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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 邱鳳臨 | |
| dc.contributor.author | Yi-Fang Li | en |
| dc.contributor.author | 李宜芳 | zh_TW |
| dc.date.accessioned | 2021-06-13T02:32:12Z | - |
| dc.date.available | 2007-02-02 | |
| dc.date.copyright | 2007-02-02 | |
| dc.date.issued | 2007 | |
| dc.date.submitted | 2007-01-24 | |
| dc.identifier.citation | 中文部份:
1. 行政院主計處民國92年台灣地區婦女婚育與就業調查報告。 2. 行政院主計處民國94年台灣地區家庭收支調查報告。 3. 符碧真(1996),「教育投資報酬率長期變化之剖析─以我國教育發展個案為例」,教育研究資訊,4:1,頁81-99。 4. 吳慧瑛(2000),「二十年來台灣地區教育發展之經濟評估」,臺灣經濟預測與政策,33:2,頁97-130。 5. 蔡淑鈴、瞿海源(1992),「台灣教育階層化的變遷」,國家科學委員會研究彙刊:人文及社會科學,2(1),頁98-118。 6. 蔡貞慧、周穎政(2000),「父母所得對子女接受高等教育的影響」,中央研究院中山人文社會科學研究所第三屆家庭與社會資源分配學術研討會論文集,頁1-24。 7. 駱明慶(2000),「教育成就的省籍與性別差異」,經濟論文叢刊,32:4 ,頁417-445。 8. 駱明慶(2002),「誰是台大學生?性別、省籍與城郷差距」,經濟論文叢刊,30:1 ,頁113-147。 9. 李玫愔(2002),「家庭背景對人力資本投資報酬的影響-台灣實證」,國立暨南國際大學經濟學研究所碩士論文。 10. 李巧琳(2002),「人力資本的代間移轉-家庭背景對子女教育成就的影響」,國立暨南國際大學經濟學研究所碩士論文。 11. 羅曉惠(2002),「快速經濟成長下人力資本投資報酬率的變化-台灣實證」,國立暨南國際大學經濟學研究所碩士論文。 12. 陳永欽(2002),「家庭背景對子女教育成就之影響」,國立暨南國際大學經濟學研究所碩士論文。 英文部份: 1. Armitage, Jane and Sabot, Richard(1987),”Socioeconomic background and the returns to schooling in two low-income countries”, Economica, 54, p103-108. 2. Becker, G.S.,(1960),”Investment in Human Capital: A Theoretical Analysis”, Journal of Political Economy,70(5),p9-49. 3. Becker, G.S. and Tomes, N.(1979), 'An Equilibrium Theory of the Distribution of Income and Intergenerational Mobility”, Journal of Political Economy, 87.6:1153-1189. 4. Behrman, Jere R. and Wolfe, Barbara L.(1984), “The socioeconomic impact of schooling in a developing country”, Review of Economics and Statistics, 66(2),p296-303. 5. Bourdieu, Pierre(1977), “Reproduction in Education, Society, Culture”, Beverly Hills, CA: Sage. 6. Carnoy, Martin(1967), “Earnings and schooling in Mexico”, Economic Development and Cultural Change,15, p408-419. 7. Thomas, Duncan(1996), “Education across generations in South Africa”, American Economic Review, 86(2), p330-334. 8. Fung-Mey Huang(2000),”The Impact of Childhood Events on Educational Achievement: A Sibling Study”, Taiwan Economic Review, 28:4, p425-450. 9. Heckman, James J. and Horz, V. Joseph(1986), “An investigation of the labor market earnings of Panamanian males: evaluating the sources of inequality”, Journal of Human Resources, 23, p207-542. 10. Jin-Tan Liu , James K. Hammitt , and Chyongchiou Jeng Lin(2000),“Family background and returns to schooling in Taiwan”, Economics of Education Review:Vol19, p113-125. 11. Lam, David and Schoeni, Robert F.(1993),”Effects of family background on earnings and returns to schooling: Evidence from Brazil”, Journal of Political Economy, 101(4), p710-740. 12. Mincer, Jacob A.(1974),“Schooling, Experience, and Earnings”, Studies in Human Behavior and Social Institutions No. 2, University Microfilms. 13. Ozdural, Sanem(1993), “Intergenerational mobility: a comparative study between Turkey and the United States”, Economics Letters, 43, p221-230. 14. Papanicolau, John and Psacharopoulos, George(1979), “Socioeconomic background, schooling and monetary rewards in the United Kingdom”, Economica, 46, p435-439. 15. Psacharopoulos, George(1985), “Returns to education: a further international update and implications”, Journal of Human Resources, 20(4), p583-604. 16. Sahn, David E. and Alderman, Harold(1988), “The effects of human capital on wages, and the determinants of labor supply in a developing country”, Journal of Development Economics, 29, p157-183. 17. Shu-Ling Tsai, Hill Gates, Hei-Yuan Chiu(1994), “Schooling Taiwan’s Women: Educational Attainment in the Mid-20th Century”, Sociology of Education, 67, p243-263. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/31144 | - |
| dc.description.abstract | 本研究主要目的是想了解家庭背景因素是否會影響子女的教育投資報酬,並進一步探討,在分階段加入個人特質、其父母親及其配偶的特質(教育程度、職業及從業身份)之後,個人特質對於解釋其工資率的效果是否會改變。本研究以Mincer(1974)的人力資本理論為基礎,根據Lam與 Schoeni (1993)提出的模型,並以Liu, Hamimt and Lin(1999)的研究為藍本,加入家庭背景因素的考量後觀察在不同的樣本及變數下教育投資報酬率的變化。此外,本研究與以往文獻最大的區別在於樣本的選取。除了已婚成年男性以外,本研究也以未婚女性為樣本進行實證分析,這群未婚女性樣本最大的特徵就是其擁有較高學歷,且對於所得具有較大的支配能力。
本研究採用採用普通最小平方法(Ordinary Least Squares, OLS)進行實證分析。所有變數之統計資料來源均來自華人家庭動態資料庫(Panel Study of Family Dynamics,以下簡稱PSFD)及行政院主計處的人力運用調查(Manpower Utilization Survey,以下簡稱MUS)的原始資料。選定所有家計部門中20至65歲的受訪者,且樣本的限制是台灣地區成年的已婚男性勞動者(MUS再另外增加未婚女性的樣本)。 本研究實證分析結果可歸納如下:男性已婚工作者的薪資可由自身的教育程度解釋一部份,若忽略家庭背景因素將造成教育投資報酬的高估,但家庭背景因素只有妻子的教育程度是顯著的,從我們的資料中卻無法證實父母親的特性對兒子薪資的影響。近年來家庭背景因素對子女薪資的影響逐漸式微。另外,未婚女性樣本的實證結果異於男性已婚樣本。本研究發現父親教育程度對未婚女性工作者薪資有正面影響,家庭背景因素對於未婚女性樣本而言較為顯著,家庭背景較佳的女性可能獲得較高的薪資報酬。這可能是因為年輕女性需藉由家庭背景的力量助其取得較高的婚姻成就。 | zh_TW |
| dc.description.abstract | Purpose of the study is to understand if the returns of schooling would be influenced by family background factor. In other words, we would like to know the relationship of the family background and the workers’ wage rates. That is, we consider into several factors such as individual his own attributes, his parents’ level of education, occupations, and his wife’s level of education and occupation, and then we would like to understand if the effects of individual his own attributes on the wage rate would change. The study is based on Mincer’s human capital theory, the model created by Lamand Schoeni in 1993, and Liu, Hamimt and Lin’s study in 1999. After adding family background variables into the consideration, we would like to observe the change of the returns to schooling with different variables and different samples. Besides, the most obvious distinction from other studies in the past is the selection of samples. In addition to adult married male samples, the study also adopts adult unmarried female samples to take a statistical analysis. The unmarried female samples are most characterized by their higher level of education, and have more domination right to income. We also like to know the effects of family background on female worker’s wage rates.
We utilize the original data of Manpower Utilization Survey (MUS) and Panel Study of Family Dynamics (PSFD) to proceed with the Ordinary Least Squares analysis and examine the relationship of family background and worker’s wage rates. In the study, we select the workers aged 20 -65, and restrict our analysis to married male workers living in Taiwan. But in the MUS data base, we also adopt the unmarried female samples. Findings of the empirical analysis are that married male workers’ wage rates can be explained partly by their level of education. Returns of schooling would be overvalued without considering family background factor, but only wives’ level of education could affect workers’ wage rates. According to the data in the study, we can’t confirm the effects of parents’ attributes on children’s wage rates. Recently the effects of family background factor on children’s wage rates are gradually fading. On the other hand, the empirical conclusion of unmarried female samples is differed from that of married male samples. The study concludes that father’s level of education plays important role on the wage rates of unmarried females. The effects of family background factors on unmarried females are more evident, that is, unmarried women who come from better family have higher wage rates. The reason may be that the ideal strategy of social mobility for women is a pattern based on attainment through marriage, rather than attainment via one’s own education, as for men. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T02:32:12Z (GMT). No. of bitstreams: 1 ntu-96-R92341065-1.pdf: 3249770 bytes, checksum: c03f2658ae5145ee326e7ddcad05cf81 (MD5) Previous issue date: 2007 | en |
| dc.description.tableofcontents | 謝誌……………………………………………………………………………………Ⅰ
中文摘要………………………………………………………………………………Ⅱ 英文摘要……………………………………………………………………………….Ⅲ 目錄…………………………………………………………………………………….Ⅴ 圖目錄………………………………………………………………………………….Ⅶ 表目錄………………………………………………………………………………….Ⅷ 第一章 緒論………………………………………………………………………...1 第一節 研究背景與研究動機………………………………………………...1 第二節 研究目的……………………………………………………………...4 第三節 研究方法與研究對象………………………………………………...5 第四節 論文架構……………………………………………….. ……………5 第二章 文獻回顧…………………………………………………………………...7 第一節 未考慮家庭背景因素的教育投資報酬……………………………...8 第二節 納入家庭背景因素………………………………………….………..9 第三章 資料及基本統計量分析………………………………………………….14 第一節 資料來源…………………………………………………………….14 第二節 樣本與變數選取說明……………………………………………….16 第三節 基本統計量分析…………………………………………………….19 第四章 研究方法………………………………………………………………….24 第一節 理論模型…………………………………………………………….24 第二節 實證模型…………………………………………………………….26 第五章 實證結果…………………………………………………… ……………30 第一節 PSFD資料庫………………………………………..……………...30 第二節 MUS資料庫………………………………………………………...33 第六章 結論與建議……………………………………………………………….38 第一節 結論………………………………………………………………..….38 第二節 研究限制與建議……………………………………………………...40 參考文獻……………………………………………………………………………….41 圖1-1 民國82~94年我國15歲以上口人不識字率的變化.................................44 圖1-2 民國65~94年我國基礎教育的變化........................................................44 圖1-3 民國65~94年我國高等教育的變化........................................................44 圖1-4 民國65~94年我國高等教育淨在學率的變化..........................................45 圖1-5 94年按教育程度別區分的受雇就業者平均每月收入..............................45 圖1-6 1980年至2005年我國所得分配情形.....................................................45 表1-1 我國15歲以上人口的教育程度........................................... ...... ...........46 表1-2 我國受僱員工每人每月平均薪資............................................................48 表1-3 89-94年我國受雇就業者平均每月收入-按教育程度別區分..................49 表2-1 文獻回顧表-未考慮家庭背景因素……………………………………......50 表2-2 文獻回顧表-納入家庭背景因素………………………………………......51 表3-1 基本統計量分析-PSFD資料庫 全樣本……………………………......56 表3-2 PSFD 不同部門間受僱者的基本統計量………………………………..60 表3-3 PSFD各變數間之相關係數表…………………………………………….60 表3-4 基本統計量分析-MUS資料庫 第一類組全樣本…………………...…61 表3-5 基本統計量分析-MUS資料庫 第二類組-成年子女與戶長父母同住 的樣本……………………………………………………………………....65 表3-6 基本統計量分析-MUS資料庫 第三類組-戶長子女與父母同住的樣本……………………………………………………………………………69 表3-7 基本統計量分析-第四類組-成年未婚女性的樣本……………………73 表3-8 MUS 不同部門間受僱者的基本統計量(全樣本)……………………76 表3-9 MUS各變數間之相關係數表……………………………………………..76 表5-1 PSFD資料庫 全樣本 男性工作者工資率之估計……………………..77 表5-2 PSFD資料庫 全樣本年齡分層 男性工作者工資率之估計…………..79 表5-3 PSFD資料庫 全樣本 男性工作者工資率之估計(以社經變數作為家 庭背景因素)………………………………………………………………80 表5-4 PSFD資料庫 全樣本-加入父母省籍…………………………………..84 表5-5 PSFD資料庫 全樣本年齡分層-加入父母省籍………………………..85 表5-6 MUS資料庫 第一類組全樣本 男性工作者工資率之估計…………....87 表5-7 第一類組全樣本 男性工作者工資率之估計(以社經變數作為家庭背景因素)………………………………………………………………….........89 表5-8 MUS資料庫 第二類組-戶長子女與父母同住的樣本 男性工作者工資率之估計……………………………………………………………………92 表5-9 MUS資料庫 第二類組-戶長子女與父母同住的樣本 男性工作者工資率之估計(以社經變數作為家庭背景因素)……………………….......94 表5-10 MUS資料庫 第三類組-戶長父母與成年子女同住的樣本 男性工作者工資率之估計…………………………………………………………......97 表5-11 MUS資料庫 第三類組-戶長父母與成年子女同住的樣本 男性工作者工資率之估計(以社經變數作為家庭背景因素)……………………. .99 表5-12 MUS資料庫 第四類組-未婚女性工作者工資率之估計……………. 102 表5-13 MUS資料庫 第四類組-未婚女性工作者工資率之估計(以社經變數作為家庭背景因素)………………………………………………………...104 表5-14 MUS資料庫 未婚男性與未婚女性工作者工資率估計之比較……….106 | |
| dc.language.iso | zh-TW | |
| dc.subject | 社會階層 | zh_TW |
| dc.subject | 家庭背景 | zh_TW |
| dc.subject | 教育投資報酬 | zh_TW |
| dc.subject | 人力資本 | zh_TW |
| dc.subject | 選擇性配對效果 | zh_TW |
| dc.subject | returns of schooling | en |
| dc.subject | social stratification | en |
| dc.subject | assortative mating | en |
| dc.subject | family background | en |
| dc.subject | human capital | en |
| dc.title | 家庭背景對教育投資報酬之影響-台灣實證 | zh_TW |
| dc.title | Family background and returns to schoolings-Evidence from Taiwanese Household Survey | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 95-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 周治邦,唐代彪 | |
| dc.subject.keyword | 家庭背景,教育投資報酬,人力資本,選擇性配對效果,社會階層, | zh_TW |
| dc.subject.keyword | family background,returns of schooling,human capital,assortative mating,social stratification, | en |
| dc.relation.page | 106 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2007-01-24 | |
| dc.contributor.author-college | 社會科學院 | zh_TW |
| dc.contributor.author-dept | 國家發展研究所 | zh_TW |
| 顯示於系所單位: | 國家發展研究所 | |
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