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題名 探討人力資本不均與薪資收入不均之關聯 - 以台灣製造業資料為例
A study on the relationship between human capital and wage inequality – Using dataset of Taiwan manufacturing sector
作者 韓詠翔
Han, Yung-Hsiang
貢獻者 蕭明福
韓詠翔
Han, Yung-Hsiang
關鍵詞 人力資本
薪資不均
固定效果模型
隨機效果模型
製造業
日期 2020
上傳時間 4-Jan-2021 11:21:26 (UTC+8)
摘要 本論文利用民國 92 年到 108 年的人力運用調查資料及經濟部製造業投資營運概況調查之資料，依製造業及其次產業別彙編成追蹤資料，探討台灣製造業之薪資收入不均與人力資本不均之間的關聯性。經由追蹤資料單根檢定，確立研究資料的定態性質，並經由 F 檢定、LM 檢定、及 Hausman 檢定，選出合適的迴歸模型進行資料分析。
對於人力資本的衡量，本論文認為教育程度適切地描述了進入職場以前的人力資本，但潛在工作年數並不足以描述職場階段的人力資本，因為產業之間存在著技術特性的差異，因而提出此階段人力資本的新衡量方式：潛在工作年數與實物資本量之乘積。
本論文實證發現，對整體製造業而言，教育年數不均度、潛在工作年數不均度、及調整後的工作經驗不均度，對薪資收入不均度皆呈現顯著的正向關係。然而，比起以潛在工作年數代理職場人力資本的迴歸模型，用潛在工作年數和實物資本量之乘積當作職場人力資本代理變數的迴歸模型，具有較高的解釋能力。在製造業次產業別裡，民生工業、化學工業以及資訊電子工業的迴歸結果顯示，民生工業與資訊電子工業的薪資收入不均度僅受潛在工作年數不均度和調整後的工作經驗不均度的顯著正向影響，但無足夠證據支持這兩個次產業的薪資收入不均度與教育年數不均度有顯著正向關係。在化學工業方面，其迴歸結果顯示，教育年數不均度對薪資收入不均度有顯著的正向關係，但沒有足夠的證據支持潛在工作年數不均度及調整後的工作經驗不均度對其有顯著的正向影響。同樣被歸類在製造業，但在次產業別間的迴歸結果顯示，不同次產業的薪資不均度的影響因素，存在著差異性。再者，除資訊電子工業之外，以潛在工作年數和實物資本量之乘積當作職場人力資本代理變數的迴歸模型，都具有較高的解釋能力。
參考文獻 一、中文參考文獻
徐美、莊奕琦與陳晏羚 (2015). 台灣家戶所得不均度來源分析初探. 社會科學論叢, 9(1), 1-32.
莊奕琦與李鈞元 (2003). 如何衡量人力資本：理論與台灣實證. 經濟論文叢刊, 31(1). 51-85.
陳建良、曹添旺與林佑龍 (2019). 臺灣個人勞動所得不均度成因之分解. 經濟研究, 55(2), 147-190.
陳建良 (2014). 臺灣家戶所得不均長期變化趨勢之分解. 臺灣經濟預測與政策, 44(2). 1-44.
黃芳玫 (2011). 臺灣人力資本與薪資不均之研究. 臺灣經濟預測與政策, 42(1).1-37.
鄭保志 (2004). 教育擴張與工資不均度：臺灣男性全職受雇者之年群分析. 經濟論文叢刊, 32(2). 233-266.

二、英文參考文獻
Acemoglu, D. (2002). Technical Change, Inequality, and the Labor Market. Journal of
economic literature, 40(1), 7-72.
Acemoglu, D. and Robinson J. (2013). Why nations fail : the origins of power,
prosperity and poverty. New York: Crown Business.
Adachi, H. (2019). Technological progress, income distribution, and unemployment :
theory and empirics. Singapore: Springer Singapore.
Angrist, J., & Acemoglu, D. (1999). How Large are the Social Returns to Education?
Evidence from Compulsory Schooling Laws. NBER Working Paper, No.7444.
Autor, D. H., Katz, L. F., & Kearney, M. S. (2008). Trends in U.S. Wage Inequality:
Revising the Revisionists. The review of economics and statistics, 90(2), 300-323.
Barro, R. J., & Lee, J. W. (1996). International Measures of Schooling Years and
Schooling Quality. The American economic review, 86(2), 218-223.
Becker, G. S. (1962). Investment in Human Capital: A Theoretical Analysis. The
Journal of political economy, 70(5, Part 2), 9-49.
Becker, G. S. (1964). Human Capital: A theoretical and empirical analysis. New
York: Columbia University Press for the National Bureau of Economic Analysis.
Berman, Y., & Shapira, Y. (2017). Revisiting r>g—The Asymptotic Dynamics of
Wealth Inequality. Physica A, 467, 562-572.
Bowman, M. J. (1969). Economics of Education. Review of educational research,
39(5), 641-670.
Breusch, T. S., & Pagan, A. R. (1980). The Lagrange Multiplier Test and its
Applications to Model Specification in Econometrics. The Review of economic
studies, 47(1), 239-253.
Card, D. (2016). The Effect of Unions on Wage Inequality in the U.S. Labor Market.
Industrial & labor relations review, 54(2), 296-315.
Chani, M. I., Jan, S. A., Pervaiz, Z., & Chaudhary, A. R. (2012). Human Capital
Inequality and Income Inequality: Testing for Causality. Quality & Quantity,
48(1), 149-156.
Christelis, D., Georgarakos, D., & Haliassos, M. (2013). Difference in Portfolios
Across Countries: Economic Environment Versus Household Characteristics.
The review of economics and statistics, 95(1), 220-236.
Chuang, Y. C., & Lai, W. W. (2017). Returns to Huamn Capital and Wage Inequality:
The Case of Taiwan. Journal of economic development, 42(3), 61-88.
Conrad, K. (1992). Comment on D.W. Jorgenson and B.M. Fraumeni, "Investment in
Education and U.S. Economic Growth.". The Scandinavian journal of
economics, 94(SUP), 71.
Castello-Climent A. and Domenech R. (2014). Human Capital and Income Inequality:
Some Facts and Some Puzzles. BBVA Research Working paper 12/28.
Dagum, C., & Slottje, D. J. (2000). A New Method to Estimate the Level and
Distribution of Household Human Capital with Application. Structural change
and economic dynamics, 11(1-2), 67-94.
Dagum, C., & Vittadini, G. (1996). Human Capital Measurement and Distributions.
Proceedings of the Business and Economic Statistics Section, American
Statistical Association, 194–199.
Dublin, L. I., & Lotka, A. J. (1930). The money value of a man. Columbia law review,
30(8), 1226-1226.
Engel, E. (1883). Der Werth des Menschen. Berlin: Leonhard Simion.
Farr, W. (1853). Equitable Taxation of Property. Journal of the Royal Statistical
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Földvári, P., & van Leeuwen, B. (2011). Should Less Inequality in Education Lead to
a More Equal Income Distribution? Education Economics, 19(5), 537-554.
Folloni, G., & Vittadini, G. (2011). Human Capital Measurement：a Survey. Journal
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Tchernis, R. (2010). Measuring Human Capital and its Effects on Wage Growth.
Journal of economic surveys, 24(2), 362-387.
Wei, H. (2008). Developments in the Estimation of the Value of Human Capital for
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17(3), 239-270.
描述 碩士
國立政治大學
經濟學系
107258024
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107258024
資料類型 thesis
dc.contributor.advisor 蕭明福zh_TW
dc.contributor.author (Authors) 韓詠翔zh_TW
dc.contributor.author (Authors) Han, Yung-Hsiangen_US
dc.creator (作者) 韓詠翔zh_TW
dc.creator (作者) Han, Yung-Hsiangen_US
dc.date (日期) 2020en_US
dc.date.accessioned 4-Jan-2021 11:21:26 (UTC+8)-
dc.date.available 4-Jan-2021 11:21:26 (UTC+8)-
dc.date.issued (上傳時間) 4-Jan-2021 11:21:26 (UTC+8)-
dc.identifier (Other Identifiers) G0107258024en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/133441-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 經濟學系zh_TW
dc.description (描述) 107258024zh_TW
dc.description.abstract (摘要) 本論文利用民國 92 年到 108 年的人力運用調查資料及經濟部製造業投資營運概況調查之資料，依製造業及其次產業別彙編成追蹤資料，探討台灣製造業之薪資收入不均與人力資本不均之間的關聯性。經由追蹤資料單根檢定，確立研究資料的定態性質，並經由 F 檢定、LM 檢定、及 Hausman 檢定，選出合適的迴歸模型進行資料分析。
對於人力資本的衡量，本論文認為教育程度適切地描述了進入職場以前的人力資本，但潛在工作年數並不足以描述職場階段的人力資本，因為產業之間存在著技術特性的差異，因而提出此階段人力資本的新衡量方式：潛在工作年數與實物資本量之乘積。
本論文實證發現，對整體製造業而言，教育年數不均度、潛在工作年數不均度、及調整後的工作經驗不均度，對薪資收入不均度皆呈現顯著的正向關係。然而，比起以潛在工作年數代理職場人力資本的迴歸模型，用潛在工作年數和實物資本量之乘積當作職場人力資本代理變數的迴歸模型，具有較高的解釋能力。在製造業次產業別裡，民生工業、化學工業以及資訊電子工業的迴歸結果顯示，民生工業與資訊電子工業的薪資收入不均度僅受潛在工作年數不均度和調整後的工作經驗不均度的顯著正向影響，但無足夠證據支持這兩個次產業的薪資收入不均度與教育年數不均度有顯著正向關係。在化學工業方面，其迴歸結果顯示，教育年數不均度對薪資收入不均度有顯著的正向關係，但沒有足夠的證據支持潛在工作年數不均度及調整後的工作經驗不均度對其有顯著的正向影響。同樣被歸類在製造業，但在次產業別間的迴歸結果顯示，不同次產業的薪資不均度的影響因素，存在著差異性。再者，除資訊電子工業之外，以潛在工作年數和實物資本量之乘積當作職場人力資本代理變數的迴歸模型，都具有較高的解釋能力。		zh_TW
dc.description.tableofcontents 第一章 緒論................................................1
第二章 文獻回顧............................................4
第一節 衡量人力資本存量的相關文獻...........................4
第二節 探討人力資本不均與薪資收入不均關聯之相關文獻..........10
第三章 計量方法............................................15
第一節 對資料時間序列性質的處理：追蹤資料單根檢定...........16
第二節 對資料橫斷面性質的處理：模型選定的檢定...............17
第四章 實證模型............................................22
第一節 不均程度的衡量與計算方式............................22
第二節 迴歸模型的被解釋變數與解釋變數之選用.................22
第三節 原始資料來源與變數之計算............................25
第四節 迴歸模型...........................................29
第五章 實證結果............................................33
第一節 敘述性統計.........................................33
第二節 追蹤資料單根檢定....................................37
第三節 模型選定...........................................40
第四節 迴歸結果...........................................45
第六章 結論...............................................52

參考文獻..................................................55		zh_TW
dc.format.extent 1169309 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107258024en_US
dc.subject (關鍵詞) 人力資本zh_TW
dc.subject (關鍵詞) 薪資不均zh_TW
dc.subject (關鍵詞) 固定效果模型zh_TW
dc.subject (關鍵詞) 隨機效果模型zh_TW
dc.subject (關鍵詞) 製造業zh_TW
dc.title (題名) 探討人力資本不均與薪資收入不均之關聯 - 以台灣製造業資料為例zh_TW
dc.title (題名) A study on the relationship between human capital and wage inequality – Using dataset of Taiwan manufacturing sectoren_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 一、中文參考文獻
徐美、莊奕琦與陳晏羚 (2015). 台灣家戶所得不均度來源分析初探. 社會科學論叢, 9(1), 1-32.
莊奕琦與李鈞元 (2003). 如何衡量人力資本：理論與台灣實證. 經濟論文叢刊, 31(1). 51-85.
陳建良、曹添旺與林佑龍 (2019). 臺灣個人勞動所得不均度成因之分解. 經濟研究, 55(2), 147-190.
陳建良 (2014). 臺灣家戶所得不均長期變化趨勢之分解. 臺灣經濟預測與政策, 44(2). 1-44.
黃芳玫 (2011). 臺灣人力資本與薪資不均之研究. 臺灣經濟預測與政策, 42(1).1-37.
鄭保志 (2004). 教育擴張與工資不均度：臺灣男性全職受雇者之年群分析. 經濟論文叢刊, 32(2). 233-266.

二、英文參考文獻
Acemoglu, D. (2002). Technical Change, Inequality, and the Labor Market. Journal of
economic literature, 40(1), 7-72.
Acemoglu, D. and Robinson J. (2013). Why nations fail : the origins of power,
prosperity and poverty. New York: Crown Business.
Adachi, H. (2019). Technological progress, income distribution, and unemployment :
theory and empirics. Singapore: Springer Singapore.
Angrist, J., & Acemoglu, D. (1999). How Large are the Social Returns to Education?
Evidence from Compulsory Schooling Laws. NBER Working Paper, No.7444.
Autor, D. H., Katz, L. F., & Kearney, M. S. (2008). Trends in U.S. Wage Inequality:
Revising the Revisionists. The review of economics and statistics, 90(2), 300-323.
Barro, R. J., & Lee, J. W. (1996). International Measures of Schooling Years and
Schooling Quality. The American economic review, 86(2), 218-223.
Becker, G. S. (1962). Investment in Human Capital: A Theoretical Analysis. The
Journal of political economy, 70(5, Part 2), 9-49.
Becker, G. S. (1964). Human Capital: A theoretical and empirical analysis. New
York: Columbia University Press for the National Bureau of Economic Analysis.
Berman, Y., & Shapira, Y. (2017). Revisiting r>g—The Asymptotic Dynamics of
Wealth Inequality. Physica A, 467, 562-572.
Bowman, M. J. (1969). Economics of Education. Review of educational research,
39(5), 641-670.
Breusch, T. S., & Pagan, A. R. (1980). The Lagrange Multiplier Test and its
Applications to Model Specification in Econometrics. The Review of economic
studies, 47(1), 239-253.
Card, D. (2016). The Effect of Unions on Wage Inequality in the U.S. Labor Market.
Industrial & labor relations review, 54(2), 296-315.
Chani, M. I., Jan, S. A., Pervaiz, Z., & Chaudhary, A. R. (2012). Human Capital
Inequality and Income Inequality: Testing for Causality. Quality & Quantity,
48(1), 149-156.
Christelis, D., Georgarakos, D., & Haliassos, M. (2013). Difference in Portfolios
Across Countries: Economic Environment Versus Household Characteristics.
The review of economics and statistics, 95(1), 220-236.
Chuang, Y. C., & Lai, W. W. (2017). Returns to Huamn Capital and Wage Inequality:
The Case of Taiwan. Journal of economic development, 42(3), 61-88.
Conrad, K. (1992). Comment on D.W. Jorgenson and B.M. Fraumeni, "Investment in
Education and U.S. Economic Growth.". The Scandinavian journal of
economics, 94(SUP), 71.
Castello-Climent A. and Domenech R. (2014). Human Capital and Income Inequality:
Some Facts and Some Puzzles. BBVA Research Working paper 12/28.
Dagum, C., & Slottje, D. J. (2000). A New Method to Estimate the Level and
Distribution of Household Human Capital with Application. Structural change
and economic dynamics, 11(1-2), 67-94.
Dagum, C., & Vittadini, G. (1996). Human Capital Measurement and Distributions.
Proceedings of the Business and Economic Statistics Section, American
Statistical Association, 194–199.
Dublin, L. I., & Lotka, A. J. (1930). The money value of a man. Columbia law review,
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dc.identifier.doi (DOI) 10.6814/NCCU202001857en_US