E3S Web Conf.
Volume 166, 2020The International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2020)
|Number of page(s)||6|
|Published online||22 April 2020|
An alternative approach to modeling the country’s business climate in conditions of limited information
Zaporizhzhia National University, Faculty of Economics, Zaporizhzhia, 69600, Ukraine
2 Classic Private University, Chair of Economics, Zaporizhzhia, 69002, Ukraine
* Corresponding author: email@example.com
To date, the country’s business climate characterizes the state of economic development and the results of its effectiveness. One of the key indicators that determine the business climate is the business confidence index (BCI). The paper proposes an approach to modeling the business climate of the country, which is based on the principles of information transparency, and makes it possible to assess the development trends of the studied indicator. The proposed approach is based on the taxonomy method, which allows one to identify the measure of influence of each factor included in the model and exclude the influence of the subjective assessment of the researcher. This approach has been tested on the example of Ukraine. The quarterly values of socio-economic indicators for the past twelve years (2008-2019) were taken as input data. Based on the correlation analysis, from the generated array of incoming data, only those indicators were selected that have a significant relationship with the business confidence index. It has been established that the GDP annual growth rate and retail sales have the greatest impact on the business confidence index. A forecast has been built for the trend of changes in the business confidence index (forecast accuracy of 87.55%), which proves the similarity of development trends in the country’s business climate. The results obtained make it possible to analyze the cyclical development of the country’s economy with high accuracy and reliability.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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