The Dynamic Effects of Economic Policy Uncertainty on Education Market Return Dynamics
- DOI
- 10.2991/978-94-6463-172-2_201How to use a DOI?
- Keywords
- economic policy uncertainty; education; dynamic effects; TVP-SV-VAR
- Abstract
In order to better explore the impact of economic policy uncertainty on the education market, this paper uses the time-varying parameter - random fluctuation vector auto regression (TVP-SV-VAR) model to analyze the impact of economic policy uncertainty (EPU) on the education rate of return and the education volatility. The results show that EPU has a significant time-varying effect on the return rate of China’s education market, and the short-term effect is the most significant. In terms of education volatility, EPU has a stronger influence on education market volatility in the medium and long term. In addition, when a crisis or major event occurs, the impact of EPU on China’s education market is greater and has a lag effect, among which the China-Us trade dispute and the impact of COVID-19 make the biggest contribution to market volatility.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Wang Gao AU - Qian Cao AU - Linlin Zhang PY - 2023 DA - 2023/06/30 TI - The Dynamic Effects of Economic Policy Uncertainty on Education Market Return Dynamics BT - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023) PB - Atlantis Press SP - 1814 EP - 1820 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-172-2_201 DO - 10.2991/978-94-6463-172-2_201 ID - Gao2023 ER -