Dataset of development of business during the COVID-19 crisis
To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.
Steps to reproduce
At the first stage, multiple calculations were made to carry out calculations separately for each country, and then to aggregate the data and form a single data table reflecting the situation in international entrepreneurship in the context of the COVID-19 pandemic and crisis. At the second stage, the dependence of changes in entrepreneurship indicators in 2020 compared to 2019 (as a percentage) on the incidence rate per 1000 people was automatically determined (using the functions of the Microsoft Excel Analysis Package). population and the percentage of deaths from COVID-19 (separately). Detailed regression statistics are provided. A qualitative interpretation of this dependence is given, which made it possible to characterize the presence and scale of the risks of a pandemic for international entrepreneurship. At the third stage, a forecast (by generating 1000 random numbers) of morbidity and mortality from COVID-19 was automatically made. Values are brought in accordance with the normal distribution and histograms are plotted. The most probable values of these indicators for the period of the second wave of the pandemic have been determined; they are substituted into the previously obtained regression equations. Based on this, the risks of the second wave of the pandemic for entrepreneurship are identified and diagrams are built for data visualization.