本研究之目的在於試圖以客觀量化資料，評估各組勞動力結構性失業惡化的程度。研究中所採用的灰預測發展係數，應為一可行指標，日後進行結構性失業惡化程度評估時，除了主觀觀察之外，還可考量此一量化指標。本研究使用Gordon所提出之方法衡量結構性失業。但評估結構性失業惡化與否為一時間序列的問題，乃利用灰預測中的發展係數進行評估。研究發現不同年齡層勞動力中，不論男女均為青少年組已發生結構性失業，且在惡化中；而女性青壯年勞動力，雖未發生結構性失業問題，但有迅速惡化跡象，值得注意後續變化。不同教育程度男性勞動力中，基層與中等教育組已發生結構性失業，所幸日有改善；女性均未發生結構性失業；但以惡化程度而言，則以高等教育程度勞動人力的惡化趨勢，較引人注意。

This study uses the development factors of Grey Forecasting Model to examine the degree of structural unemployment on twenty workforce groups. Empirical results show that the development factor could be a valid and object indicator when we try to judge the trend of structural unemployment from a time series data set. In addition, the results reveal that the structural unemployment by age: (1) youth workforce continues to grow; (2) female whose age is between 25-44 has grown rapidly. Meanwhile, the empirical results show that structural unemployment by education: (1) male who is or less than senior high school has declined slightly; (2) the workforce who is or above university goes up.