In 2020, researchers and practitioners collaborated to better understand how inclusive growth can be conceptualised and measured across a large, diverse and predominantly rural region in the north and west of Scotland.
The project, in collaboration with Highlands and Islands Enterprise (HIE), led to a focused statistical and spatial analysis which identified the underlying dimensions ‘behind’ inclusive growth, and then classified small areas in the Highlands and Islands into clusters, representing differences in inclusive growth performance and protected characteristics. With further investigation, this analysis can support a significantly improved evidence base on inclusive growth and rural diversity in Scotland.
Stage
Work CompletedDirectory of Expertise
Purpose
There is a growing need for detailed information about Scotland’s communities, as well as increasing concern about high levels of regional inequality in the UK. The UK2070 Commission have reflected that “the UK is one of the most spatially unequal economies in the developed world”. In addition, the Scottish Government’s National Performance Framework defines “sustainable and inclusive economic growth” as a key aspiration for the country and inclusive growth is emphasized as a goal in key development policies, such as Regional Growth Deals.
However, inclusive growth (economic development which drives lower inequalities) has also been described as “conceptually fuzzy and operationally problematic”, and a 2019 review for the Poverty and Inequality Commission (‘Delivering Inclusive Growth in Scotland’) found confusion over the meaning of this term, and uncertainty in how it can be measured, among organisations and practitioners in Scotland. In addition, there is an awareness of the limitations of some of the indicators and classifications which are currently used to understand Scotland’s communities. For example, practitioners and researchers at Highlands and Islands Enterprise (HIE) have a growing interest in inclusive growth and in developing a more nuanced understanding of their region, as a means of informing more customized and targeted investments and support.
We felt we could help because social scientists and geographers within SEFARI have a long-standing interest in place-based policies, measuring rural development and outcomes, and spatial inequality, which informed themes of research into demographic change and place-based policy, within the 2016-22 Strategic Research Programme. We also have a good understanding of life experiences on islands (e.g., 'Research on the Edge' and National Islands Plan Survey) and value chains that contribute to resilience and sustainability of mountain areas.
Therefore, to support this clear unmet need on the evidence base for inclusive growth, SEFARI and HIE worked together, to create a typology of area profiles for the north and west of Scotland, reflecting characteristics of inclusive growth. Collectively we were aiming to produce these resources to address demands for a more detailed understanding of rural development in the Highlands and Islands.
Results
Collaboration between SEFARI and Highlands and Islands Enterprise (HIE) was conducted in 2020 as part of ‘Towards Inclusive Growth’, a SEFARI Gateway Responsive Opportunity funded project, and project outputs also contributed to Scottish Government funded strategic research on place-based policy.
During the project, an in-person engagement workshop, in Aberdeen in early March 2020, was able to take place before Covid-19 restrictions necessitated a move to working online. The workshop brought the collaborators from the James Hutton Institute, BioSS and HIE together for facilitated discussions on understandings of inclusive growth, its measurement, and the Highlands and Islands context, which led to the planning and prioritisation of tasks.
Image: View of Inverness
The first key achievement of the project was the co-development of a framework of inclusive growth, representing themes which are relevant to the Highlands and Islands: this incorporates a framework published by the Joseph Rowntree Foundation (in 2016) but also extends this by adding additional contextual themes of ‘Physical geography and connectivity’ and ‘Population and social characteristics’, which capture community resources and affect the vulnerability and resilience of different places.
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Themes |
Dimensions |
Potential indicators* |
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Primary themes |
Inclusion |
Income |
Benefits; In-work tax credits; Low earnings |
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Living costs |
Housing affordability; Housing costs; Fuel poverty |
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Labour market inclusion |
Unemployment; Economic inactivity; Workless households |
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Prosperity |
Output growth |
Output; Diversity of business interests; Private sector businesses; Wages / earnings |
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Employment |
Workplace jobs; Private / public sector employment balance; People in employment; Employment in low pay sectors |
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Human capital |
Educational attainment; Intermediate / higher-level skills; Type of workforce, occupations |
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Contextual themes |
Physical geography and connectivity |
Physical geography |
Urban-rural classification; Mainland or island; Population density or sparsity; Natural hazards |
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Access to services |
Transport infrastructure; Access to key services; Digital connectivity |
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Environmental assets |
Area of carbon ‘sinks’; Renewable energy potential / existing schemes; Area protected / designated in some way |
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Population and social characteristics |
Social strength |
Community strength and cohesion; Commuting; Second or empty homes |
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Social infrastructure |
Existence of community centres, libraries and similar facilities, community owned land |
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Social vulnerability |
Age structure; Rates of disability, poor health (physical and mental); Ethnicity; Gender; Public transport infrastructure |
*Some names of potential indicators have been shortened.
The framework was then used to support an iterative and collaborative indicator selection process, leading to the calculation and compilation of a database of indicators, for 630 small areas (Data Zones) within the Highlands and Islands region. Our analysis was informed by further discussions, and factor analysis (exploratory multivariate analysis) was used to identify seven concepts (or ‘dimensions’) which lie behind inclusion and prosperity: these concepts were interpreted and labelled based upon the contributing indicators:
- ‘Lower income’: evidence of low income and unemployment, and correlated poor life outcomes
- ‘Big output’: economic strength and large employers
- ‘Rural services’: “typical rural services”: high drive times to key services, poor broadband, relatively high numbers of vacant/second homes
- ‘Quality of life’: not straightforward to interpret: includes positive loading for area within National Scenic Area and seems to reflect quality of life/wellbeing
- ‘Private sector’: positive loadings for variables reflecting employment and workplaces within the private sector
- ‘Community support’: positive loadings for variables reflecting accessible childcare places and local charities: high availability of supportive services
- ‘Small diverse businesses’: economic output per 1,000 employees (negative loading) and economic diversity (positive loading) suggest small business activities and ‘vibrancy’.
Cluster analyses, involving scores for these concepts and additional demographic indicators, were then explored to identify groups of small areas with similar characteristics. A nine-cluster model (other numbers of clusters have been explored) shows spatial variation in multidimensional development related to inclusive growth performance. Interpretation using mean scores suggests that the clusters represent different patterns of strengths and weaknesses across the multiple dimensions of inclusive growth. Based on the average scores, we can identify very different combinations of strengths and assets in these nine regions. A simplified illustration of these is below, indicating the clusters which have the three highest averages (dark-light blue) and the three lowest averages (dark-light red) for each of the standardised concept scores and demographic indicators.
Note: that the ‘Lower income’ concept is given a different name (‘Struggling’) within the report.
Our report presents more detailed descriptions of these clusters, but it is notable that there are differences in recent demographic change (in terms of total population change) between the clusters, and mapping (below) indicates that some clusters are clearly concentrated in certain regions or types of settlement:
- Cluster 1 is found across remote rural areas across the west of Scotland and parts of the Western Isles.
- The vast majority of cluster 2 is within remote rural areas, including much of the western Highlands and Islands, as well as parts of Strathspey, the Cairngorms, the far north and the Northern Isles.
- Most of cluster 3 is found at remoter small towns and urban areas: examples include Stornoway and Dunoon.
- Cluster 4 is concentrated in urban areas and towns, including Data Zones in Inverness, Elgin, Fort William and Oban.
- Almost all of cluster 5 is in remote areas (both towns and rural areas): the cluster forms an arc around Inverness and Elgin, and also includes other isolated settlements (e.g., Thurso, Wick and nearby rural areas in the far north, and the majority of Campbeltown)
- Cluster 6 is made up of very remote rural areas and towns, many of which are in the Orkney and Shetland mainland islands.
- Urban areas and accessible areas form a large majority of Cluster 7, which is focused in areas on or near the Moray Firth coastline (including parts of Inverness, Nairn, Forres and Elgin)
- Cluster 8 is also found in the Moray Firth region and appears as accessible 'commuter areas' to larger settlements, as well as parts of these settlements.
- Cluster 9 is located in the isolated rural outer islands of Orkney and Shetland.
This analysis, based on a regionally-defined framework of inclusive growth, has contributed to a more nuanced and multidimensional understanding of rural development across the Highlands and Islands. This analysis has helped to inform the locations of locally-led and developed population pilot areas by a working group of the Convention of the Highlands and Islands.
The ‘Towards Inclusive Growth’ project was funded by the SEFARI Gateway Responsive Opportunity Initiative and the Rural and Environment Science and Analytical Services (RESAS) Division as part of the Scottish Government’s Strategic Research Portfolio. Views expressed are those of the authors and are not necessarily those of the Scottish Government or RESAS.
Updated analysis and research papers
The analysis described above was produced in 2020. A re-run of the analysis in 2022, which incorporated reproduced and updated spatial data inputs, has generated differences in some indicator values and Data Zone classifications compared with the results described in this case study. The 2022 results will be documented in a manuscript (in preparation). Some of Jonathan Hopkins’ publications and outputs are available on his ResearchGate page.
Benefits
The multi-dimensional and data-rich approach described in this case study offers, with development, the potential to significantly increase the understanding of inclusive growth at the sub-national and sub-regional levels.
The cluster analysis approach can contribute to a more nuanced understanding of communities across the Highlands and Islands through evidence of spatial patterns of multidimensional development. Further investigation of differences between clusters, and variation within clusters, is important and should develop the understanding further.
More immediately and directly, the project has led to new and valuable research collaborations between SEFARI and HIE. The project also provided an excellent learning experience in how to deliver this kind of collaboration and research remotely during COVID-19.
A paper is being written, which will include results from a re-run of the analysis produced in 2022 (noted below), and in the longer term, this multi-dimensional approach to understanding inclusive growth can potentially be extended, to support improved targeting and design of development policies.
Project Partners
Highlands and Islands Enterprise
Biomathematics & Statistics Scotland