Modelling broadband access impact on the economic growth at NUTS 3 level
This output is a quantitative model for assessing the impact of broadband access to regional economic growth. It is based on a Rural Digitisation Index, mapping the evolution of broadband coverage and running regression models for different connectivity rates.
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Output Description
DESIRA carried out a quantitative analysis of the impact of broadband infrastructure on economic growth, at regional level, in order to consider the dynamics between urban and rural areas and eventual gaps between them.
At the conceptual level, a first distinction was made between digitisation and digitalisation.
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Process by which analogic information is codified into numbers. Digitalisation is a reorganisation of human activities in relation to digitisation.
The first step was to construct a Rural Digitisation Index (RDI) reflecting the digital performance of European rural areas. The aim was to use the Rural Digitisation Index to map digitalisation at the lowest territorial level covered by Eurostat (i.e. the NUTS 3 level) when classifying regions by urban-rural typology. Due to data limitations at NUTS 3 level, the RDI includes only fixed broadband coverage related indicators.
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The starting point for the construction of a Rural Digitisation Index was the disaggregation of the existing Digital Economy and Society Index (DESI) which is a composite index used by Member States and constructed at the national (NUTS 0) level.
The DESI assists Member States in designing priority reforms specifically targeted at five key dimensions in the digital economy for which progress is relatively slow (connectivity, human capital, use of internet, integration of digital technology and digital public services) and comprises 37 different indicators.
DESIRA explored the available data for all the indicators to conclude that out of all DESI indicators, only data on fixed broadband coverage can be retrieved at NUTS 3 level. Consequently, only the connectivity dimension of the DESI immediately lends itself for regional assessment.
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Fixed broadband coverage is defined as the share of households per region with access to fixed broadband networks capable of realistically achieving download speeds of at least 2 Mbps, 30 Mbps, and 100 Mbps.
The main assumption for using only the broadband coverage out of all the Digital Economy and Society Index (DESI) indicators in the RDI is because broadband coverage is a necessary condition for the development of the other dimensions targeted by the DESI. Therefore it can be partially regarded as a one-directional proxy for these policy areas. Furthermore, at NUTS 3 level, data exists only for fixed broadband coverage.
The next step was to map the evolution of broadband coverage (> 30 Mbps) in all EU Member States per NUTS 3 region between 2011 and 2018. This examination of regional broadband access between 2011 and 2018 is then analysed quantitatively in relation to its contribution to economic growth.
A quantitative model, the system generalised method of moments estimator, was used.
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In the system generalised method of moments estimator, the rate of growth of real GDP per capita is affected by its preceding growth, the provision of high-speed broadband access and a number of control variables, including population growth, trade openness, government consumption expenditure and gross domestic investments. Moreover, a variable measuring lagged GDP per capita was included to test for convergence.
Regression models were run for connectivity rates of at least 30 Mbit/s and then for connectivity rates of at least 100 Mbit/s. The regression results showed that after a certain threshold speed level is reached, further increasing broadband speed does not translate into additional economic growth.
Moreover, the regression results indicated a decreased upper bound of speed-related gains for the provision of broadband access in rural Europe compared to urban areas and in the agricultural industry compared to other sectors.
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First, three regression models were run concerning connectivity rates of at least 30 Mbit/s:
- Model 1, yielded the regression results for the general economy, all sectors and regions combined.
- Model 2, showed the results for the agricultural sector, while still combining all regions.
- Model 3, trimmed down the data to the agricultural sector and excluded all predominantly urban regions.
The results show that the provision of high-speed broadband access has a significant and positive impact on real output per capita. The results indicate a relatively weaker effect in rural areas compared to their urban counterparts.
Second, the 30 Mbit/s broadband variable were replaced with the share of households that has access to network speeds of at least 100 Mbit/s. There, the significant impact on economic growth disappears for the agricultural sector but remains when we consider the different economies as a whole. Contrary to the conclusions drawn from the 30 Mbit/s regression, economic growth in intermediate and predominantly rural areas benefits more from the provision of broadband infrastructure in terms of connectivity rates offering 100 Mbit/s and up, as opposed to the more urbanised regions.
In terms of connectivity rates offering at least 100 Mbit/s, this threshold level has long been attained in urban Europe, while rural areas are still falling behind significantly in 100 Mbit/s broadband infrastructure compared to their urban counterparts. At the sectoral level, the agricultural industry witnessed large gains from digitalisation between 2011 and 2018, aligning with the emergence of innovations in smart farming technologies and reassuring its importance in the future.
Relevance for monitoring and evaluation of the CAP
The system generates metric models' regression, which is a dynamic linear panel model. That can account for the interplay between broadband coverage and stimulation of economic growth and account for measurement error. It further accounts for other problems that are usually well known in these growth regressions data if real GDP per capita and purchasing power parities are used. Some of the control variables include past economic growth, population growth and proxies for investments and trade orders. These data are proxied by using information on formal sector employments, usually.
Modelling impacts of digitalisation can be very useful for assessing the effects of interventions that aim to increase the digitalisation of rural areas, in particular, the effects on economic growth. The contextual background offered by DESIRA indicated the lack of data at the NUTS 3 level for measuring indicators related to human capital, use of internet, integration of digital technology or digital public services. However, it has shown that it is possible to analyse broadband access at the NUTS 3 level. This opens a new door to impact assessment at this territorial level, where many of these interventions are implemented.
Furthermore, the fixed broadband coverage at different speeds measured at the NUTS 3 level is important for monitoring and evaluation because of the Farm to Fork objective stating that ‘The Commission aims to accelerate the roll-out of fast broadband internet in rural areas to achieve the objective of 100% access by 2025’. The RDI (which includes DESI indicators on fixed broadband coverage) may be a good monitoring and reporting indicator of progress.
Knowledge of econometrics to understand and use the 'system generalised method of moments estimator' is required to model broadband access.
Relevance of the output per CAP Objectives
- Specific Objective 8 - Vibrant rural areas
- Cross-cutting Objective - Fostering knowledge and innovation
Additional output information
Associated evaluation approaches:
- Desk research
- Scenario analysis
- Impact evaluation ex post
- Impact evaluation ongoing
Spatial scale:
- Regional
Data collection systems used:
- Eurostat
- Ad-hoc data collection
Type of output:
- New indicators
- Methodology
- Forecasting model / tool
Project information
Digitalisation: Economic and Social Impact in Rural Areas
DESIRA aims to improve the capacity of society and political bodies to respond to the challenges that digitalisation generates in agriculture, forestry and rural areas.
Specific objectives:
- Fill the socio-economic knowledge gaps on digitalisation in agriculture, forestry and rural areas.
- Assess the past and current socio-economic impact of digitalisation in relation to Sustainable Development Goals.
- Improve the capacity of communities to reflect on future risks and opportunities of digitalisation.
- Improve the capacity of rural communities to reap the opportunities offered by digitisation and to improve resilience related to associated risks.
- Promote online and offline interaction and learning among a wide range of stakeholders.
- Increase the uptake of societal concerns in ICT-related policy and innovation, and to align digitalisation scenarios with societal needs and expectations.
Project’s timeframe: 01/06/2019 – 31/5/2023
Contact of project holder: Gianluca Brunori, University of Pisa (gianluca.brunori@unipi.it)
Website: DESIRA: https://desira2020.eu/Open link in new windowOpen link in new window
CORDIS database: https://cordis.europa.eu/project/id/818194Open link in new window
Territorial coverage:
Austria, Belgium, Croatia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Poland, Spain, The Netherlands