勞動力為國家主要之經濟資源，它可以用來生產財貨與勞務，若未能善加運用，對個人與社會而言，皆是一種損失。勞動參與狀態可區分為勞動力與非勞動力，其中勞動力狀況又可分為就業與失業，失業率向來為重要之社會經濟指標，近年來隨著經濟發展程度提高，產業結構變動，結構性失業之情況值得重視。本研究之目的為探究人口因子影響勞動參與狀態，以2006年及2007年行政院主計處「人力資源調查」及「人力運用調查」資料庫之資料，將每年約6萬筆調查資料，以15歲以上民間人口（不含現役軍人及監管人口）資料為例，萃取出勞動力之人口因子變數，包括性別、年齡、教育程度、婚姻狀況、子女狀況、居住地區、前職行業別及前職職業別，應用邏輯斯迴歸方法建立勞動失業模型及非自願性離職模型。研究結果顯示性別、年齡層、教育程度、婚姻狀況變數對於就業、失業與否，具有顯著影響，地區別則無顯著差異；影響失業者自願或非自願離職因素，主要係年齡層、教育程度及前職行業、職業變數，性別、婚姻狀況及地區別則無顯著影響。由勝算比可得出男性較女性失業機率高；男性偏向非自願離職，女性則偏向自願離職；年齡層愈高者，較易有非自願離職情況；其中45歲以上者較25－34歲者較傾向非自願離職；教育程度者相較低教育程度者偏向自願性離職；2006年非自願離職以東區最高，2007年則以南區最高；前職行業方面，服務業較農工業不易發生非自願性離職狀況；前職職業方面，藍領階級較偏向非自願離職。

The purpose of this study is to find factors affecting labor participation status, by using data collected by government's manpower survey which were conducted by DGBAS. We select the civilian population of aged 15 and over and classify them into labor force (including employed or unemployed) and not in labor force based on the definition of ILO. The individual characteristics including gender, age, education level, marital status, children's age, living area and work experience (industry and occupation) are used as explanatory variables labor on. Three models are established by logistic regression analysis in this study. Model I is an unemployment event model, discussing the factors affecting employment and unemployment. Model II is an involuntary unemployment event model. The results show that factors such as gender, age, education level have effects on the unemployment rate, but not by living area. Involuntary unemployment event is affected by age, education level and work experience.