Demand for MOOC - An Application of Big Data

Tingting Tong and Haizheng Li

China Economic Review, 2018, vol. 51, issue C, 194-207

Abstract: We evaluate factors affecting the demand for MOOC by estimating its demand function in OECD countries and in China. We apply a Big Data approach to construct a proxy for MOOC demand using Google Trends for OECD and Baidu Index for China. Based on estimation results of various panel data models, we find that in both cases, higher unemployment promotes MOOC demand. However, in OECD countries, the proportion of individuals with high school level or higher education have positive and significant effects on MOOC demand, while in China, we observe positive and significant effects from internet speed and average income.

Keywords: Online education; MOOC; Big Data; Google Trends; Baidu Index (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1043951X17300718
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:51:y:2018:i:c:p:194-207

DOI: 10.1016/j.chieco.2017.05.007

Access Statistics for this article

China Economic Review is currently edited by B.M. Fleisher, K. X. D. Huang, M.E. Lovely, Y. Wen, X. Zhang and X. Zhu

More articles in China Economic Review from Elsevier
Bibliographic data for series maintained by Catherine Liu ().