data.europa.eu/doi/10.2873/674111.
[19] Fadic, M. et al. (2019), “Classifying small (TL3) regions based on metropolitan population, low density and remoteness”, OECD Regional Development Working Papers, No. 2019/06, OECD Publishing, Paris, https://doi.org/10.1787/b902cc00-en.
[13] Ferreira, J., C. Fernandes and M. Raposo (2015), “The effects of location on firm innovation capacity”, Journal of the Knowledge Economy, Vol. 8/1, pp. 77-96, https://doi.org/10.1007/S13132-015-0281-4.
[15] Freshwater, D. et al. (2019), “Business development and the growth of rural SMEs”, OECD Regional Development Working Papers, No. 2019/07, OECD Publishing, Paris, https://doi.org/10.1787/74256611-en.
[65] Goos, M., A. Manning and A. Salomons (2014), “Explaining job polarization: Routine-biased technological change and offshoring”, American Economic Review, Vol. 104/8, pp. 2509-2526, https://doi.org/10.1257/aer.104.8.2509.
[66] Grossman, G. and E. Helpman (1990), “Trade, innovation, and Growth”, The American Economic Review, Vol. 80/2, pp. 86-91, http://www.jstor.org/stable/2006548.
[38] Guadalupe, M., O. Kuzmina and C. Thomas (2012), “Innovation and foreign ownership”, American Economic Review, Vol. 102/7, pp. 3594-3627, https://doi.org/10.1257/aer.102.7.3594.
[47] Guzman, J. and A. Kacperczyk (2019), “Gender gap in entrepreneurship”, Research Policy, Vol. 48/7, pp. 1666-1680, https://doi.org/10.1016/j.respol.2019.03.012.
[45] Hall, B., G. Graevenitz and C. Helmers (2020), “Technology entry in the presence of patent thickets”, Oxford Economic Papers, Vol. 73/2, pp. 903-926, https://doi.org/10.1093/oep/gpaa034.
[11] Hall, J. (2008), “Adding meaning to measurement: Evaluating trends and differences in innovation capacity among the states”, Economic Development Quarterly, Vol. 23/1, pp. 3-12, https://doi.org/10.1177/0891242408326467.
[12] Hamidi, S., A. Zandiatashbar and A. Bonakdar (2019), “The relationship between regional compactness and regional innovation capacity (RIC): Empirical evidence from a national study”, Technological Forecasting and Social Change, Vol. 142, pp. 394-402, https://doi.org/10.1016/J.TECHFORE.2018.07.026.
[52] Hunt, J. (2011), “Which immigrants are most innovative and entrepreneurial? Distinctions by entry visa”, Journal of Labor Economics, Vol. 29/3, pp. 417-457, https://doi.org/10.1086/659409.
[53] Kerr, W. (2013), “US high-skilled immigration, innovation, and entrepreneurship: Empirical approaches and evidence”.
[69] Lengyel, B. et al. (2020), “The role of geography in the complex diffusion of innovations”, Scientific Reports, Vol. 10/1, https://doi.org/10.1038/s41598-020-72137-w.
[28] Mayer, H. (2020), “Slow innovation in Europe’s peripheral regions: Innovation beyond acceleration”, ISR-Forschungsberichte, Vol. 51, pp. 8-21, https://doi.org/10.1553/isr_fb051s8.
[60] McCann, P. (2019), “Perceptions of regional inequality and the geography of discontent: Insights from the UK”, Regional Studies, Vol. 54/2, pp. 256-267, https://doi.org/10.1080/00343404.2019.1619928.
[42] Melitz, M. and S. Polanec (2015), “Dynamic Olley-Pakes productivity decomposition with entry and exit”, RAND Journal of Economics, Vol. 46/2, https://doi.org/10.1111/1756-2171.12088.
[48] Neumeyer, X. et al. (2018), “Entrepreneurship ecosystems and women entrepreneurs: A social capital and network approach”, Small Business Economics, Vol. 53/2, pp. 475-489, https://doi.org/10.1007/s11187-018-9996-5.
[5] NRS (2021), Population Estimates by 6-fold Urban Rural Classification, 2001-2020, National Records of Scotland, https://www.nrscotland.gov.uk/files//statistics/population-estimates/special-area-2011-dz/urban-rural/urban-rural-20-tab-1.xlsx.
[55] OECD (2023), “Foreign-born population (indicator)”, https://doi.org/10.1787/5a368e1b-en (accessed on 5 April 2023).
[31] OECD (2022), Enhancing Innovation in Rural Regions of Switzerland, OECD Rural Studies, OECD Publishing, Paris, https://doi.org/10.1787/307886ff-en.
[6] OECD (2022), OECD Regions and Cities at a Glance 2022, OECD Publishing, Paris, https://doi.org/10.1787/14108660-en.
[23] OECD (2022), OECD Territorial Grids, OECD Centre for Entrepreneurship, SMEs, Regions and Cities, Paris, https://www.oecd.org/cfe/regionaldevelopment/territorial-grid.pdf.
[10] OECD (2022), Unlocking Rural Innovation, OECD Rural Studies, OECD Publishing, Paris, https://doi.org/10.1787/9044a961-en.
[8] OECD (2021), OECD’s Rural Agenda for Climate Action, OECD Centre for Entrepreneurship, SMEs, Regions and Cities, Paris, https://www.oecd.org/regional/rural-development/Rural-Agenda-for-Climate-Action.pdf.
[2] OECD (2021), Policies for Present and Future Service Delivery Across Territories, OECD, Paris.
[39] OECD (2020), Enhancing Productivity in UK Core Cities: Connecting Local and Regional Growth, OECD Urban Policy Reviews, OECD Publishing, Paris, https://doi.org/10.1787/9ef55ff7-en.
[1] OECD (2020), Rural Well-being: Geography of Opportunities, OECD Rural Studies, OECD Publishing, Paris, https://doi.org/10.1787/d25cef80-en.
[22] OECD (2018), OECD Regions and Cities at a Glance 2018, OECD Publishing, Paris, https://doi.org/10.1787/reg_cit_glance-2018-en.
[57] OECD (2016), OECD Regional Outlook 2016: Productive Regions for Inclusive Societies, OECD Publishing, Paris, https://doi.org/10.1787/9789264260245-en.
[67] OECD (2013), Regions and Innovation: Collaborating across Borders, OECD Reviews of Regional Innovation, OECD Publishing, Paris, https://doi.org/10.1787/9789264205307-en.
[46] OECD (forthcoming), Enhancing Innovation in Rural Regions of Canada, OECD Rural Studies, OECD Publishing, Paris.
[32] OECD (forthcoming), Enhancing Innovation in Rural Regions of the United States, OECD Rural Studies, OECD, Paris.
[7] OECD (n.d.), OECD Regional Database, OECD, Paris, https://doi.org/10.1787/region-data-en.
[27] OECD/Eurostat (2018), Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, The Measurement of Scientific, Technological and Innovation Activities, OECD Publishing, Paris/Eurostat, Luxembourg, https://doi.org/10.1787/9789264304604-en.
[36] ONS (2021), Business Structure Database, 1997-2020: Secure Access [data collection] 12th Edition, UK Data Service, Office for National Statistics, https://doi.org/10.5255/UKDA-SN-6697-12.
[26] ONS (2013), Region and Country Profiles, Office for National Statistics, UK Government, https://www.data.gov.uk/dataset/0fb6b475-71d8-4085-b4bc-0e93f59a7d10/region-and-country-profiles.
[24] ONS (2013), Region and Country Profiles, Key Statistics, December 2013, Office for National Statistics, UK Government, https://webarchive.nationalarchives.gov.uk/ukgwa/20151014064946/http://www.ons.gov.uk/ons/rel/regional-trends/region-and-country-profiles/key-statistics--december-2013/index.html.
[43] ONS North Ireland/DETI/BIS (2021), UK Innovation Survey, 1994-2018: Secure Access, Office for National Statistics, North Ireland, Department of Enterprise, Trade and Investment, Department for Business, Innovation and Skills, https://doi.org/10.5255/UKDA-SN-6699-7.
[21] Pesaresi, M. et al. (2019), GHS-SMOD R2019A - GHS settlement layers, updated and refined REGIO model 2014 in application to GHS-BUILT R2018A and GHS-POP R2019A, multitemporal (1975-1990-2000-2015) - OBSOLETE RELEASE., https://doi.org/10.2905/42E8BE89-54FF-464E-BE7B-BF9E64DA5218.
[58] Romer, P. (1990), “Endogenous technological change”, Journal of Political Economy, Vol. 98/5, part 2, pp. S71-S102, https://www.jstor.org/stable/2937632.
[30] Scottish Government (2022), Business in Scotland: 2022, Scottish Government, https://www.gov.scot/publications/businesses-in-scotland-2022/.
[20] Scottish Government (2022), Scottish Government Urban Rural Classification 2020, https://www.gov.scot/publications/scottish-government-urban-rural-classification-2020/pages/2/.
[25] Scottish Government (2021), Rural Scotland Key Facts 2021, https://www.gov.scot/publications/rural-scotland-key-facts-2021/pages/2/.
[9] Scottish Government (2020), Scottish Energy Statistics Hub, https://scotland.shinyapps.io/sg-energy/?Section=Other&Chart=TargetTracker.
[17] Scottish Government (2018), Scottish Government Urban Rural Classification 2016, https://www.gov.scot/publications/scottish-government-urban-rural-classification-2016/pages/2/#:~:text=Categories%205%20and%206%20are,(6)%20Remote%20Rural%20Areas.
[16] Shearmur, R., C. Carrincazeaux and D. Doloreux (2016), “The geographies of innovations: Beyond one-size-fits-all”, in Handbook on the Geographies of Innovation, Edward Elgar Publishing, https://doi.org/10.4337/9781784710774.00006.
[29] Shearmur, R. and D. Doloreux (2016), “How open innovation processes vary between urban and remote environments: Slow innovators, market-sourced information and frequency of interaction”, Entrepreneurship & Regional Development, Vol. 28/5-6, pp. 337-357, https://doi.org/10.1080/08985626.2016.1154984.
[70] Sorenson, O. (2018), “Innovation policy in a networked world”, Innovation Policy and the Economy, Vol. 18, pp. 53-77, https://doi.org/10.1086/694407.
[50] Stewart, A. and M. Logan (2023), Pathways: A New Approach for Women in Entrepreneurship, https://www.gov.scot/publications/pathways-new-approach-women-entrepreneurship/ (accessed on 10 April 2023).
[40] Tsoukalas, J. (2021), “Scotland’s productivity challenge: Exploring the issues”, Productivity Insights Paper, No. 006, The Productivity Institute, https://www.productivity.ac.uk/wp-content/uploads/2021/11/PIP006-Scotlands-Productivity-Challenge-FINAL-011221.pdf.
[4] UK BEIS (2022), UK Innovation Survey 2021: Report Covering the Survey Period 2018 to 2020, UK Department for Business, Energy and Industrial Strategy, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1074069/UK_Innovation_Survey_2021_Report.pdf.
[61] Vanino, E., S. Roper and N. Hewitt-Dundas (2022), “Assessing the business growth and productivity effects of Invest NI and UKRI grant support for R&D and innovation”.
[49] Watson, J. and S. Robinson (2003), “Adjusting for risk in comparing the performances of male- and female-controlled SMEs”, Journal of Business Venturing, Vol. 18/6, pp. 773-788, https://doi.org/10.1016/s0883-9026(02)00128-3.
Notes
← 1. For example, one entrepreneur from a food and beverages company in the north of Scotland grew substantially through the period of COVID-19 lockdowns by creating a circular model of product delivery that involved co‑ordination with public sector services (postal) and a subscription-based model that simplified access to their products, with the opportunity to return the remaining packaging for reuse or recycling.
← 2. Given the economic structure of rural areas, this production-based analysis of GHG emissions can only provide part of the picture on progress towards reaching climate change goals.
← 3. See Office for National Statistics North Ireland/DETI/BIS (2021[43]).
← 4. Office for National Statistics (2021), Business Structure Database, 1997-2020: Secure Access (data collection), 12th Edition, UK Data Service, http://doi.org/10.5255/UKDA-SN-6697-12.
← 5. Because of lag times in release of UKIS and the BSD, the only additional year available was in 2020. Because this contained a crisis year (COVID-19), the use of this additional year of data would bias overarching messages that would overly focus on non-standard periods of time.
← 6. See Office for National Statistics North Ireland/DETI/BIS (2021[43]).
← 7. Office for National Statistics (2021), Business Structure Database, 1997-2020: Secure Access (data collection), 12th Edition, UK Data Service, http://doi.org/10.5255/UKDA-SN-6697-12.
← 8. In fact, only in the last 2021 update to OECD territorial classifications, released recently, did Scotland have any TL3 region that was classified as a non-metropolitan region with access to small-sized cities.
← 9. Rural here is defined as belonging to one of the accessible or remote rural categories in the six-tiered classification system described in Table 2.1. Firms do not include public enterprises.
← 10. In comparison, in large urban areas, over the period of 2015-18, there was a 5.5% increase in the number of firms in large urban areas and a 4.4% increase in other types of rural areas.
← 11. There were 48 300 firms in rural and remote areas and 105 700 firms in large and other urban areas in 2015.
← 12. Accessible and remote small towns were the worse off in the years between 2015 and 2018, where growth in the number of firms was lowest or negative (Figure 2.8, Panel B).
← 13. There were 27 500 workers in rural and remote areas and 1.5 million workers in urban areas in 2015.
← 14. This refers to firms operating in the following categories of sectoral activities: Wholesale, retail and repair (G); Transportation and storage (H); Information and communication (J); Accommodation and food service activities (I); Financial and insurance activities (K); Real estate activities (L); Professional, scientific and technical activities (M); Administrative and support service activities (N); Arts, entertainment and recreation (R); and Other service activities (S).
← 15. This includes non-employee firms. If we exclude non-employee firms, the total share goes down to 76% but the relative trend between places remains the same.
← 16. In comparison, Canada, a country in which foreign ownership status is determined as a majority foreign-owned firm, the rate of foreign firm ownership is even lower, at less than 1%. In rural Canada, a very small share of firms is owned by foreigners and the share is larger in urban areas than in rural areas. The share of foreign ownership in urban areas is 0.48%, while it almost a fifth of the size, 0.11% in rural areas. While in part, this may be due to the cluster of firms near the border with the United States where most urban areas are located, it does suggest that international networks may be more difficult for equal access to international markets for rural firms (OECD, forthcoming[46]).
← 17. A recent review of survey data collection methodologies in the United Kingdom suggests that standard business and enterprise research and development (BERD) figures in Scotland and the United Kingdom under-report R&D carried out by small businesses, whereas data from the HM Revenue & Customs on R&D tax credits suggest that small businesses have accounted for a growing amount of R&D activity.
← 18. The real living wage is independently calculated based on what employees and their families need to live and therefore varies from the minimum wage. Providing the real living wage is non-mandatory. It is calculated once a year.
← 19. The labour force participation rate refers to those employed and those unemployed but looking for work.
← 20. The impact of COVID-19 was different for women across regions. In 2020, while progress was hindered for women in large metropolitan regions, more women per men were employed in non-metropolitan regions close to small cities. This may be related to the territorial dimension of access to services for women and in particular the loss of jobs among the male population.
← 21. This includes management and marketing practices.
← 22. As a rule of thumb, self-reported innovation overcomes some of the challenges with proxies for innovation such as patents or R&D but also does not harmonise what substantial increase to the previous product or process across firms. This decision was deliberately made to avoid meticulous determination of what may be considered as an improvement on products or processes within the firm.
← 23. Likewise, using the classification of the OECD metropolitan areas based on access to cities, non‑metropolitan regions are less innovative than metropolitan regions but the difference between them is spurious.