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Article
Undergraduate International Student Enrollment Forecasting Model: An Application of Time Series Analysis
Journal of International Students
  • Yu Chen, Louisiana State University
  • Ran Li, Iowa State University
  • Linda S. Hagedorn, Iowa State University
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2019
DOI
10.32674/jis.v9i1.266
Abstract

This study developed statistical models to forecast international undergraduate student enrollment at a Midwest university. The authors constructed a SARIMA (Seasonal Autoregressive Integrated Moving Average) model with input variables to estimate future enrollment. The SARIMA model reflected enrollment patterns by semester through highlighting seasonality. Further, authors added input variables such as visa policy changes, the rapid increase of Chinese undergraduate enrollment, and tuition rate into the model estimation. The visa policy change and the increase of Chinese undergraduate enrollment were significant predictors of international undergraduate enrollment. The effect of tuition rates was significant but minimal in magnitude. Findings of this study generate significant implications for policy, enrollment management, and student services for international students.

Comments

This article is published as Chen, Y., Li, R., & Hagedorn, L. S. (2019). Undergraduate International Student Enrollment Forecasting Model: An Application of Time Series Analysis. Journal of International Students, 9(1), 242-261. doi: 10.32674/jis.v9i1.266

Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 4.0
Copyright Owner
The Author(s)
Language
en
File Format
application/pdf
Citation Information
Yu Chen, Ran Li and Linda S. Hagedorn. "Undergraduate International Student Enrollment Forecasting Model: An Application of Time Series Analysis" Journal of International Students Vol. 9 Iss. 1 (2019) p. 242 - 261
Available at: http://works.bepress.com/linda_hagedorn/43/