Drivers of rural business growth, decline and stability

CONFIDENTIAL

 

This work contains statistical data from ONS which is Crown Copyright. The use of the ONS statistical data in this work does not imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical data. This work uses research datasets which may not exactly reproduce National Statistics aggregates

Rural and urban definitions used in the analysis

Rural-urban classification Sparsity classification

Classification at OA level

Rural and Urban are not very different…

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…but Rural performed better

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Which sectors drove the difference?

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Tourism

Health/ social work /education / publicFinance

Services

Wholesale/ retail / logistics

Manufacturing

Mining/ quarrying/construction / utilityAgriculture/ fishing

Overall net change

Top 10 growth sectors Top 10 decline sectorsSocial work without accommodation Employment activities

Residential care activities Construction of buildings

Education Civil engineering

Retail Manufacture non-metal mineral

Human health activities Manufacture fabricated metal

Agriculture Manufacture motor vehicle

Service to buildings Office admin, business support

Computer prog, consultancy Manufacture plastic / rubber

Sports & recreation Repair installation machinery

Telecommunications Manufacture machinery nec

Which sectors have changed the most in rural areas?

These are a mix of cyclical sectors (e.g. construction / business support) and

manufacturing

Main growth is in social work and residential – both key sources of

employment growth. Other growth sectors are more of a mixed group

Rural performed better in each region…

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Rural Urban

Why do rural businesses do better in some places than others?

Supply side Demand side

● Input costs (diverse and vary by industry)

● Labour: price + quality

● Transport / transactions costs

● Local demand drivers (population, income)

● Search goods (customers’ knowledge of product)

● Wider e.g. global demand – exchange rates etc.

But for reliable analysis you need data at a fine spatial scale

Postcode / OA level data

c. 170k OAs

LAD level data

Only 326 LADs

● Broadband

● Population, households and income

● Transport infrastructure

● House prices

● Demographics – pensioners and graduates

● Number of public sector employees

● Measures of sectoral agglomeration

● Business rates

Quantitative analysis found some drivers related to rural business performance…

Broadband / mobile infrastructure

● Rural areas with good broadband have fared a lot better

● Strongly correlated with business births and employment growth

● Also linked to churn…

Local demand

● Population, households and income are all correlated with business performance

● Effect seen in relation to both changes and levels; the latter effect could suggest some form of agglomeration effects occurring (relatively more growth in more populated areas)

Transport infrastructure

● Better connected areas have higher rates of both start-ups and failure (i.e. higher churn)

● More flexibility to re-deploy inputs in other uses, so this should enhance productivity

Qualitative analysis confirmed many of these findings and identified other areas of concern

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● Access and speed

□ Slow broadband constitutes a major time cost, both waiting for up/downloads and/or traveling to use the internet

□ High cost of installing lines in rural areas

□ Barrier on tourism as free Wifi expected

● Roads

□ Poor public transport options perceived as a major barrier to employing low level staff as they cannot afford to run a car

□ Closures can be costly in terms of customer access and time cost for employees

● Rail

□ Seen as a driver in North-East/North-West and a major barrier in South-West

● Participants felt investment capital was unavailable

□ Banks requiring too much security on loans, loss of the ‘local’ bank manager

□ Most had written off commercial finance and were extremely adverse to debt. They were therefore expanding from profits alone

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● Lack of awareness

□ Grant application process too complex with multiple organisations. Participants were put off by this

□ No real marketing of peer-to-peer lending schemes

● “Can’t do”, “Detached from reality”

□ Participants felt that planning authorities were not on their side and as a result there was too much of a time burden on senior staff

□ Planning authorities unrealistic about stopping development on green land

Employees need cheep housing

● Payroll and Auto-Enrolment

□ Frustration at the time cost on senior management at having employees on payroll and auto-enrolment

● Access to Labour

□ There was a wide perception that employers weren’t getting value for money and employment law was making it hard to remove poor performers

Summary

● Rural and urban overlap considerably in terms of sector. Around 80% of rural employment is in sectors that are equally important in the urban economy.

● Rural has performed better than urban (at least as far as employment), in most sectors and regions.

● Rural growth has been stronger in areas that are in close proximity to urban areas, suggesting there may be agglomeration benefits in linking resource-rich rural areas with centres of economic activity.

● Much of the change in rural economic activity can be characterised by sector-specific structural factors or cyclical factors.

● There is a strong relationships between rural performance and broadband provision.

● The planning system is claimed to be an over-zealous constraint on economic development and on housing.

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