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題名 應用關聯結構隨機邊界法探討我國勞工薪資低付與性別差異問題 作者 黃台心 貢獻者 金融系 關鍵詞 樣本選擇;薪資低付;組合誤差項;關聯結構法;隨機邊界關聯結構模型;薪資效率
sample selection; wage underpayment; composed errors;copula methods; stochastic frontier copula model;wage efficiency日期 2015 上傳時間 26-Dec-2017 17:45:04 (UTC+8) 摘要 當勞動市場上存在樣本選擇 (sample selection) 問題時, 本研究嘗試建構聯立迴歸模型, 同時包含隨機工資與工時兩條邊界方程式, 藉以探討男女兩性勞工薪資低付程度課題。基於組合誤差項的存在, 必須使用關聯結構法推導出它們的聯合機率密度函數, 進而建構隨機邊界關聯結構模型。整理民國94、96、98、100 與102等五年的台灣「人力運用調查」資料, 進行迴歸實證分析。再按年齡、工作經驗、教育程度、工作身分、婚姻狀態和工作地等6類, 分別比較男、女性勞工的薪資效率並檢定6個假說。實證結果發現考慮樣本選擇的平均薪資效率遠低於未考慮樣本選擇者,工作身分、工作地等 2 類, 不論有無考慮樣本選擇, 相同性別勞工薪資效率變動趨勢大致一致, 但其餘 4 類, 變動趨勢相左。考慮樣本選擇的實證結果與以往文獻有相當差異, 可能是因為以往文獻探討薪資效率時, 多未同時考慮樣本選擇問題, 即將無工作者樣本完全排除, 導致迴歸分析結果僅適用於有工作者。
This paper compiles the “Manpower Utilization Survey” data, conducted by Directorate General of Budget, Accounting, and Statistics, Executive Yuan, ROC, to study the issue of wage underpayment. Under the case of sample selection, we apply the copula methods to derive the joint probability density function for composed errors in the equations of wage and hours of work. The likelihood function is able to take both workers, who have observed wages, and non-workers, who have no observed wages, into account. Non-workers are usually excluded by previous researchers, studying similar issues like ours, since they overlook the role of sample selection. We separately estimate the male and female wage equations and evaluate the wage efficiency on the basis of six different classifications. The empirical results show that the trend of wage efficiency in the categories of working identity and working area are almost the same in each gender, whether correcting for the sample selection problem or not. However, in the remaining 4 categories, the sample selection bias appears to play an important role on the determination of wage efficiency. With the correction of the sample election bias, most of the findings differ from the past literatures that consider only workers with wage and salary.關聯 執行起迄：2015/08/01~2016/07/31
104-2410-H-004-012資料類型 report dc.contributor 金融系 zh_Tw dc.creator (作者) 黃台心 zh_TW dc.date (日期) 2015 en_US dc.date.accessioned 26-Dec-2017 17:45:04 (UTC+8) - dc.date.available 26-Dec-2017 17:45:04 (UTC+8) - dc.date.issued (上傳時間) 26-Dec-2017 17:45:04 (UTC+8) - dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/115429 - dc.description.abstract (摘要) 當勞動市場上存在樣本選擇 (sample selection) 問題時, 本研究嘗試建構聯立迴歸模型, 同時包含隨機工資與工時兩條邊界方程式, 藉以探討男女兩性勞工薪資低付程度課題。基於組合誤差項的存在, 必須使用關聯結構法推導出它們的聯合機率密度函數, 進而建構隨機邊界關聯結構模型。整理民國94、96、98、100 與102等五年的台灣「人力運用調查」資料, 進行迴歸實證分析。再按年齡、工作經驗、教育程度、工作身分、婚姻狀態和工作地等6類, 分別比較男、女性勞工的薪資效率並檢定6個假說。實證結果發現考慮樣本選擇的平均薪資效率遠低於未考慮樣本選擇者,工作身分、工作地等 2 類, 不論有無考慮樣本選擇, 相同性別勞工薪資效率變動趨勢大致一致, 但其餘 4 類, 變動趨勢相左。考慮樣本選擇的實證結果與以往文獻有相當差異, 可能是因為以往文獻探討薪資效率時, 多未同時考慮樣本選擇問題, 即將無工作者樣本完全排除, 導致迴歸分析結果僅適用於有工作者。 zh_TW dc.description.abstract (摘要) This paper compiles the “Manpower Utilization Survey” data, conducted by Directorate General of Budget, Accounting, and Statistics, Executive Yuan, ROC, to study the issue of wage underpayment. Under the case of sample selection, we apply the copula methods to derive the joint probability density function for composed errors in the equations of wage and hours of work. The likelihood function is able to take both workers, who have observed wages, and non-workers, who have no observed wages, into account. Non-workers are usually excluded by previous researchers, studying similar issues like ours, since they overlook the role of sample selection. We separately estimate the male and female wage equations and evaluate the wage efficiency on the basis of six different classifications. The empirical results show that the trend of wage efficiency in the categories of working identity and working area are almost the same in each gender, whether correcting for the sample selection problem or not. However, in the remaining 4 categories, the sample selection bias appears to play an important role on the determination of wage efficiency. With the correction of the sample election bias, most of the findings differ from the past literatures that consider only workers with wage and salary. en_US dc.format.extent 1298468 bytes - dc.format.mimetype application/pdf - dc.relation (關聯) 執行起迄：2015/08/01~2016/07/31 zh_TW dc.relation (關聯) 104-2410-H-004-012 zh_TW dc.subject (關鍵詞) 樣本選擇;薪資低付;組合誤差項;關聯結構法;隨機邊界關聯結構模型;薪資效率 zh_TW dc.subject (關鍵詞) sample selection; wage underpayment; composed errors;copula methods; stochastic frontier copula model;wage efficiency en_US dc.title (題名) 應用關聯結構隨機邊界法探討我國勞工薪資低付與性別差異問題 _TW dc.type (資料類型) report
