Proceedings of the 6th International Conference on Strategies, Models and Technologies of Economic Systems Management (SMTESM 2019)

Neural network technology forecasting the country's business climate

Authors
Vita Los, Dmytro Ocheretin, Hanna Kucherova, Olha Bilska
Corresponding Author
Vita Los
Available Online September 2019.
DOI
https://doi.org/10.2991/smtesm-19.2019.62How to use a DOI?
Keywords
business climate, business confidence index, correlation analysis, socio-economic indicators, neural network modelling
Abstract
One of the important leading indicators that show the current state of the country's economic cycle, its prospects in the near future and generally characterize the country's business climate is the business confidence index (BCI). In this paper a forecast of the business confidence index is built using neural network technology using the example of the four European countries (Germany, Hungary, Poland, Slovenia).Forecasting was carried out taking into account economic indicators that characterize the socio-economic situation in the country. The selected economic indicators based on correlation analysis and have significant relationship with the business confidence index. For forecasting, the quarterly values of economic indicators for the last 12 years (2007-2018) were taken. Also the accuracy of the obtained forecasts was also assessed and the trends of the business confidence index development are established. It was found that the accuracy of the obtained forecasts is high. It has been proven that level of the BCI in the next period will decrease by 0.41% in Germany, by 1.05% in Hungary, by 0.99% in Poland and will remain unchanged in Slovenia. The obtained forecasting results make it possible to predict changes in the business climate in a country earlier than other macroeconomic indicators. The perspectives of the research are the elaboration of a country's business climate development strategies, based on the results of the BCI forecasting.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Vita Los
AU  - Dmytro Ocheretin
AU  - Hanna Kucherova
AU  - Olha Bilska
PY  - 2019/09
DA  - 2019/09
TI  - Neural network technology forecasting the country's business climate
BT  - Proceedings of the 6th International Conference on Strategies, Models and Technologies of Economic Systems Management (SMTESM 2019)
PB  - Atlantis Press
SP  - 320
EP  - 324
SN  - 2352-5428
UR  - https://doi.org/10.2991/smtesm-19.2019.62
DO  - https://doi.org/10.2991/smtesm-19.2019.62
ID  - Los2019/09
ER  -