Angrist, J., Bettinger, E., & Kremer, M. (2006). Long-term educational consequences of secondary school vouchers:Evidence from administrative records in Colombia. The American Economic Review, 96(3), 847-862. Angrist, J. D., & Lavy, V. (1999). Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement.The Quarterly Journal of Economics, 114(2), 533-575. Angrist, J. D., & Steffen, P. J. (2015).Mastering metrics:the path from cause to effect. NJ:Princeton University Press. Borman, G. D. (2009). The use of randomized trials to inform education policy. In Sykes, G.,Schneider, B. & Plank, D. N. (Eds.).Handbook of education policy research (pp. 129-138). New York:Routledge. Cappelleri, J. C., Darlington, R. B., & Trochim, W. M. K. (1994). Power analysis of cutoff-based randomized clinical trials. Evaluation Review, 18(2), 141-152. Card, D. (1999).The Causal Effect of Education on Earnings.In Ashenfelter, O. & Card, D. (Eds.).Handbook of Labor Economics, 3A (pp. 1801-1864). New YorK:Elsevier. Guo, S., & Fraser, M. W. (2010).Propensity score analysis. Thousand Oaks:Sage. Heckman, J. J. (1979). Sample selection bias as a specification error.Econometrica, 47(1), 153-161. Heckman, J. J. (2005). The scientific model of causality.Sociological methodology, 35(1), 1-97. Hoxby, C. M. (2000). The Effects of Class Size on Student Achievement:New Evidence from Population Variation. The Quarterly Journal of Economics, 115(4), 1239-1285. Imbens, G. W., & Angrist, J. D. (1994).Identification and estimation of local average treatment effects.Econometrica, 62(2), 467-475. Imbens, G. W., & Rubin, D. B. (2015).Causal inference in statistics, social, and biomedical sciences:An introduction.New York:Cambridge University Press. Jacob, B. A., & Lefgren, L. (2004). Remedial education and student achievement:A regression-discontinuity analysis. Review of Economics and Statistics, 86(1), 226-244. Kaplan, D. (2009). Causal inference in non-experimental educational policy research.In Sykes, G.,Schneider, B. & Plank, D. N. (Eds.).Handbook of education policy research (pp. 139-153). New York:Routledge. Khandker, S. R., Koolwal, G. B., &Samad, H. A. (2010).Handbook on impact evaluation:quantitative methods and practices. Washington, D. C.:World Bank Publications. Lee, D. S., &Lemieuxa, T. Regression discontinuity designs in economics.Journal of Economic Literature, 48(2), 281-355. Li, H., & Luo, Y. (2004). Reporting errors, ability heterogeneity, and returns to schooling in China. Pacific Economic Review, 9(3), 191-207. Murnane, R. J., & Willett, J. B. (2011).Methods matter:Improving causal inference in educational and social science research. Oxford:Oxford University Press. Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician, 39(1), 33-38. Rubin, D. B. (1986).Which ifs have causal inference. Journal of the American Statistical Association, 81, 961-962. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002).Experimental and quasi-experimental designs for generalized causal inference. Boston:Houghton, Mifflin and Company. Smith, W. C. (2014). Estimating unbiased treatment effects in education using a regression discontinuity design. Practical Assessment, Research & Evaluation, 19(9), 2. Thistlethwaite, D. L., & Campbell, D. T. (1960). Regression-discontinuity analysis:An alternative to the ex post facto experiment. Journal of educational Psychology, 51(6), 309. Trochim, W. M. K. (1984). Research design for program evaluation:the regression-discontinuity approach. CA:Sage. 黄斌,钟晓琳. (2012). 中国农村地区教育与个人收入——基于三省六县入户调查数据的实证研究. 教育研究, (3),18-26. 黄斌,汪栋.(2016).中国义务教育财政投入的回顾与展望.华中师范大学学报:人文社会科学版, 55(4),154-161. 黄斌,苗晶晶,金俊. (2016)."新机制"改革对农村中小学公用经费的因果效应分析——基于准实验研究设计(工作论文). 南京:南京财经大学公共财政研究中心. |