:::

詳目顯示

回上一頁
題名:教育報酬、工資不均與異質性人力資本的研究
作者:賴偉文
校院名稱:國立政治大學
系所名稱:經濟研究所
指導教授:莊奕琦
學位類別:博士
出版日期:2008
主題關鍵詞:教育報酬分量迴歸人力資本投資工具變數異質性比較利益
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(1)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:55
隨著理論與實證方法的發展,人力資本報酬的異質性已被國內外學者所重視,因此,本論文採取將人力資本視為異質性的觀點,首先以分量迴歸模型估計不同工資分配下教育的邊際報酬率,呈現人力資本投資在不同工資水準下的異質性,並進一步探討台灣地區工資不均的成因。實證結果發現,若增加對教育的投資將有助於降低勞動市場的工資不均度,而工作經驗的累積則將會擴大工資的不均度。此外,若增加勞動市場高教育程度與(或)女性工作者的比例,將有助於改善工資的不均度,但若勞動市場上高經驗年數之工作者所占的比例愈高,則對工資不均度將有不利的影響。
而為了避免因選擇橫斷面資料分析時所可能產生的偏誤與不一致,本論文以年群世代的資料進一步描述學校教育品質的時間變化,體現教育的品質與內涵。發現過去較年長世代所接受之教育的效果,乃在於加強個人的能力,深化個人專業能力進而表現在工資水準上。而年輕世代所接受之現代教育的效果,則在於補足個人能力的不足之處,表示在年輕的世代中,教育乃做為培養多元或多樣化能力的途徑,彌補先天能力的異質性,更突顯教育於二十一世紀之人力資本投資的重要性。
另外,本論文並考慮人力資本投資的內生性,以工具變數法呈現特殊群組的異質性教育報酬率,並解決可能產生的內生性偏誤估計。結果發現,以工具變數法所估計教育報酬率,均高於傳統OLS所估計的教育報酬率。且透過不同工具變數的選擇與結合,經由多重判斷標準,可得到對平均教育報酬率較有效的一致性估計。我們發現男性與女性教育報酬率分別為5.97%與14.69%,顯示傳統OLS估計的女性教育報酬率存在嚴重的低估現象。
最後以異質性教育報酬率模型估計個人教育決策的選擇結果所造成之異質性教育報酬率。估計的結果發現,若忽略異質性與選擇偏誤的重要性,將導致估計參數的偏差與不一致。而由邊際處置效果MTE曲線發現,愈有可能進入大學就讀的人,有愈高的教育報酬,顯示勞動市場存在比較利益,而遞減的MTE曲線更進一步指明,樣本在教育選擇過程中存在未觀測到的異質性,也更確切地顯示勞動市場中人力資本的異質性與比較利益原則的存在。
行政院主計處,《中華民國台灣地區人力運用調查報告》,台北,行政院主計處。
吳慧瑛 (2000),「二十年來教育發展之經濟評估, 1978-2001」,《台灣經濟預測與政策》33,97-130。new window
張宏基與朱敬一 (1996),「用Pseudo Panel Data估計台灣男性跨期勞動替代彈性」,《經濟論文叢刊》,24(3),313-337。
符碧真 (1996),「教育投資報酬率長期變化之剖析-以我國發展個案為例」,《教育研究資訊》,4,,82-89。new window
陳建良與管中閔 (2006),「台灣工資函數與工資性別歧視的分量迴歸分析」,《經濟論文》,34(4),435-468。
黃台心 (2000),「我國已婚婦女勞動供給的生命循環分析」,《經濟論文叢刊》28(1),1-24。new window
鄭保志 (2004a),「教育擴張與工資不均度:台灣男性全職受雇者之年群分析」,《經濟論文叢刊》,32(2),233-265。new window
鄭保志 (2004b),「工資流動性與終身不均度的年群分析」,《經濟論文叢刊》,32(3),369-393。new window
Ammermüller, A., and A. M. Weber, (2003), “Education and Wage Inequality in Germany: A Review of the Empirical Literature,” Discussion Paper No. 03-29, Centre for European Economic Research.
Angrist, J. D., and A. B. Krueger (1991), “Does Compulsory Schooling Attendance after Schooling and Earning?” Quarterly Journal of Economics, 106(4), 979-1014.
Arcand, J. L., B. D’hombres, and P. Gyselinck (2004), “Instrument Choice and the Returns to Education: New Evidence from Vietnam,” Economics Working Paper Archive at WUSTL, 0510011.
Arias, O., K. F. Hallock, and W. Sosa-Escudero (2001), “Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data,” Empirical Economics, 26(1), 7-40.
Ashenfelter, O., and A. B. Krueger (1994), “Estimates of the Economic return to Schooling from a New Sample of Twins,” American Economic Review 84(5), 1157-1173.
Barro, R. J., and X. Sala-i-Martin (1995), Economic Growth, Cambridge, MA: MIT Press.
Benhabib, J., and M. M. Spiegel, (1994), “The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data,” Journal of Monetary Economics, 34, 143-161.
Berman, E., J. Bound, and S. Machin, (1998), “Implications of Skill-Biased Technological Change: International Evidence,” Quarterly Journal of Economics, 113, 1245-1279.
BJorklund, A., and R. Moffitt (1987), “The Estimation of Wage Gains and Welfare Gains in Self-Selection Model?” Review of Economics and Statistics, 69, 42-49.
Blau, F., and L. Kahn, (1992), “The Gender Earnings Gap: Some International Evidence,” NBER Working Paper No. 4224, NBER.
Bound J., D. A. Jaeger, and R. Baker (1995), “Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak,” Journal of the American Statistical Association, 90, 443-450.
Bronars, S. G., and G. S. Oettinger (2006), “Estimates of the Return to Schooling and Ability: Evidence from Sibling Data,” Labour Economics, 13(1), 19-34.
Buchinsky, M. (1994), “Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression,” Econometrica, 62, 405-458.
Buchinsky, M. (1995), “Quantile Regression, Box-Cox Transformation Model, and U.S. Wage Structure 1963-1987,” Journal of Econometrics 65(1), 109-154.
Buchinsky, M. (1998), “The Dynamics of Changes in the Female Wage Distribution in the USA: A Quantile Regression Approach,” Journal of Applied Econometrics, 13, 1-30.
Buchinsky, M. (2001), “Quantile Regression with Sample Selection: Estimating Women’s Return to Education in the U.S.,” Empirical Economics, 26(1), 87-113.
Card, D. (1999), “The Causal Effect of Education on Earnings,” In Ashenfelter, O. and D. Card, (eds) Handbook of Labor Economics, Volume 3A, Amsterdam: Elsevier.
Card, D. (2001), “Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems,” Econometrica 69(5), 1127-1160.
Carneiro, P., and J. Heckman (2002), “The Evidence on Credit Constraints in Post-Secondary Schooling,” Economic Journal, 112, 705-734.
Carneiro, P., J. Heckman, and E. Vytlacil (2001), “Estimating the Return to Education When It Varies Among Individuals,” Working Paper, University of Chicago.
Chen, B. L., and M. Hsu, (2001), “Time-Series Wage Differential in Taiwan: the Role of International Trade,” Review of Development Economics, 5, 336–354.
Chuang, H. L., and E. S. Lin (2007), “Gender wage Gaps by Industry in Taiwan: Evidence from 1978-2003 Manpower Utilization Survey,” paper presented at 2007 Conference for Labor Economics, National Central University, Hsinchu, Taiwan.
Chuang, Y. C. (1999), “The Role of Human Capital in Economic Development: Evidence from Taiwan,” Asian Economic Journal, 13, 117-144.
Chuang, Y. C. and C. Y. Chao, (2001), “Educational Choice, Wage Determination, and Rates of Return to Education in Taiwan,” International Advances in Economic Research, 7, 479-504.
Cruz, L. M., and M. J. Moreira (2005), “On the Validity of Econometric Techniques with Weak Instruments: Inference on Returns to Education Using Compulsory School Attendance Laws,” Journal of Human Resources, 40 (2), 393–410.
Davidson, R., and J. G. MacKinnon (2003), Econometric Theory and Methods, Oxford, UK: Oxford University Press.
Deaton, A. S., and C. H. Paxon (1994), “Saving, Growth and Aging in Taiwan,” in David A. Wise (ed.), Studies in the Economics of Aging, 331-361, Chicago: University of Chicago Press
Donald, S., and W. Newey (2001), “Choosing the Number of Instruments,” Econometrica, 69(5), 1161-1191.
Duflo, E. (1999), “Schooling and Labor Market Consequences of Schooling in Indonesia: Evidence from an Unusual Policy Experiment,” Mimeo, Department of Economics, MIT
Durbin, J. (1954), “Error in Variables,” Review of the International Statistical Institute, 22, 23-32.
Eide, E., and M. H. Showalter (1998), “The Effect of School Quality on Student Performance: A Quantile Regression Approach,” Economics Letters, 58, 345-350.
Fersterer, J., and R. Winter-Ebmer (2003), “Are Austrian Return to Education Falling Over Time?” Labour Economics, 10(1), 73-89.
Garcia, J., P. Hernandez, and A. L’opez-Nicolas (2001), “How Wide Is the Gap? An Investigation of Gender Wage Difference Using Quantile Regression,” Empirical Economics, 26, 149-167.
Gindling, T. H., M. Goldfarb, and C.C. Chang (1995), “Changing Return to Education in Taiwan,” World Development, 23(2), 343-356.
Gonzalez, X., and D. Miles, (2001), “Wage Inequality in a Developing Country: Decrease in Minimum Wage or Increase in Education Returns,” Empirical Economics, 26(1), 135-148.
Griliches, Z. (1977), “Estimating the Return to Schooling: Some Econometric Problems,” Econometrica, 45(1), 1-22.
Hamermesh, D. S. (2005), “Four Questions on the Labor Economics of Higher Education,” manuscript, University of Texas at Austin.
Hansen L. P. (1982), “Large Sample Properties of Generalized Method of Moments Estimators,” Econometrica, 45, 1-22.
Harmon, C. and I. Walker (1995), “Estimates of the Economic Return to Schooling for the UK,” American Economic Review, 85, 1279-1286.
Harmon, C., H. Oosterbeek, and I. Walker (2003), “The Returns to Education: Microeconomics,” Journal of Economic Surveys, 17(2), 115-155.
Hartgo, J., P. T. Pereira, and J. A. Vieira (2001), “Changing Return to Education in Portugal during the 1980s and Early 1990s: OLS and Quantile Regression Estimators,” Applied Economics, 33(8), 1021-1037.
Hausman J. (1978), “Specification Test in Econometrics,” Econometrica, 46(3), 262-280.
Haveman, R., and B. Wolfe (1995), “The Determinants of Children’s Attainments: A Review of Methods and Findings,” Journal of Economic Literature, 33, 1829-1878.
Heckman, J. J., and E. Vytlacil (1999), “Local Instrumental Variable and Latent Variable Models for Identifying and Bounding Treatment Effects,” Proceedings of the National Academy of Sciences, 96, 4730-4734.
Heckman, J. J. (1997), “Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations,” Journal of Human Resources, 32(3), 441-462.
Heckman, J. J., and E. Vytlacil (2000), “Local Instrumental Variables,” in C. Hsiao, K. Morimune, and J. Powells, (eds), Nonlinear Statistical Modeling: Proceedings of the Thirteenth International Symposium in Economic Theory and Econometrics: Essays in Honor of Takeshi Amemiya, Cambridge: Cambridge University Press, 1-46.
Heckman, J. J., and S. Navarro-Lozano (2003), “Using Matching, Instrumental Variables and Control Functions to Estimate Economic Choice Models,” NBER Working Papers #9497.
Heckman, J. J. (1979), “Sample Selection Bias as a Specification Error,” Econometrica, 47(1), 153-161.
Heckman, J. J. (2000), “Policies to Foster Human Capital," Research in Economics, 54, 3-56.
Heckman, J. J. (2003), “China’s investment in Human Capital,” Economic Developemnt and Cultural Change, 795-804.
Heckman, J. J., L. J. Lochner, and P. E. Todd (2003), “Fifty Teatrs of Mincer Earnings Regressions,” Working Paper 9732, National Bureau of Economic Research, Cambridge, MA.
Heckman, J. J., L. Lochner, and C. Taber, (1998), “Explaining Rising Wage Inequality: Explorations with a Dynamic General Equilibrium Model of Labor Earnings with Heterogeneous Agents,” Review of Economic Dynamics, 1(1), 1-58.
Heckman, J. J., R. J. Lalonde, and J. A. Smith (1999), “The Economics and Econometrics od Active Labor Market Programs,” In Ashenfelter, O. and D. Card, (eds) Handbook of Labor Economics,Volume 3A, Amsterdam: Elsevier.
Heckman, J. J., and X. Li (2003), “Selection Bias, Comparative Advantage and Heterogeneous Return to Education,” NBER Working Papers: #9877.
Koenker, R. (2005), Quantile Regression, Cambridge, New York: Cambridge University Press.
Koenker, R., and G. J. Bassett (1978), “Regression Quantiles,” Econometrica, 46, 33-50.
Koenker, R., and K. F. Hallock (2001), “Quantile Regression,” Journal of Economic Perspectives, 15, 143-156.
Lin, C. H., and P. F. Orazem (2003), “Wage Inequality and Returns to Skill in Taiwan, 1978-1996,” Journal of Development Studies, 39, 89-108.
Lin, C. H., and P. F. Orazem (2004), “A Reexamination of the Time Path of Wage Differentials in Taiwan,” Review of Development Economics, 8, 295-308.
Machado, J. and J. Mata (2005), “Counterfactual Decomposition of Changes in Wage Distributions Using Quantile Regression,” Journal of Applied Economics, 20, 445-465.
Martin, P. S., and P. T. Pereira, (2004), “Does Education Reduce Wage Inequality? Quantile Regression Evidence from 16 Countries,” Labour Economics, 11, 355-371.
Mincer, J. (1974), Schooling, Experience an Earning, New York: Columbia University Press.
Moretti, E. (2004), “Estimating the Social Return to Higher Education: Evidence from Longitudinal and Repeated Cross-Sectional Data,” Journal of Econometrics, 121(1-2), 175-212.
Mwabu, T., and T. P. Schultz (1996), “Education Return Across Quantiles of the Wage Function: Alternative Explanation for Education by South Africa,” American Economic Review, 86(2), 335-339.
O'Neill, J., and S. Polachek (1993), “Why the Gender Gap in Wages Narrowed in the 1980s,” Journal of Labor Economics, 11, 205-28.
Patrinos, H., and C. Sakellariou (2005), “Schooling and Labor Market Impacts of a Natural Policy Experiment,” Labour, 19(4), 705-719.
Psacharopouls, G. (1985), “Return to Education: A Further International Update and Implications,” Journal of Human Resources, 20(4), 583-604.
Roy, A. (1951), “Some Thoughts on the Distribution of Earnings,” Oxford Economic Papers, 31, 831-880.
Saavedra, L. A. (2001), “Female Wage Inequality in Latin American Labor Markets,” Policy Research Working Paper Series No. 2741, the World Bank.
Sakellariou, C. (2006), “Education Policy Reform, Local Average Treatment Effect and Returns to Schooling from Instrumental Variables in the Philippines,” Applied Economics, 38, 473-481.
Sargen, J. (1958), “The Estimation of Economic Relationships Using Instrumental Variables,” Econometrica, 26(3), 393-415.
Schultz, T. W. (1975), “The Value of the Ability to Deal with Disequilibria,” Journal of Economic Literature, 13, 827-846.
Steiger, D., and J. H. Stock (1997), “Instrumental Variables Regression with Weak Instruments,” Econometrica, 65(3), 557-586.
Stock, J. H., and M. W. Watson (2007), Introduction to Econometrics, 2nd ed., Boston: Person Education.
Thomas, D., J. Strauss, and M. H. Henriques (1991), “How Does Mother’s Education Affect Child Height?” Journal of Human Resources, 26, 183-211.
Trostel P., I. Walker, and P. Woolley (2002), “Estimates of the Economic Return to Schooling for 28 Countries,” Labour Economics, 9(1), 1-16.
Willis, R. (1986), “Wage Determinants: A Survey and Reinterpretation of the Human Capital Earning Function,” in O. Ashenfelter and R. Layard (eds), Handbook of Labor Economics, 525-602, Amsterdam, North-Halland: Elsevier.
Willis, R., and S. Rosen (1979), “Education and Self-Selection,” Journal of Political Economy, 87(5), Pt2, S7-36.
Wu, D. (1973), “Alternative Tests of Independence between Stochastic Regressors and Disturbances,” Econometrica, 41, 733-750.
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關著作
 
QR Code
QRCODE