Prediction of the Situation of Postgraduate Entrance in China: Applicants and Enrollments

Authors

  • Chiyang Zhong

DOI:

https://doi.org/10.54097/fbwr5x54

Keywords:

ARIMA, postgraduate, applicant, enrollment.

Abstract

Applying for a postgraduate program has always been a popular choice after the four undergraduate years in China because it is deemed to increase competitivity in the job market. In recent years, applying for a postgraduate program has become more and more of a necessity when entering the job market. Therefore, it is important to understand and predict the postgraduate entrance trend. This paper used ARIMA model to predict the number of postgraduate applicants and enrollments in the near future after using KPSS tests to determine the order of differencing, and a combination of unit root tests, and optimization of AICc and MLE to find the optimal order of autoregression and moving average. The result reached is that the number of postgraduate applicants follows an ARIMA (1,2,0) model, and that of enrollments follows an ARIMA (3,2,0) model. The number of both postgraduate applicants and enrollment will keep on rising in the near future, while the admission rate is mostly stable.

Downloads

Download data is not yet available.

References

Laura Tucker. Ten Good Reasons to Go to Grad School. Postgraduate enrollment report, 2022.

Xue Gexi. The Number of Postgraduate Entrance Applicants is Estimated to be 4.91 million, Why the Anxiety. Working paper, 2023.

Shi Yi. Prediction of the National Graduate Postgraduate Enrollment Based on R Language and ARIMA Model. Computer Knowledge and Technology, 2018, 14.

Sun Mengjie, Chen Baofeng, Wen Chunhui, Ren Jinzheng. Postgraduate Enrollment Modeling and Forecast based on ARIMA models. Decision and Reference, 2010.

Hu Yun. Postgraduate Applicants Forecast based on QPSO-BP. Microcomputer Information, 2010.

Li Fengliang, Yuan Bentao, Liu Huiqin. Medium to Long Term Prediction of the Size of Chinese Graduate Students in School: An International Comparative Perspective. Higher Education Research, 2008, 29 (5): 7.

Zhang Wei, Wang Jinsong. Prediction of Graduate Education Scale and Comparison between China and the United States. Degree and Graduate Education, 2022, 2: 1 - 7.

Liu Shucai, Yin Ping. Prediction of the Development Scale of Graduate Education Based on BP Neural Network. Chinese Journal of Social Medicine, 2008, 3: 3.

Yin Fayue. Research on the Current Situation of Graduate Employment and Prediction of Employment Prospects. China Higher Education Evaluation, 2007, 3: 5.

Li Hongxia, Li Chuanwei. Application of Artificial Neural Network Models in Predicting Graduate Enrollment Quantity. Mathematical Practice and Understanding, 2009, 12: 7.

Downloads

Published

10-04-2024

How to Cite

Zhong, C. (2024). Prediction of the Situation of Postgraduate Entrance in China: Applicants and Enrollments. Highlights in Science, Engineering and Technology, 92, 56-66. https://doi.org/10.54097/fbwr5x54