Huanjia Ma, Raquel Ortega-Argilés (p), Matthew Lyons

Nikolaos Terzidis

In 2022, the UK Government launched its latest iteration of the national industrial strategy with the Levelling Up White Paper. To rebalance the UK national economy, the white paper sets twelve main “missions” centred around science, technology and education. One of the core twelve “missions” is focused on increasing the domestic public R&D outside the South East of England by at least 40% by 2030.

The Levelling Up White Paper sets clear plans for how R&D investment will be spent and locally redistributed. Based on these documents and combining information from data from different sources (UKRI and ONS), we calculate the current UK R&D sub-national and sectoral distribution (GERD and BERD) and set up different redistribution scenarios reflecting three different sets of assumptions about the distribution of R&D spending.

Following similar attempts to evaluate the impact of R&D using input-output techniques, we use the multi-regional Socio-Economic Impact Model for the UK (SEIM-UK) to evaluate our three proposed R&D spending scenarios. Our analysis allows us to assess the extent to which such proposed changes will impact the UK regions in terms of output, GVA and employment.

Our findings vary significantly across the different UK regions in different scenarios. A more redistributive approach, allocating more additional GERD to regions with previously low funding levels, yields the largest effects. On average, output, employment and GVA in regions outside LSE increase by 0.33%, 0.37% and 0.34%, respectively, showing a potentially positive effect on the levelling up of R&D in the country.

Nikolaos Terzidis (p), Alexandra Tsvetkova

Raquel Ortega Argiles

The current paper exploits the business dynamism theoretical concept to shed further light into the declining productivity trends in the OECD countries. Notably, the comprehensive analysis investigates region- and industry-specific effects. Drawing on an extensive dataset, covering 581 European NUTS-3 regions between 2008 and 2018, the dynamic GMM analysis fails to identify consistent economy-wide productivity effects from business dynamism. Nevertheless, the industry-level approach uncovers positive impact in some economic sectors (trade and public administration), which extend over multiple years. In line with the theoretical expectations, we reveal divergent trends once we distinguish between firm birth and death rates. Finally, the analysis highlights far-reaching regional heterogeneity by illustrating that the effects materialize mostly in rural regions. From a policy perspective, the reported results indicate the necessity for place-sensitive policies to relax labor market rigidities and thus stimulate market entry, as well as policies allowing the spread of productivity gains to incumbent firms.