The Role of Digitalisation in Reducing Risks and Bridging Regional Economic Welfare Gaps within a Sustainable Development Framework: The Case of Romania
Managing Risk and Decision Making in Times of Economic Distress, Part B
ISBN: 978-1-80262-972-9, eISBN: 978-1-80262-971-2
ISSN: 1569-3759
Publication date: 28 March 2022
Abstract
Introduction: Regional economies are significantly shaped by the new developments in technology, digital transformations, as well as by the demographic processes (the ageing population and international migration), all of these being amplified by the Covid-19 pandemics and requiring tailored strategies to bridge regional welfare gaps and enhance sustainable economic development.
Aim: This research provides a review of the interplay between the regional economic welfare and digitalisation, with a keen focus on digital transformations, education, digital skills and risk management strategies in filling development gaps and enhancing regional economic growth in a sustainable development framework, with a keen focus on Romania. In this approach, the study undertakes several essential research questions and designs an advanced theoretical and empirical research to inforce the knowledge in this scientific field.
Method: The methodological framework consists of robust regression models and spatial analysis with two types of spatial models, namely spatial lag-autoregressive and spatial error. National data compiled for Romania during the 2010–2019 lapse of time were exploited.
Findings: Main results encompass that digitalisation coordinates, education and digital skills are essential for enhancing the economic development and labour market performance of various regions in Romania, with beneficial spill-overs on sustainable economic welfare and poverty reduction. These advances bring to the fore important shifts in both demand and supply sides across regional economies that affect the equilibrium and overall performance, while public discourse, regulatory authorities, policy-makers and business representatives render global the keen need to strengthen the understandings in this scientific field.
Keywords
Citation
Noja, G.G., Cristea, M., Sîrghi, N. and Vădăsan, I. (2022), "The Role of Digitalisation in Reducing Risks and Bridging Regional Economic Welfare Gaps within a Sustainable Development Framework: The Case of Romania", Grima, S., Özen, E. and Romānova, I. (Ed.) Managing Risk and Decision Making in Times of Economic Distress, Part B (Contemporary Studies in Economic and Financial Analysis, Vol. 108B), Emerald Publishing Limited, Leeds, pp. 131-142. https://doi.org/10.1108/S1569-37592022000108B037
Publisher
:Emerald Publishing Limited
Copyright © 2022 Emerald Publishing Limited
1. General Considerations: Current Global and European Context and the Potential Impact of Digitalisation
Digital transformations and technological progresses are notably shaping the skills needed by individuals to actively engage in the world of online work, in a modern economy and, especially, post-pandemic crisis (de Lucas Ancillo, del Val Núñez, & Gavrila, 2021; Sousa & Rocha, 2019). Global job losses due to digitalisation are estimated to reach 2 billion by 2030 (World Economic Forum, 2018), while the current Covid-19 pandemic has outburst on the global economy making digitalisation even more relevant and a key milestone to overcome these challenges and to enhance the sustainable economic development.
As Coibion, Gorodnichenko, and Weber (2020) underline, the preliminary indicators to assess the impact of Covid-19 on the global economy show dramatic declines in employment (20 million decrease in the number of workers), and a wave of early retirements with obvious negative effects on the economy. Another particularly worrying aspect that the authors highlight is the fact that most of those who lost their jobs due to the Covid-19 outbreak are not looking for a new job. Also in Romania, because of inherent government public health strategies and social distancing measures to mitigate the spread of Covid-19, many businesses have dwindled the number of workers or even closed down all the activities, while other have reoriented their activities online, making digitalisation even more relevant and decisively important for any economy (Radulescu et al., 2021; Zamfir & Aldea, 2020). Mas and Pallais (2020, p. 7) emphasised that ‘median worker reports that only 6 percent of their job could be feasibly done from home’, compared with white collar workers from the information technology (IT) sector or business and financial sector, who can easily work from home. Mongey and Weinberg (2020) prove that individuals who cannot work from home are more likely to be medium or low educated, non-white, lower-income and without employer-provided health insurance. The number of jobs that can be made from home, using digital instruments, will be an important indicator for the economy’s performance (Dingel & Neiman, 2020). Countries, which will be able to enhance and efficiently use the digital skills of the labour force, will win the economic battle in these times of social distancing.
These challenges are amplified for Romania in the digitalisation framework, due to some of the lowest digitalisation performances accounted by the country over the years. Within the European Union (EU), the European Commission’s Digital Economy and Society Index (DESI) for 2020 (European Commission, DESI 2020) shows that even though several EU countries have registered a notable progress (e.g. Ireland, the Netherlands, Malta and Spain), the countries, which ranked a degree of digitisation lower than the EU average, have registered this situation over the last five years. Hence, the EU Member States (MS) still face deep digital development gap, Romania being placed at the bottom of this ranking, along with Greece and Bulgaria. Technology is significantly changing jobs and occupations, and the effect of digitalisation on the labour markets grasp numerous advantages, but also pitfalls.
Based on these facts and amplified challenges, this research is driven by the needs of addressing the EU countries’ responses to digitalisation, with a particular focus on Romania, to develop new, innovative and more effective approaches to equipping the labour force with the digital skills required for employability/job security in the digital economy in order to decrease socioeconomic welfare gaps and enhance sustainable development.
Moreover, in a globalised Digital Era, on the one hand, young people (‘millennials’) tend to demand a more dynamic and engaged form of education and use of digital technologies, required to advance their careers (Musinszki, Vallasek, Mélypataki, Csolák, & Lipták, 2020), and thus this study comprehensively frame these needs by providing new innovative insights on the role of digitalisation for sustainable development and reduced welfare gaps in a digital era. On the other hand, adults (elderly population) are facing a massive skills mismatch and digital gaps linked to professional profiles that pose major challenges to their labour market success (Cristea, Noja, Stefea, & Sala, 2020), with spill-over effects on regional economic development, particularly during these challenging pandemic and post-pandemic times.
The objective of this research is to assess the interplay between the national regional economic welfare and digitalisation in Romania, focussed on digital transformations, education, digital skills and risk management. The methodological framework consists of robust regression models (RREG) and spatial analysis with two types of spatial models, namely spatial lag-autoregressive (SAR) and spatial error (SEM), based on national data compiled for the period 2010–2019.
After the overall introduction of current context and the potential impact of digitalisation, the structure of this chapter comprises an overview of Romania’s national and regional digitalisation background and associated performances, followed by an advanced empirical analysis on the interplay between digitalisation and regional economic development. Therefore, data and the research methodology applied are introduced further. Based on the results and discussions presented in the final sections of this chapter, concluding remarks and policy implications enclose the main findings and provide a comprehensive perspective on the entire research endeavour.
2. Digitalisation and Regional Welfare Effects in Romania in a Sustainable Framework
2.1. Overview of Romania’s National and Regional Digitalisation Background
Romania is being placed on the 26th position out of 27 EU MS within the DESI 2020 (European Commission, 2020). Romania’s performance was identical in four out of five dimensions measured by DESI, broadband connectivity being the only coordinate in which Romania has very good achievement. Romania’s digitalisation progress has fallen way behind since almost one-fifth of the Romanian people have never used the Internet, while a very small share (the lowest in the EU) have used the internet for interaction with public authorities (% of people aged 16–74), same low performances being accounted in terms of using the internet to order goods or services for private use (% of people aged 16–74). Moreover, the share of people who never used a computer (% of people aged 16–74 in 2017) is the highest in EU, with small differences across Romania’s regions, the West region accounting slightly improved numbers (European Commission, 2020).
On the other hand, however, Romania holds a good position with regard to Information and Communications Technology (ICT) graduates, being placed on the fifth place among the EU MS (5.6% compared to the EU average of 3.6% of total graduates), yet, if we consider the employed IT specialists, the results are modest, namely 2.2% compared to an EU average of 3.9% (European Commission, 2020). Higher education institutions are a landmark in providing digital skills, being essential in bridging the educational offer with the labour market needs, tailored to professional profiles (Abad-Segura, González-Zamar, Infante-Moro, & Ruipérez García, 2020). The employment rate of recent graduates as a percentage of population aged 20–34 is relatively high in Romania, even though there are notable differences across regions. The West region registered 72.1% in 2018, which is only slightly higher than 62.3% accounted by the Centre region with the lowest performance, and way behind 91.9% which is the best achievement registered regionally (European Commission, 2020).
At the same time, Romania registered notable achievements in terms on the educational background and labour market insertion of young people, still significantly behind the other EU MS, again with different performances from one region to another, as attested by the share of people neither in employment nor in education and training (European Commission, 2020). However, the level of digital skills in the country is very low, Romania holding the second to last position among the EU MS, with no progress compared to the previous year. Same low achievements are registered in terms of ‘at least basic’ digital skills in the software area (European Commission, 2020).
Less than one-third of the persons aged 16–74 has at least basic digital skills (compared to 58% overall the EU), while 35% have at least basic software skills (compared to an EU average of 68%). The situation is worst if we compare the ‘above basic’ digital skills, Romania registering only 10%, thus ranking last in the EU in 2020 and without any progress in the last two years (European Commission, 2020).
2.2. Empirical Analysis on the Interplay Between Digitalisation and Regional Economic Development
2.2.1. Data and Indicators Applied in the Econometric Analysis
Based on these facts, in order to assess the interlinkages between digitalisation and regional socioeconomic welfare in Romania, we have extracted a sample of nine specific indicators compiled during 2010–2019, for the eight development regions of Romania by the Nomenclature of Territorial Units for Statistics (NUTS) 2, as follows (European Commission, 2021):
‘Real growth rate of regional gross value added (GVA) at basic prices by NUTS 2 regions, percentage change on previous year’ (GVA_GR).
‘Gross domestic product (GDP) per capita (Euro/inhabitant)’ (GDP_C).
‘People at risk of poverty or social exclusion by NUTS regions’ (POV).
‘Households with access to the internet at home’ (HIA).
‘Individuals who used the internet, frequency of use and activities’ (IUI).
‘Individuals who ordered goods or services over the internet for private use’ (IOP).
‘Participation rate in education and training (last four weeks), by NUTS 2 regions’ (EDU_TR).
‘Persons with tertiary education (ISCED) and employed in science and technology, percentage of total population, by NUTS 2 regions’ (TE_EST).
Descriptive statistics of the indicators/variables applied in this empirical research are detailed in Table 1.
Descriptive Statistics of the Indicators Encompassed by the Empirical Analysis.
| Variables | N | Mean | Standard Deviation | Minimum | Maximum |
|---|---|---|---|---|---|
| GVA_GR | 80 | 2.175 | 5.307518 | −14.6 | 12.2 |
| EDU_TR | 79 | 1.348101 | 0.6069809 | 0.6 | 4.4 |
| HIA | 80 | 64.9 | 15.77099 | 35 | 96 |
| IUI | 80 | 52.125 | 14.09316 | 28 | 81 |
| IOP | 80 | 11.575 | 7.471083 | 1 | 36 |
| POV | 80 | 37.685 | 9.523111 | 14 | 54.1 |
| GDP_C | 80 | 20,139.22 | 9,979.809 | 9,896.26 | 55,850.6 |
| EDU_TR | 80 | 1.34 | 0.6074641 | 0.6 | 4.4 |
| TE_EST | 80 | 8.1675 | 3.810371 | 5.1 | 22.3 |
| N total | 80 |
Source: Own process in Stata.
Romania’s real growth rate of regional GVA in 2019 ranged between 3.8% and 4% for the eight development regions, being enhanced in the North-West, West, South and South-East (4%) (Fig. 1a). In terms of GDP_C, the differences among regions are notable, the values of this indicator ranging from 15,269.36 euro/inhabitant in the South-West region to 55,850.6 euro/inhabitant in the Bucharest-Ilfov region in 2019 (Fig. 1b). At the same time, the share of POV was significantly lower in 2019 in the Bucharest-Ilfov region (14%), and particularly high in the North-East region (47.1%) (Fig. 1c). These statistics outline important welfare gaps between Romania’s eight development regions that need to be further evidenced and addressed in order to ensure long-term economic development.
While considering the digitalisation credentials, we noticed that the Bucharest-Ilfov region has the highest share of households with internet access at home (91%), compared to the South-East region (79%) (Fig. 2a). With regard to the individuals accessing the internet with a weekly frequency (even daily) we notice that the North-East region account the lowest performances with only 18% of total individuals, while the best achievements on these lines are registered by the North-West and Bucharest-Ilfov regions with 29% and 31%, respectively (Fig. 2b). Moreover, the North-West (80%) and West (76%) regions lead the way in terms of the share of IOP in the last 12 months (Fig. 2c).
Nevertheless, education is essential particularly in the framework of this research through the importance of the human capital potential and the digital skills needed by the labour market in the digital economy to succesfully engage in the world of online work during pandemic and post-pandemic times (Abad-Segura et al., 2020). We have therefore considered the EDU_TR as a measure of lifelong learning to encompass the learning activities undertaken by individuals aged 25–64 years to improve skills (particularly digital skills due to notable technological transformations and during the current pandemic times) and capabilities and employment-related perspectives. These percentage are quite small for Romania, the South region registering 3%, while at the opposite end there is the North-West region with only 0.6% (Fig. 3a). Also, the share of ISCED and TE_EST is relatively high in the Bucharest-Ilfov region (22.3%) and very small in the other regions, particularly the South region (6.1%) and North-East region (6.2%) (Fig. 3b).
2.2.2. Research Methodology
The research methodology grasps RREG (with Huber and biweight iterations), applied for the entire panel comprising eight development regions of Romania according to NUTS 2, for the period 2010–2019, along with two types of spatial models that better capture the regional welfare synergies under the impact of digitalisation, namely SAR and SEM.
We built three RREG, comprising a series of specific independent variables for each considered dependent variable, namely: GVA_GR, GDP_C and POV.
The basic multiple RREG is described in Equation 1.
where, δ and β, parameters that need to be estimated; ε, stochastic element; and θi and λt, variables accounting for spatial and time effects.
Spatial analysis models are configured according to Marcu, Siminică, Noja, Cristea, and Dobrotă (2018), as follows from Equations (2a) and (2b).
SAR models:
SEM:
where, W is the inverse distance weights matrix (row-standardised); y is the dependent variable; X is the explanatory (independent) variables; λ and ρ are scalars, which estimate the dependence of yi on nearby y and the spatial correlation in the errors; u is the error term (spatially correlated residuals); and ν is an independent and identically distributed disturbances (Marcu et al., 2018, p. 8).
Spatial models are processed with Stata econometric package, based on the maximum likelihood estimator (MLE).
3. Results and Discussions
The first set of results, associated with the RREG, are detailed in Table 2, and encompasses the interplay between regional economic welfare and digitalisation, namely the role of digitalisation, education, particularly TE_EST in filling development gaps and enhancing regional economic growth in a sustainable development framework in Romania.
Results of Econometric Models, RREG, Romania, 2010–2019.
| Variables | (1) | (2) | (3) |
|---|---|---|---|
| GVA_GR | GDP_C | POV | |
| HIA | 0.475*** | 0.0667 | −0.197 |
| (0.134) | (0.0652) | (0.249) | |
| IUI | 0.0561 | 0.0139 | 0.149 |
| (0.175) | (0.00849) | (0.318) | |
| IOP | 0.491** | 0.0157* | −0.395 |
| (0.158) | (0.00766) | (0.280) | |
| TE_EST | 0.199 | 0.0536*** | −1.006*** |
| (0.175) | (0.00850) | (0.286) | |
| EDU_TR | 1.387 | 0.110** | 0.708 |
| (0.810) | (0.0393) | (1.440) | |
| _cons | −23.44*** | 8.793*** | 54.63*** |
| (3.005) | (0.146) | (5.698) | |
| N | 71 | 71 | 79 |
| R2 | 0.598 | 0.800 | 0.491 |
Source: Authors’ research.
Note: Standard errors in parentheses: *p < 0.05; **p < 0.01; ***p < 0.001.
As attested by the accurate and robust results (Table 2) obtained after processing the multiple regression models through the RREG, with Huber and biweight iterations, there is a strong interdependence between digitalisation (captured through HIA, IUI and IOP), EDU_TR, TE_ES,T regional economic welfare, captured through the level of GDP_C, GVA_GR and POV. Hence, the coefficient of determination entails that 80% of the variation in regional GDP_C, 59.8% in the variation of GVA_GR and 49.1% in the variation of POV is explained by the variation in the selected digitalisation and educational credentials. The slope coefficients associated with GVA_GR and GDP_C are positive, thus entailing that particularly the use of IOP and the HIA, along with an increased number of EDU_TR and TE_EST significantly contribute to improving regional economic welfare by increasing GDP_C, reducing the POV and increasing the regional GVA.
Results of the Spatial Analysis (SAR and SEM), Romania, Regional Level (Eight Regions), 2010–2019.
| Variables | (1) | (2) | (3) | (4) | (5) | (6) |
|---|---|---|---|---|---|---|
| GVA_GR | GVA_GR | GDP_C | GDP_C | POV | POV | |
| SAR | SEM | SAR | SEM | SAR | SEM | |
| Main | ||||||
| HIA | 0.469*** | 0.478*** | 0.00414 | 0.00498 | −0.145 | −0.150 |
| (0.107) | (0.106) | (0.00535) | (0.00637) | (0.235) | (0.242) | |
| IUI | 0.101 | 0.0715 | 0.00934 | 0.0116 | 0.110 | 0.129 |
| (0.128) | (0.128) | (0.00727) | (0.00809) | (0.293) | (0.292) | |
| IOP | 0.463*** | 0.478*** | 0.0104 | 0.00998 | −0.426 | −0.430 |
| (0.103) | (0.103) | (0.00543) | (0.00549) | (0.226) | (0.230) | |
| TE_EST | 0.202* | 0.217* | 0.0590*** | 0.0603*** | −1.039*** | −1.030*** |
| (0.103) | (0.108) | (0.00549) | (0.00533) | (0.191) | (0.190) | |
| EDU_TR | 1.494* | 1.457** | 0.100* | 0.0962* | 0.694 | 0.663 |
| (0.605) | (0.549) | (0.0436) | (0.0420) | (1.203) | (1.225) | |
| _cons | −21.72*** | −23.46*** | 7.932*** | 8.805*** | 55.43*** | 53.23*** |
| (2.860) | (2.930) | (1.103) | (0.137) | (7.955) | (6.075) | |
| Rho | ||||||
| _cons | 0.172 | 0.0954 | −0.0423 | |||
| (0.133) | (0.121) | (0.165) | ||||
| Sigma | ||||||
| _cons | 3.205*** | 3.160*** | 0.162*** | 0.162*** | 6.487*** | 6.490*** |
| (0.256) | (0.254) | (0.0104) | (0.0103) | (0.363) | (0.360) | |
| Lambda | ||||||
| _cons | 0.271 | 0.0473 | −0.0213 | |||
| (0.159) | (0.209) | (0.200) | ||||
| N | 80 | 80 | 80 | 80 | 80 | 80 |
Source: Authors’ research.
Standard errors in parentheses: *p < 0.05; **p < 0.01; ***p < 0.001.
Similar findings are also revealed by the two sets of results of the spatial analysis models detailed in Table 3. The estimated coefficients associated with models 1–4 are also positive and statistically significant, particularly for HIA, IOP, TE_EST and EDU_TR. TE_EST significantly contribute to reducing the POV (negative estimated coefficients statistically significant at the 0.1% threshold), while HIA and the IOP have the same positive effect in terms of poverty alleviation but also with regard to the increase in GVA for the eight development regions of Romania.
4. Concluding Remarks and Policy Implications
This research aimed to enhance the fundamentals of regional economic welfare in Romania under the shaping factors of digitalisation, a research topic increasingly relevant in the current context of technological swifts and transformations, Covid-19 pandemic and post-pandemic times. Main results encompass that digitalisation credentials, education and digital skills are essential for enhancing the economic development and labour market performance of various regions in Romania, with beneficial spill-overs on sustainable economic development, welfare and poverty lessening.
These advances bring to the fore important shifts in both demand and supply sides across regional economies that affect the equilibrium and overall performance, while public discourse, regulatory authorities, policy-makers and business representatives render global the keen need to strengthen the understandings in this scientific field. Main challenges and strategic areas evidenced by this study in terms of digitalisation in Romania are: (i) multilevel digital skills in ICT of graduates from education system; (ii) online labour market inclusion; (ii) research and development and innovation (RDI) in technologies, ICT; (iv) advanced digital services MS, which corresponds to the lowest level of at least basic digital skills accounted by the country in the last few years (DESI 2020). Counter performances are registered in terms of digital public services, where Romania holds the bottom position in the last three years. Hence, the e-government, cybernetic security and social media development represent a main problem and strategic area with a decisive impact on long-term socioeconomic development. The focus is on online public services, e-Governance platforms, electronic systems, cybernetic infrastructure, etc.
In terms of education, the ICT knowledge are considered essential in the teaching–learning process, since the ICT infrastructure can facilitate communication, knowledge transfer, as core elements of a knowledge-based digital society. Therefore, Romania’s national education system must briskly redesign the curricula, adjusted to the challenges of digitalisation era. E-commerce, RDI in ICT are other key directions considered by Romania as fundamentals of digitalisation. Broadband and digital services infrastructure complement previous strategic components and enhance the progress achieved by Romania in this area.
The main limitations of this research are given by constrained availability of regional data and relatively lower level of statistical significance for some variables. Our future research is set to assess the teleworking implications on the labour market, related to the job vacancies and specific skills tailored by educational providers, with a particular focus on higher education level.
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Acknowledgement
This work was supported by the Erasmus+ Project 2019-1-RO01-KA203-063214 entitled ‘Coordinated higher institutions responses to digitalization’ (ESCALATE).
- Prelims
- Chapter 1: Macroprudential Policy Contribution to the Post-COVID-19 Pandemic Economic Recovery
- Chapter 2: Sustainable Tourism in the Current European Context
- Chapter 3: The Path Towards International Non-financial Reporting Framework
- Chapter 4: Public Policy and Entrepreneurial Activity: Do We Have a Winning Tandem? Channels and Conduits
- Chapter 5: The Importance of Human Resources Competencies in Organisational Cyber Risk Management
- Chapter 6: Sustainability Development Assessment and Indicators
- Chapter 7: The Credit Market for Small and Medium Enterprises in the Republic of Moldova
- Chapter 8: The Role of Digitalisation in Reducing Risks and Bridging Regional Economic Welfare Gaps within a Sustainable Development Framework: The Case of Romania
- Chapter 9: The Impact of Information Technologies on Business During the COVID-19 Pandemic Outbreak
- Chapter 10: Examining the Effects of Sustainable HRM on Work Wellbeing: The Role of Voice Behaviour and Trust in Management
- Chapter 11: Changing Consumer Behaviour During the Pandemic Period: The Rise of Digital Transformation
- Chapter 12: Estimating the Financial Cycle Under Limited Data Availability: Alternative Methods
- Chapter 13: An Assessment of the Borsa Istanbul Insurance Index Return Structure: The Markov Regime Switching Model
- Chapter 14: Portfolio Performance of Public Sector General Insurance Companies in India: A Comparative Analysis
- Index