Evaluation of trade influence on economic growth rate by computational intelligence approach

Svetlana Sokolov-Mladenović, Milos Milovančević and Igor Mladenović

Physica A: Statistical Mechanics and its Applications, 2017, vol. 465, issue C, 358-362

Abstract: In this study was analyzed the influence of trade parameters on the economic growth forecasting accuracy. Computational intelligence method was used for the analyzing since the method can handle highly nonlinear data. It is known that the economic growth could be modeled based on the different trade parameters. In this study five input parameters were considered. These input parameters were: trade in services, exports of goods and services, imports of goods and services, trade and merchandise trade. All these parameters were calculated as added percentages in gross domestic product (GDP). The main goal was to select which parameters are the most impactful on the economic growth percentage. GDP was used as economic growth indicator. Results show that the imports of goods and services has the highest influence on the economic growth forecasting accuracy.

Keywords: Trade; Computational intelligence; Forecasting; Economic growth (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:465:y:2017:i:c:p:358-362

DOI: 10.1016/j.physa.2016.08.031

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