Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 26, 20 December 2023
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World unemployment problem and the unemployment rate forecasting with ARIMA model
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Abstract
In a rapidly changing global economic landscape, the level of unemployment remains one of the most important indicators of economic health, social stability and political dynamics. Due to the complexity and diversity of the unemployment problem, there are still some shortcomings and controversies in the existing research. Therefore, the aim of this study is to explore and predict unemployment in depth. This study mainly explores the history, current situation and influencing factors of unemployment statistics in depth, so as to make corresponding predictions and analyses. The research methods include literature review and R for relevant statistics and prediction. According to the forecast results, the world unemployment problem is still relatively serious, and the unemployment rate of the world population will remain relatively high in the coming years. However, due to the existence of various force majeure factors, the future unemployment rate may still show a relatively large increase or decline. This study demonstrated the applicability of the ARIMA model in predicting the values of this variable. These models do a good job of capturing patterns and trends, and the predicted values are reliable. At the same time, this study breaks through the traditional thinking, explores the causes of unemployment from multiple angles and analyzes the future social situation, which also has certain implications for further exploring the unemployment problem.
Keywords
World unemployment, ARIMA model, forecast
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-235-0
- ISBN (Online)
- 978-1-83558-236-7
- Published Date
- 20 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/26/20241031
- Copyright
- 20 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited