Abstract
This paper aims to model the cause-and-effect relationships between the world economy’s digital development and sustainable living. A broad selection of developed and developing countries examines what the world economy would have looked like without the crisis in 2020. Drawing on whether the virus is swept off or merely reduced, the dataset contains a forecast of the world economy for 2022. Being aware of alternative scenarios can be helpful in a wide range of scientific studies. The practical implications of the results of the scenario analysis consist in them allowing for the assessment of opportunities to overcome the COVID-19 viral threat with the help of vaccination.
Keywords: COVID-19 crisis, Cross-country overview, Development, Sustainability, Stability, Quick digital growth, Dataset
Introduction
Conveniently, conventional forecasts could not predict the COVID-19 crisis, indicating its non-standard nature. The development of a unique study methodology becomes highly topical because it was challenging to integrate the COVID-19 crisis into existing methodologies. To provide consistent knowledge of the world economy after the COVID-19 period, an innovative model is required to describe the crisis accurately and reliably.
Two scholarly hypotheses support this. According to the first hypothesis, the universal community will devote particular attention to achieving meaningful progress in achieving the SDGs (Okeke, 2021; Palomares et al., 2021; Sueyoshi et al., 2021; Zmiyak et al., 2021). The COVID-19 crisis will be solved by successfully implementing the SDGs to stabilize the world economy in the coming years (Popkova et al., 2020b).
According to the alternative hypothesis, the world economy is in for rapid digital growth (Bracci et al., 2021; Caldarelli et al., 2021; Castaldo et al., 2021; Cui and Kertész, 2021; Pollmann et al., 2021; Salvatore, 2021) that will overcome the crisis through high-tech innovation (Popkova et al., 2020a; Popkova et al., 2021).
These hypotheses illustrate how the world economy might change. In order to reduce uncertainty, the existing hypotheses need to be adequately explained. This paper describes each scenario and how digital development in the world economy and sustainable living are connected.
Data Description
Statistics on three blocks were collected and put in one Microsoft Excel table.
1st block: values of digital competitiveness index (in points) in 2020, from IMD Report (2021). The archive values of this indicator for 2019 are retrieved from the Dataset “Big data of the modern world economy: a digital platform for intellectual analytics – 2020” of the Institute of Scientific Communications (2021).
2nd block: values of sustainable development index from UNDP Report (Institute of Scientific Communications, 2021). The archive values of this indicator for 2019 are retrieved from the Dataset “Big data of the modern world economy: a digital platform for intellectual analytics – 2020” of the Institute of Scientific Communications (2021).
3rd block: statistics on the number of COVID-19 cases as of 5 August 2021 are from Infotables online table (Infotables, 2021). The growth of the digital competitiveness index and sustainable development index in 2020 as compared to 2019 is calculated. The data from the 2020 IMD Ranking are presented (Popkova and Sergi, 2021).
When analyzing data, it is essential to have timeliness, data compatibility, and reliability. Since the most severe phase of the crisis occurred in 2020, the chosen period is best for this research. The dataset included is as of August 2021, and the chosen period is ideal for this research. Thus, the timeframe of the research is 2019-2021. This allows taking into account the pre-pandemic status quo (2019) and the most acute phase of the COVID-19 pandemic and crisis (2020) and, the period of the post-crisis recovery of the economy and continuation of the pandemic in 2021.
Regression dependence is calculated on the growth of the digital competitiveness index and sustainable development index in 2020, compared to 2019, on the number of COVID-19 cases per 1,000 people (as of 5 August 2021). This paper evaluates the impact of the 2020 crisis using digital competitiveness and sustainable development indexes. The calculations are multipurpose to understand how the COVID-19 crisis affected digital competitiveness and resulted in sustainable development. We compare the digital and sustainable development losses to economic growth. The world economy forecast is based on reducing or defeating viral threats.
The digital competitiveness index for 2020 is sourced from the IMD report (IMD, 2021). The UNDP report (UNDP, 2021) is the data source on the sustainable development index. The source of archive data of these indices for 2019 is the Dataset “Big data of the modern world economy: a digital platform for intellectual analytics – 2020” of the Institute of Scientific Communications (2021). The data source for the number of COVID-19 cases (as of 5 August 2021) is the Infotables online table (Infotables, 2021). Data are presented in a numerical data array in one Microsoft Excel table. It is open access in Russian and English in a public repository, “Mendeley Data.”
New data from the data set is shown against a grey background. In contrast, the official statistics data is shown against a white background. This paper keeps this difference. In Table 1, the first ten countries are listed alphabetically.
Table 1.
Statistics on economic development in 2019-2020 and its growth, and statistics on the pandemic and the COVID-19 crisis as of 5 August 2021
| Country | Basic statistics on economic development | Statistics on the pandemic and the COVID-19 crisis as of 5.08.2021 | |||||
|---|---|---|---|---|---|---|---|
| Digital competitiveness index, points 1-100 | Sustainable development index, points 1-100 | Number of cases per 1,000 people | |||||
| 2019 | 2020 | Growth, % | 2019 | 2020 | Growth, % | ||
| Australia | 88.897 | 85.472 | -3.853 | 73.9 | 74.9 | 1.313 | 1.36 |
| Austria | 84.473 | 83.129 | -1.591 | 81.1 | 80.7 | -0.493 | 74.2 |
| Argentina | 56.044 | 48.784 | -12.954 | 72.4 | 73.2 | 1.064 | 111.0 |
| Belgium | 82.491 | 76.977 | -6.684 | 78.9 | 80.0 | 1.343 | 98.5 |
| Bulgaria | 63.663 | 56.295 | -11.573 | 74.5 | 74.8 | 0.362 | 60.9 |
| Brazil | 57.346 | 52.095 | -9.157 | 70.6 | 72.7 | 2.932 | 94.6 |
| Hungary | 65.472 | 55.914 | -14.599 | 76.9 | 77.3 | 0.572 | 83.3 |
| Venezuela | 27.763 | 23.991 | -13.586 | 63.1 | 61.7 | -2.250 | 9.45 |
| Germany | 86.216 | 81.062 | -5.978 | 81.1 | 80.8 | -0.407 | 45.5 |
| Greece | 59.633 | 56.209 | -5.742 | 71.4 | 74.3 | 4.104 | 46.6 |
Source: Fragment of the dataset (Popkova and Sergi, 2021)
According to the new data presented in Table 1, the growth (reduction) of the digital competitiveness index in Australia in 2020 was -3.853%, compared to 2019, and the growth of the sustainable development index – 1.313%. The number of COVID-19 cases in Australia (as of 5 August 2021) is meagre: 1.07 per 1,000 people, i.e., 1.07/1000=0.00107%.
Experimental Design, Materials, and Methods
Data and modelling applied to the global economic system. Results are dependable at the global level of the economy. The regression curves are derived from the primary data and reflect the dependence of the growth of the digital competitiveness index and sustainable development index on the number of COVID-19 cases (Figs. 1 and 2).
Fig. 1.
Regression curve of the dependence of growth of digital competitiveness index on the number of COVID-19 cases. Source: Fragment of the dataset (Popkova and Sergi, 2021)
Fig. 2.
Regression curve of the growth of sustainable development index on the number of COVID-19 cases. Source: Fragment of the dataset (Popkova and Sergi, 2021)
The number of COVID-19 cases per 1,000 people reduces the digital competitiveness index by 0.0349% (Fig. 1). A low value of the correlation coefficient (0.48%) indicates that the pandemic and the COVID-19 crisis are ordinary (not the primary) factors of the digital growth of the world economy in 2020.
Figure 2 indicates that an increase in the number of COVID-19 cases per 1,000 people increases the sustainable development index by 0.0004%. The very low correlation coefficient indicates that the pandemic and the COVID-19 crisis are common, insignificant factors of sustainable development of the world economy in 2020. The regression coefficients (Figs. 1 and 2) allow us to calculate the growth of the digital competitiveness index and the sustainable development index directly under the isolated influence of the crisis in 2020. Table 2 shows the opportunities for each country’s development lost due to the crisis in 2020.
Table 2.
Growth under the influence of the crisis and lost opportunities for digital and sustainable development of countries of the world in 2020
| Country | Growth under the influence of the crisis in 2020 | Opportunities for development in 2020 that are lost due to the crisis | ||
|---|---|---|---|---|
| Digital competitiveness index, % | Sustainable development index, % | Digital competitiveness index, % | Sustainable development index, % | |
| Australia | -6.998 | 1.090 | 3.145 | 0.222 |
| Austria | -7.451 | 1.096 | 5.860 | -1.589 |
| Argentina | -7.890 | 1.101 | -5.064 | -0.037 |
| Belgium | -8.339 | 1.106 | 1.654 | 0.238 |
| Bulgaria | -7.282 | 1.094 | -4.291 | -0.731 |
| Brazil | -7.882 | 1.100 | -1.274 | 1.832 |
| Hungary | -7.287 | 1.094 | -7.312 | -0.521 |
| Venezuela | -7.060 | 1.091 | -6.527 | -3.341 |
| Germany | -7.211 | 1.093 | 1.233 | -1.500 |
| Greece | -7.104 | 1.092 | 1.362 | 3.012 |
Source: Fragment of the dataset (Popkova and Sergi, 2021)
The example of Australia has been used to perform calculations. The number of cases in Australia is shown in Fig. 1 to determine the growth of the digital competitiveness index. The following equation (-0.0349*1.07+6.9602=-6.998%) shows that the digital competitiveness index is declining amid the 2020 crisis. The digital competitiveness index was assessed under the impact of the 2020 crisis by placing the value of the number of cases in Australia (1.07) in the equation in Fig. 2. This equation follows: 0.0004*1.07+1.0899=1.090.
Regression analysis results are only reliable for individual countries, not the world economy. In this example, research into the Australian experience would provide more specific recommendations.
The recommended replacement value of 1.07 for Australia to get 1.090 represents a value determined by the regression curve. Furthermore, In 2020, the Australian economy lost 3.145% (-6,998-(-3,853)), that is, the difference between general growth from Table 1 (-3.853) and growth amid the pandemic crisis from Table 2 of its potential growth due to the COVID-19 crisis (-6.998). In 2020, Australia’s digital competitiveness index would have grown by 3.145% compared to 2019, demonstrating the negative impact of the crisis.
The following is a forecast of the world economy after the COVID-19 crisis (for 2022) based on the above data. The two most probable scenarios of post-COVID-19 pandemic development follow:
The scenario of overcoming the viral threat envisages that the development of innovations in healthcare (drugs and vaccines) or an independent end of the pandemic (similar to “Spanish flu” at the beginning of the 20th century) will lead to a reduction of the number of cases in all countries down to 5% of the population – i.e., 50 cases per 1,000 people. Then the expected growth of the digital competitiveness index will equal (-0.0349*50-6.9602)/100+1=0.9129, and the expected growth of the sustainable development index will equal: (0.0004*50+1.0899)/100+1=1.0111;
Reducing the viral threat and normalising the number of cases envisages COVID-19 becoming a typical acute respiratory disease, and 100% of the world population will have had it – i.e., up to 1,000 cases per 1,000 people. Then the expected growth of the digital competitiveness index will be: (-0.0349*1,000-6.9602)/100+1=0.5814, and the expected growth of the sustainable development index will be: (0.0004*1,000+1.0899)/100+1=1.0149. The forecast employs the products of the actual values of the indicators for 2020 and the obtained values of their growth (see Table 3).
Table 3.
Forecast of the world economy for 2022
| Country | Forecast of the world economy after the COVID-19 crisis (for 2022) | |||
|---|---|---|---|---|
| According to the scenario of overcoming the viral threat | According to the scenario of reduction of the viral threat and normalization of the number of cases | |||
| Digital competitiveness index, points 1-100 | Sustainable development index, points 1-100 | Digital competitiveness index, points 1-100 | Sustainable development index, points 1-100 | |
| Australia | 78.031 | 75.701 | 49.693 | 75.985 |
| Austria | 75.892 | 81.596 | 48.331 | 81.902 |
| Argentina | 44.537 | 73.982 | 28.363 | 74.260 |
| Belgium | 70.276 | 80.847 | 44.754 | 81.151 |
| Bulgaria | 51.394 | 75.600 | 32.730 | 75.884 |
| Brazil | 47.560 | 73.477 | 30.288 | 73.753 |
| Hungary | 51.047 | 78.198 | 32.508 | 78.492 |
| Venezuela | 21.903 | 62.365 | 13.948 | 62.599 |
| Germany | 74.005 | 81.666 | 47.129 | 81.973 |
| Greece | 51.316 | 75.155 | 32.680 | 75.437 |
From: Fragment of the dataset (Popkova and Sergi, 2021)
Let us consider Australia. The digital competitiveness index equalled 85.472 points in 2020. The scenario of overcoming the viral threat in 2022 will equal 85.472*0.9129=78.031 points; reducing the viral threat and normalising the number of cases will equal 85.472*0.5814=49.693 points. The sustainable development index in Australia equals 74.9 points in Australia. According to the scenario of overcoming the viral threat in 2022, it will equal 74.9*1.0111=75.701 points. Reducing the viral threat and normalising the number of cases will equal 74.9*1.01449=75.985 points.
Therefore, overcoming the viral threat will allow the world economy to experience rapid digital growth and reclaim the opportunities squandered under the influence of the pandemic in 2020. Normalizing the number of cases will exacerbate the problem of sustainable development and capture the world’s attention to the issue of impending viral threats. It is therefore, preferable to overcome the viral threat, which implies reducing the number of cases in all countries to 5% of the population, i.e., 50 cases per 1,000 people. Unfortunately, this scenario is only being implemented in some countries. Unusual attention should be directed to China, which faced a new wave of the growth of COVID-19 cases after the cancellation of the “zero COVID” policy at the end of 2022. We should also note that China is the only country worldwide that has vaccinated a billion people at once. Due to the limited capabilities of the modern global healthcare system, the modern healthcare system is facing a severe challenge.
Conclusions
The dataset includes statistics on digital competitiveness, sustainable development, and the number of COVID-19 cases in 63 developed and developing countries. The editable table can be used for research to investigate the world economy during and after the COVID-19 crisis.
It is possible to use the dataset for thorough research of the world economy’s development in digitalization and sustainable living because it provides data for 2019-2020 in the general table. The link between the number of COVID-19 cases and digital competitiveness and sustainability, as well as between the number of COVID-19 cases and their change (growth) in the 2019–2020 dynamics, were determined;
The digital competitiveness index and sustainable development index growth are included in the data. It is significant to note that the growth forecast for 2020 is based on the COVID-19 crisis and does not consider any other factors. The growth figures for 63 countries would benefit studies on the 2020 crisis and provide data for various developed and developing countries.
The dataset assessed the loss of profit from digital competitiveness and sustainable development for 63 countries in 2020. According to the Australian experience before the pandemic, the sustainable development index was expected to grow from 73.9 points in 2019 to 74.9 points in 2020 (+1.313). However, due to the COVID-19 pandemic, Australia’s sustainable development index experienced growth of 1.090%; to such a degree, the unrealized profit was 0.222% (1.313-1.090). The world economy would have developed otherwise if the crisis had not occurred. The alternative scenarios allow for the use of this forecast in a broad range of scientific research.
Declarations
Ethics Approval
The data set contains only data from open sources. Any use of the data that are a commercial secret or are under regulatory & legal or ethical limitations is impossible.
Competing Interest
The dataset is the development of Prof. Elena G. Popkova and Prof. Bruno S. Sergi.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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