高等教育中途退学が就業形態や賃金に与える影響-ベイジアンネットワークを用いた分析-

Translated title of the contribution: Impact of Dropping out during Higher Education on Type of Employment and Wage - Analysis using the Bayesian Network

Shun Ikemoto, Hideo Suzuki

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

According to the survey “The circumstance of dropout and registered absence from higher education” conducted by the Japanese Ministry of Education in 2014, the number of dropouts from higher education is around 80,000. This accounts for 2.6% of all students. As for studies about dropouts, some of them are focused on the reason why students quit higher education institutions. However, there is little empirical research focused on the individual career, such as an employment, changing jobs and income after dropping out of higher education. This study places importance on data at the individual level, and analyzes 323 samples of higher education dropout workers and high school graduate workers gathered through a web-based questionnaire in January 2018. Our question items included gender, age, the type of first and current employment, annual income in 2017, information about their adjusted standard deviation score at high school and higher education institution, and family background such as their mother's and father's education and so on in order to carry out a detailed analysis. This uses the Bayesian Network based on conditional probability to examine the effects of dropping out of higher education on employment and annual income in 2017 by making comparisons to those of high school graduate workers.

Translated title of the contributionImpact of Dropping out during Higher Education on Type of Employment and Wage - Analysis using the Bayesian Network
Original languageJapanese
Pages (from-to)1-9
Number of pages9
JournalJournal of Japan Industrial Management Association
Volume70
Issue number1
DOIs
Publication statusPublished - 2019 Jan 1

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Impact of Dropping out during Higher Education on Type of Employment and Wage - Analysis using the Bayesian Network'. Together they form a unique fingerprint.

  • Cite this