分位數迴歸分析在高等教育報酬率的應用

Quantile Regression Analysis in Returns to Higher Education

分位數迴歸分析有別於普通最小平方法，除了可以估計中間值外，亦可求得不同分位數之估計成果，解釋整個分配情況，也因較全面性的解釋，使得分位數迴歸分析在各領域漸漸獲得重視。本文旨在探討分位數迴歸分析於教育領域上的應用，除整理分位數迴歸之資料處理與統計分析，並以臺灣教育改革20年高等教育科系別之教育報酬率為題，舉例說明分位數迴歸分析之應用。期許未來教育領域研究上可以融入分位數迴歸分析方法，以助於針對教育議題進行更深入之探討。

Quantile regression is different from the Ordinary Least Squares method, besides estimating intermediate values; it can also obtain different quantiles estimation, to effectively explain the whole distribution. Due to the more comprehensive explanation, quantile regression started to get more attention in all areas. This study aims to explore quantile regression analysis on education applications. Organize data and statistical analysis for quantile regression, using “Higher Education Disciplines Returns to Education in Taiwan” as an example to exemplified quantile regression analysis. Expect in future the field of educational research can integrate with quantile regression analysis, helping explore more deeply in the education area.