Issue |
SHS Web Conf.
Volume 39, 2017
Innovative Economic Symposium 2017 (IES2017)
|
|
---|---|---|
Article Number | 01005 | |
Number of page(s) | 10 | |
Section | Strategic Partnerships in International Trade | |
DOI | https://doi.org/10.1051/shsconf/20173901005 | |
Published online | 06 December 2017 |
CZ GDP Prediction via neural networks and Box-Jenkins Method
The Institute of Technology and Business in České Budějovice, School of Expertness and Valuation, Okružní 10, 370 01 České Budějovice, Czech Republic
* Corresponding author: dvorakova@mail.vstecb.cz
Economic indicators are nowadays ones of the most observed, their development does not only serve for comparing individual countries among each other but also show how the given country is prospering. That is why economists are trying to predict also the future development of these indicators via different statistical instruments. Neural networks or Box-Jenkins Method, able to predict future development based on data from the past, are one of the many instruments. The aim of this contribution is to find CZ GDP prediction per individual quarters using neural networks and Box-Jenkins Method, compare them mutually, and evaluate which of them is better.
Key words: GDP / prediction / neural networks / Box-Jenkins Method
© The Authors, published by EDP Sciences, 2017
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. (http://creativecommons.org/licenses/by/4.0/).
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