COVID-19 impacts by types of regions

January 2022

The COVID-19 pandemic affects regional development in many ways and the impacts on local and regional development differ across places. This has already been discussed in a previous blog post

A recent study to the European Parliament raises the issue of impacts vary according to regions’ particular geographical characteristics and the regional classifications used in Cohesion Policy. Looking a little deeper into regional sensitivities to COVID-19 related restrictions, such as lockdowns or travel bans, offers some starting points for discussion.

Based on previous research, regional characteristics which affect the sensitivity to COVID-19 related restrictions, include the share of employment in risk sectors (e.g. accommodation, food service, arts, entertainment), the reliance on the tourism sector, the share of people with low education levels, the share of young people without occupation, the share of people at risk of poverty, the share of micro-enterprises and self-employed people, and lower quality of governance. A detailed rationale of this choice of sensitivities factors can be found in an earlier study to the European Committee of the Regions.

Working with very rough regional categories at NUTS 2 level, it appears that some sensitivities are more pronounced in some types of regions than in others. Certainly, this can only serve as a teaser for further analyses and debate. Given that NUTS 2 regions cover a wide range of geographical characteristics, and that impacts of the pandemic vary even between neighbourhoods (and not just regions), more nuanced reflections are needed.

Nevertheless, the results are worthwhile some discussion. The below graphic provides an aggregated summary of the data collected for the European Parliament study. The dark red points indicate a comparably high sensitivity, light red is a rather medium sensitivity and grey is a comparably low sensitivity.

Geographical characteristics

Urban-rural differences seem to showcase that urban areas display much more mixed sensitivities, while rural areas are in the medium range for most sensitivity indicators. However, below these figures hide considerable variations. The degree to which metropolitan areas are impacted by COVID-19 effects varies widely. Strongly impacted areas seem to bounce back quickly due to their economic structures, so harsher impacts on urban areas are followed by a quicker recovery compared to many non-metropolitan areas.

Very Sparsely populated areas with less than 12.5 inhabitants per km2 appear to have rather low sensitivity to most of the factors affected by the pandemic restrictions. Sparsely populated areas having between 12.5 and 50 inhabitants per km2 on the other hand show comparably high sensitivities with regards to several factors incl. reliance on tourism, young people without occupation, share of people at risk of poverty and share of microenterprises.

Islands and coastal regions appear to be more sensitive to many of the factors affected by COVID-19 restrictions than other types of regions. This is largely related to structural characteristics, such as a high reliance on tourism for many islands and coastal areas, which often goes hand in hand with high shares of people working in micro-enterprises and seasonal employment. In particular, the reliance on tourism seems to be crucial for understanding the pandemics impacts on islands and coastal regions, as coastal and maritime tourism account for 42% of nights-spent in the EU.

Outermost regions are an even more specific case. Their high sensitivity is partly due to the high share of people working in micro-enterprises, high shares of young people without occupation and comparably low quality of government. In addition, geographical distance, interrupted flight connections and supply chain disruptions are important factors. This concerned trade, but also caused significant problems for essential equipment, such as protective medical gear.

Mountain regions are very diverse, and so are the pandemic’s impacts on their development. The high levels of sensitivity of mountain regions embrace a wide diversity with some of these regions heavily affected by the pandemic and others only mildly affected. Some examples concern the high reliance on tourism in mountain regions which often comes with strong seasonality, but also the importance of agri-food production has been affected by the pandemic.

Border regions were in many regards at the forefront of areas affected by the political responses to the pandemic. Cross-border integration and cross-border functional areas were put into question during the first wave of infections in spring 2020, when some national borders were suddenly closed. This posed, among others, considerable difficulties for employees and employers relying on cross-border commuting. The effects of the pandemic in border regions did not vanish once the borders reopened and many border crossings do still require COVID-19 related paperwork.

Cohesion Policy regions

The same analysis of regional sensitivities can also be applied to the categorisation of regions into more developed, transition and less developed regions used in EU Cohesion Policy. It shows that both for the 2014-2020 and 2021-2027 period the regions considered less developed are highly sensitivity to a larger number of factors affected by the pandemic than transition or more developed regions.

While for the 2021-2027 period more developed regions have higher shares of people working in risk sectors, transition regions have higher sensitivities due to young people without occupation and less developed regions show comparably higher sensitivities to a wider range of factors.

Conclusions

Overall, it seems the regional categorisation of Cohesion Policy should be well suited to address the impacts of the COVID-19 pandemic. When it comes to geographical types of regions, coastal areas, islands and mountain areas seem to be more sensitive to the impacts of the pandemic than other types of regions. However, as afore mentioned, the analysis of broad NUTS 2 typologies can only serve as a teaser. More nuanced analysis is needed.

More details on this are available on the European Parliament study on impacts of the COVID-19 pandemic on EU cohesion and EU cohesion policy.

by Kai Böhme, Sebastian Hans & Flavio Besana

https://steadyhq.com/en/spatialforesight/posts/63d0e9e3-201c-4357-9695-eaf9921d54b7

https://steadyhq.com/en/spatialforesight/posts/3ffed741-e203-4dc3-b135-72d156ec3246

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