Author
Listed:
- Bruno S. Sergi
(Department of Economics, University of Messina, 98122 Messina, Italy)
- Elena G. Popkova
(“Scientometrics and International Ratings” Laboratory, Armenian State University of Economics, Yerevan 0025, Armenia)
- Elena Petrenko
(Academic Department of Management and Business Technologies, Plekhanov Russian University of Economics, Stremyanny Lane 36, 117997 Moscow, Russia)
- Shakhlo T. Ergasheva
(Department of Accounting, Tashkent State University of Economics, Tashkent 100066, Uzbekistan)
- Mkhitar Aslanyan
(Department of Finance, Armenian State University of Economics, Yerevan 0025, Armenia)
- Vahe Mikayelyan
(Faculty of Applied Finance, Armenian State University of Economics, Yerevan 0025, Armenia)
Abstract
This article presents an innovative methodology for enhancing statistical databases as reliable sources of information. The study leverages data from “Big Data of the Modern Global Economy: A Digital Platform for Data Mining—2020”, which serves as a digital tool designed to predict economic development at both global and national levels, particularly in the context of the COVID-19 crisis and its aftermath. Utilizing a dataset focused on the G7 and BRICS nations as a case study, we assemble forecasts for several key indicators: the Digital Competitiveness Index, Global Innovation Index, Human Development Index, Gross Domestic Product (GDP), Economic Growth Rate, GDP per Capita, Quality of Life Index, Happiness Index, and Sustainable Development Index for 2021. Additionally, we conducted a plan-fact analysis. The accuracy of the post-pandemic economic recovery forecast is validated through comparison with actual data. Furthermore, this research provides statistical analyses and forecasts to minimize uncertainty during crises, considering the interconnected nature of climate change and financial factors inherent in these crises.
Suggested Citation
Bruno S. Sergi & Elena G. Popkova & Elena Petrenko & Shakhlo T. Ergasheva & Mkhitar Aslanyan & Vahe Mikayelyan, 2025.
"An Innovative Digital Platform for Socioeconomic Forecasting Climate Risks and Financial Management,"
JRFM, MDPI, vol. 18(5), pages 1-20, May.
Handle:
RePEc:gam:jjrfmx:v:18:y:2025:i:5:p:277-:d:1658124
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