臺灣博碩士論文加值系統

本文的研究目的，主要利用台灣地區於1994與2004年的資料，探討男性及女性工資的變化及其原因。我們利用Machado與Mata(2005)提出的方法，結合分量迴歸法(Quantile Regression) 與假設性陳述分析法(counterfactual analysis)，將工資分配之變化分解為兩個部份：第一個部份為迴歸係數的改變所造成的影響，第二個部分則為解釋變數本身分配改變所造成的變化，進而探討影響男女工資結構變化的因素。在本文的實證分析中，分量迴歸的估計結果與Buchinsky(1994)、Plotnick(1982)及Chiswick與Mincer(1991)等研究一致，皆顯示年齡及教育程度會對工資分配有較大的影響，但藉由假設性陳述分析法及進行工資分解後，我們進一步發現影響男性工資分配不均的主因為迴歸係數的變動，而女性變為解釋變數本身分配改變的影響較大。我們更進一步模擬單一變數分配改變下，工資分配的變化，結果顯示，因為受教育年數、年齡及工作經驗的分配於這十年間有明顯的改變，因而對工資分配不均的影響也相對較大，且女性工資受解釋變數分配改變影響的程度較男性為大。

The goal of this thesis is to investigate the change of wage structure of male and female in Taiwan during 1994 to 2004. We use the approach proposed by Machado and Meta (2005) to decompose the change of male and female wage structure into two parts: The first part is caused by the change of the regression coefficients, which measures the direct impacts of the covariates on wage. The second part results from the changes of the distributions of the covariates over the period. Our empirical results show that, among all the variables investigated in this study, age and education have relatively more significant effects on wage distribution, which is consistent with the findings of Buchinsky(1994)、Plotnick(1982) and Chiswick and Mincer(1991), etc. Furthermore, with an application of counterfactual analysis we find that the change in male wage inequality is mainly from the direct effect of changing in the regression coefficients, but on the contrary most of the change in female wage inequality can be explained by the changes in the distributions of all covariates. In particular, distributions of education years, age structure, and working experience are the crucial factors in accounting for wage inequality during the past ten years.

目 錄
第一章 緒論
第一節 研究動機與目的……………………………………… 1
第二節 研究方法與步驟……………………………………… 2
第三節 研究架構……………………………………………… 3
第二章 文獻回顧
第一節 工資差異……………………………………………… 4
第二節 假設性陳述分析法及分量迴歸………………………10
第三節 本章小結………………………………………………12
第三章 理論模型…………………………………………………13
第四章 計量模型與方法
第一節 分量迴歸………………………………………………15
第二節 假設性陳述分析法……………………………………17
第五章 資料分析
第一節 資料來源及處理………………………………………24
第二節 變數說明及符號………………………………………25
第三節 資料敘述統計…………………………………………28
第四節 本章小結………………………………………………38
第六章 實證結果
第一節 分量迴歸的估計結果………………………………… 39
第二節 假設性陳述法分析結果……………………………… 46
第三節 本章小結……………………………………………… 54
第七章 結論與建議
第一節 研究結論……………………………………………… 55
第二節 政策建議與未來方向………………………………… 56
參考文獻………………………………………………………… 58






表 目 錄
表2.1 工資差異文獻回顧………………………………………… 7
表5.1 變數之定義………………………………………………… 28
表5.2 工資之四分位數與第10及90分位數……………………… 29
表5.3 敘述統計…………………………………………………… 31
表5.4 資料分組方式……………………………………………… 33
表5.5 各解釋變數之分組比例…………………………………… 37
表6.1 係數估計值………………………………………………… 43
表6.2 男性工資分配之分解……………………………………… 47
表6.3 女性工資分配之分解……………………………………… 48





圖 目 錄
圖4.1 實證分析架構圖…………………………………………… 23
圖5.1 男性工資密度函數………………………………………… 30
圖5.2 女性工資密度函數………………………………………… 30
圖5.3 男性年齡之密度函數……………………………………… 34
圖5.4 女性年齡之密度函數……………………………………… 34
圖5.5 男性年資之密度函數……………………………………… 35
圖5.6 女性年資之密度函數……………………………………… 35
圖5.7 男性工作經驗之密度函數………………………………… 36
圖5.8 女性工作經驗之密度函數………………………………… 36
圖6.1 分量迴歸係數估計圖……………………………………… 42
圖6.2 單一變數分配改變下模擬之工資密度函數……………… 52

一、中文部份：
江豐富(1995),「以文憑還是以人力資本取才：台灣地區實證研究」,《教育研究資訊》, 5, 17-35。
吳忠吉(2003),「勞動結構變遷與社會安全制度」,《國家政策季刊》, 4, 23-52。
吳惠林(1988),「專上人力勞動報酬的決定因素：台灣實證分析」,《經濟論文叢刊》357-369。
阮國強(1996),「工資相關理論之文獻回顧」,《勞工研究季刊》, 128, 25-44。
邱曉培(1996),「台灣地區工資的性別差異」, 《勞工研究季刊》, 122, 43-85。
苗坤齡(1989),「初入勞動市場之工資差異：台灣專上畢業生之調查分析」,《中華經濟研究院經濟專論》, 130。
莊奕琦、李均元(2003), 「如何衡量人力資本：理論與台灣實證」, 《經濟叢刊》, 31, 51-85。





二、英文部分：
Blau, F. and L. Kahn (1996), “International differences in male wage inequality: institutions versus market forces,” Journal of Political Economy, 104, 791-837.
Buchinsky, M. (1994), “Changes in the U.S. wage structure 1963-1987: an application of quantile regression,” Econometrica, 62, 405-458.
Buchinsky, M. (1998), “The dynamics of change in the female wage distribution in the USA: a quantile regression approach,” Journal of Applied Economics, 13, 1-30.
Card, D. (1994), “Earnings, schooling, and ability revisited,” National Bureau of Economic Research Working Paper No. 4832.
Chiswick, B. R. and J. Mincer （1972）, “Time-Series in personal income inequality in the United States from 1939 with Projections to 1985,” Journal of Political Economy, 3, S34-S36.
DiNardo, J., N. Fortin, and T. Lemieus (1996), “Labor Market Institutions and the distribution of wages, 1973-1992: a semi parametric approach,” Econometrica, 64, 1001-1044.
Donald, S., D. Green, and H. Paarsch (2000), “Differences in the wage distributions between Canda and the United States: an application of a flexible estimator of the distribution function in the presence of covariates,” Review of Economic Studies, 67, 609-633.

Fitzenberger B., and C. Kurz(2003), “New insights on earnings trends across skill groups and industries in West Germany,” Empirical Economics, 28, 479-514.
Fortin, N., and T. Lemieux (2000), “Rank regressions, wage distributions, and the gender gap,” Journal of Human Resources, 8, 610-643.
Gannicott, K. (1986), “Women, wages, and discrimination: some evidence from Taiwan,” Economic Development and Culutral Change, 34, 721-730.
Gonzalex, X. and D. Miles (2001), “Wage inequality in a developing country: decrease in minimum wage or increase in education returns,” Empirical Economics, 26, 135-148.
Heckman, J. J. H. and J. Edward (1999), “Local instrumental variables and latent variable models for identifying and bounding treatment effects,” Proceedings of the National Academy of the United States of America, 96, 4730-4734.
Heckman, J. J. H. (1999), “Sample selection bias as a specification error,” Econometrica, 47, 153-162.
Hirsch, B. T. (1978), “Earnings inequality across labor markets: a test of the human capital model,” Southern Economic Journal, 1, 32-45.
Jacques V. D. G and W. Vijverberg(1998), “A switching regression model for wage determinants in the public and private sectors of a developing country,” Review of Economics and Statistics, 70, 244-252.

Juhn, C., M. Kevin and P. Brooks, “Wage inequality and the rise in returns to skill,” Journal of Political Economy, 101, 410-442.
Koenker, R. and G. Bassett (1978), “Regression Quantiles,” Econometrica, 46, 33-50.
Koenker, R. and G. Bassett (1982), “An empirical Quantile function for linear models with iid errors,” Journal of the American Statistical Association, 77, 407-415.
Machado, J.A.F and J. Mata (2005), “Counterfactual decomposition of changes in wage distributions using quantile regression,” Journal of Applied Econometrics, 20, 445-465.
Mincer, J. (1974), Schooling, experience, and earnings, New York: Columbia University Press.
Morillo, D. S. (2000), “Monte Carlo American option pricing with nonparametric regression,” Essays in Nonparametric Econometrics, Dissertation, University of illinois.
Nielsen, H. and M. Rosholm (2001), “The public-private sector wage gap in Zambia? A quantile regression approach,” Empirical Economics, 26, 169-182.
Oaxaca, R. (1973), “Male-female wage differentials in urban labor markets,” International Economic Review, 14, 693-709.
Petersen T. and A. M. Laurie (1995), ”Separate and unequal occupation-establishment sex segregation and the gender wage gap,” American Journal of Sociology, 101, 329-365.
Psacharopoulos, G.. and V. Educardo(1981), “Returns to education: an update international comparison,” Comparative Education, 17, 321-341.
Robert D. P.(1982), “Trends in male earnings inequality, ” Southern Economic Journal, 48, 724-732.
Wood, R. G., M. E. Corcoran and P. N. Courant (1993), “Pay differences among the highly paid: The male-female earnings gap in lawyers’ salaries,” Journal of Labor Economics, 11, 417-44.