Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/27915
標題: 以分量迴歸方法在政府規模、工資不均與學習成就之應用
Three Applications of Quantile Regression Approach on Government Size, Wage Inequality and Educational Achievement
作者: 陳盛通
Chen, Sheng Tung
關鍵字: Quantile regression
分量迴歸
Government size
Wage inequality
Educational achievement
政府規模
工資不均
學習成就
出版社: 應用經濟學系所
引用: Chapter 1 references AmirKhalkhali, S., and Atul A. Dar. 1995. A varying-coefficients model of export expansion, factor accumulation, and economic growth. Economic Modelling 12(4): 435-441. Baltagi, Badi H. 1995. Econometric Analysis of Panel Data. John Wiley and Sons Ltd. Barro, Robert J. 1990. Government spending in a simple model of endogenous growth. Journal of Political Economy 98: S103-S125. Bilias, Y., S. Chen, and Z. Ying. 2000. Simple resampling methods for censored regression quantiles. Journal of Econometrics 99: 373-386. Chen, S. T., and C. C. Lee. 2005. Government size and economic growth in Taiwan: A threshold regression approach. Journal of Policy Modeling 27: 1051-1066. Conte, Michael A., and Ali F. Darrat. 1988. Economic growth and the expanding public sector: A reexamination. The Review of Economics and Statistics 70(2): 322-330. Dar, Atul A., and S. AmirKhalkhali. 1999. On the impact of government size on the economic growth: A time series cross-country study. Development Policy Review 17: 65-76. Dar, Atul A., and S. AmirKhalkhali. 2002. Government size, factor accumulation, and economic growth: evidence from OECD countries. Journal of Policy Modeling 24: 679-692. Easterly, W., and S. Rebelo. 1993. Fiscal policy and economic growth: An empirical investigation. Journal of Manetary Economics 32: 417-458. Fatás, A., and I. Mihov. 2001. Government size and automatic stabilizers: international and intranational evidence. Journal of International Economics 55: 3-28. Fölster, S., and M. Henrekson. 2001. Growth effects of government expenditure and taxation in rich countries. European Economic Review 45: 1501-1520. Ghali, Khalifa H. 1998. Government size and economic growth: evidence from a multivariate cointegration analysis. Applied Economics 31: 975-987. Hahn, J. 1995. Bootstrapping quantile regression models. Econometric Theory 11: 105-121. Hansen, Bruce E. 1999. Threshold effects in non-dynamic panels: Estimation, testing, and inference. 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Applied Statistics 36: 383-393. Powell, James L., 1991. Estimation of Monotonic Regression Models under Quantile Restrictions, in Nonparametric and Semiparametric Methods in Econometrics (ed. by W. Barnett, J. Powell, and G. Tauchen), Cambridge: Cambridge University Press. Mincer, J. 1974. Schooling, Experience and Earnings. New York: National Bureau of Economic Research. Mwabu, G. and Schultz, P. T. 1996. Education Returns Across Quantiles of the Wage Fumction: Alternative Explanations for Returns to Education by Race in South Africa. American Economic Review Papers and Proceedings 86: 335-339. Chapter 3 references Bilias, Y., S. Chen, and Z. Ying. 2000. Simple Resampling Methods for Censored Regression Quantiles. Journal of Econometrics 99, 373-386. Borg, M. O., P. M. Mason and S. L. Shapiro. 1989. The Case of Effort Variables in Student Performance. Journal of Economic Education 20(3), 308-313. Caldas, S. J. and C. Bankston III. 1997. Effect of School Population Socioeconomic Status on Idividual Academic Achievement. Journal of Educational Research 90(5), 43-55. Coleman, J. C., Campbell, E. Q., Hobson, C. J., McPartland, J., Mood, A. M., Weinfeld, F. D. and R. L. York. 1966. Equality of educational opportunity. Washington, DC: U.S. Government Printing Office. Deller, S. C.and E., Rudnicki. 1993. Production Efficiency in Elementary Education: The Case of Maine Public Schools. Economics of Education Review 12(1), 45-57. Eide, E., and M. Showalter. 1998. The Effect of School Quality on Student Performance: A Quantile Regression Approach. Economics Letters 58, 345-350. Goldhaber, D. D. 1996. Public and Private High Schools: Is School Choice an Answer to the Productivity Problem? Economics of Education Review 15(2), 93-109. Hendricks, W., and R. Koenker. 1991. Hierarchical Spline Models for Conditional Quantiles and the Demand for Electricity. Journal of the American Statistical Association 87, 58-68. Koenker, R. 2005. Quantile Regression. Cambridge University Press. Koenker, R., and G. Bassett. 1978. Regression Quantiles. Econometrica 46, 33-50. Koenker, R., and V. d'Orey. 1987. Computing Regression Quantiles. Applied Statistics 36: 383-393. Levin, J. 2001. For Whom the Reductions Count: A Quantile Regression Analysis of Class Size and Peer Effects on Scholastic Achievement. Empirical Economics 26, 221-246. McEwan, P. J. 2003. Peer Effects on Student Achievement: Evidence from Chile”, Economics of Education Review 22, 131-141. Okpala, C.O., A.O. Okpala and F.E. Smith. 2001. Parental Involvement, Instructional Expenditures, Family Socioeconomic Attributes, and Student Achievement. Journal of Educational Research 95(2), 110-115. Powell, J. L. 1991. Estimation of Monotonic Regression Models under Quantile Restrictions, in Nonparametric and Semiparametric Methods in Econometrics (ed. by W. Barnett, J. Powell, and G. Tauchen), Cambridge: Cambridge University Press. Robertson,D. and J. Symons. 2003. 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摘要: Koenker and Hallock (2001)指出分量迴歸方法可以視為傳統條件最小平方估計方法的衍生,而近年來亦有大量的研究以此分量迴歸的方法進行分析,例如Chamberlain(1994)及Buchinsky(1994)即利用分量迴歸的方法探討勞動經濟學上的研究,而Arias et al.(2001)更利用此方法於教育成就分析上。而分量迴歸可以讓變數間的關係超越了傳統的條件平均的概念。本研究第一部份即結合分量迴歸與縱橫資料的概念,建立一個以分量迴歸處理縱橫資料時的方法來檢視政府規模與經濟成長之間的關係,而發現政府規模效果在不同經濟成長分量點時的效果是有差異的,當經濟成長相對較差時,擴大政府規模會有正效果,但當經濟成長較好時,此效果卻相反。 此外,本研究的第二部份利用分量迴歸的方法檢視台灣從1991年至2006年間教育擴張政策是否會影響不同分量工資的人之教育邊際報酬,而我們發現台灣工資不均與教育邊際報酬是相關的。而相對低工資的族群,其教育邊際報酬相對較低,而教育擴張政策反而讓低工資族群受到影響較大。另外,本文第三部份則利用2005年針對全台灣309所高級中學學校發出問卷調查當年度高一新生2004年時的國中基本學力測驗的分數來進行教育生產函數的估計,而估計方法除了利用傳統的Probit two stage least square來進行內生變數的處理並利用分量迴歸來檢視因變數的條件分配中不同分量的行為,結果發現,城鄉差距對高分群的影響小於中上成績的族群,而也顯示城鄉差距對中上成績者的影響最大,能力分班與否對學測成績的影響並不明顯,家庭因素在對學生學習成就中的影響具有絕對影響力,在家庭教育支出上,低分群中,增加教育支出對其學測成績的效果較為顯著,而分數越高的群體,其效果則相對而言較不顯著而針對學生個人學習因素上。
As Koenker and Hallock (2001) indicate that quantile resression may be viewed as a natural extension of classical least squares estimation of conditional mean models to the estimation of an ensemble of models for conditional quantile functions. Recently, large researches have pay attention to this econometric method. For instance, there are a lot of empirical quantile regressions researches in labor economics (Chamberlain, 1994; Buchinsky, 1994) and educational achievement analysis (Arias et al., 2001). The relationship between variables can go beyond models for conditional mean while the quantile regression can be considered. If the estimation of quantile regression with panel data can be defined clearly, the empirical research with short data span can be solved. So, the empirical models which apply quantile regression can estimate the result with panel data. The problems of using quantile regression to estimate and compare the robust of the estimation of panel data quantile regression analysis will be identified. Therefore, I firstly applied the issue to an empirical investigation on the relationship between economic growth and government size in OECD countries as the first part of the dissertation. We find that the effect magnitude of government size to economic growth varies through quantiles. When the economic growth is low, increasing its government size may have positive effect and stimulate economic growth. Secondly, I will use the Manpower Survey data in Taiwan to examine the returns on schooling in Taiwan from 1991 to 2006 as the second part of my dissertation. It is found that wage inequality is associated with the returns to education in Taiwan. Besides, the marginal returns to education change with time much slighter in lower quantiles than higher quantiles and returns to education in higher quantile wage distribution group have an increase trend from 1991 to 2003 but the trend is inversed in lower quantiles after 2000. Finally, the original quantile regression methodology is applied into analyze the factors which affect the score of Basic Competence Test for Junior High School Students of Taiwan in 2005. It is found that the difference between urban and country affects the relative higher score group much more than other one. And the family factor has the vital effect on the educational achievement. Besides, increasing educational expenditure can improve the performance more in the relative lower achievement ones than the other ones.
URI: http://hdl.handle.net/11455/27915
其他識別: U0005-2106200709375500
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