Evaluating education programs that have lotteried admission and selective attrition

Journal of Labor Economics

Volumn 32, Issue 1, 2014, Pages 27-63

  Engberg, John ^a   Epple, Dennis ^b   Imbrogno, Jason ^b   Sieg, Holger ^c   Zimmer, Ron ^d  

^a RAND CORPORATION   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c UNIVERSITY OF PENNSYLVANIA   (United States)

^d VANDERBILT UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84889666526     PISSN: 0734306X     EISSN: None     Source Type: Journal    
DOI: 10.1086/671797     Document Type: Article

References (45)

1. Abadie, Alberto, and Guido Imbens. 2006. Large sample properties of matching estimators for average treatment effects. Econometrica 74, no. 1: 235-67.
2. Abdulkadiroglu, Abdulah, Joshua Angrist, Susan Dynarski, Thomas Payne, and Parak Pathak. 2009. Accountability and flexibility in public schools: Evidence from Boston's charters and pilots. Working Paper no. 15549, National Bureau of Economic Research, Cambridge, MA.
3. Ahn, Hyungtaik, and James Powell. 1993. Semiparametric estimation of censored selection models with a nonparametric selection mechanism. Journal of Econometrics 58:3-29.
4. Angrist, Joshua. 1990. Lifetime earnings and the Vietnam era draft lottery: Evidence from Social Security administrative records. American Economic Review 80:313-36.
5. Angrist, Joshua, Eric Bettinger, Eric Bloom, Elisabeth King, and Michael Kremer. 2002. Vouchers for private schooling in Colombia: Evidence from a randomized natural experiment. American Economic Review 92: 1535-58.
6. Angrist, Joshua, Guido Imbens, and Donald Rubin. 1996. Identification of causal effects using instrumental variables. Journal of the American Statistical Association 91:444-56.
7. Barnard, John, Constantine Frangakis, Jennifer Hill, and Donald Rubin. 2003. Principal stratification approach to broken randomized experiments: Acase study of school choice vouchers inNewYorkCity. Journal of the American Statistical Association 98:299-311.
8. Bjorklund, Anders, and Robert Moffitt. 1987. The estimation of wage and welfare gains in self-selection models. Review of Economics and Statistics 69:42-49.
9. Blundell, Richard, Amanda Gosling, Hidehiko Ichimura, and Costas Meghir. 2007. Changes in the distribution of male and female wages accounting for employment composition using bounds. Econometrica 75, no. 2:323-63.
10. Chernozhukov, Victor, Han Hong, and Eli Tamer. 2007. Estimation and confidence regions for parameter sets in econometric models. Econometrica 75, no. 5:1243-84.
11. Cullen, Julie, Brian Jacob, and Steven Levitt. 2006. The effect of school choice on student outcomes: Evidence from randomized lotteries. Econometrica 74, no. 5:1191-1230.
12. Das, Mitali, Whitney Newey, and Francis Vella. 2003. Nonparametric estimation of sample selectionmodels. Review of Economic Studies 70:33-58.
13. Dobbie, Will, and Roland Fryer. 2009. Are high quality schools enough to close the achievement gap? Evidence from a social experiment in Harlem. Working Paper no. 15473, National Bureau of Economic Research, Cambridge, MA.
14. Fisher, Ronald. 1935. Design of experiments. New York: Hafner.
15. Frangakis, Constantine, and Donald Rubin. 2002. Principal stratification in causal inference. Biometrics 58:21-29.
16. Frolich, Markus, and Michael Lechner. 2010. Combining matching and nonparametric IV estimation: Theory and an application to the evaluation of active labor market policies. Working paper, http://ideas.repec.org/p/usg/dp2010/2010-21.html.
17. Hansen, Lars Peter. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50, no. 4:1029-53.
18. Hastings, Justine, Thomas Kane, and Doug Staiger. 2010. Heterogeneous preferences and the efficacy of public school choice. Working paper, http://justinehastings.com/research/jh-papers/item/108-hastings-kane-staiger-rev2010.
19. Heckman, James. 1974. Shadow prices, market wages and labor supply. Econometrica 42, no. 4:679-94.
20. Heckman, James. 1978. Dummy endogenous variables in a simultaneous equation system. Econometrica 46:931-60.
21. Heckman, James. 1979. Sample selection bias as a specification error. Econometrica 47, no. 1:153-61.
22. Heckman, James. 1990. Varieties of selection bias. American Economic Review Papers and Proceedings 80:313-18.
23. Heckman, James, Hidehiko Ichimura, and Petra Todd. 1997. Matching as an econometric evaluation estimator: Evidence from evaluating a job training programme. Review of Economic Studies 64, no. 4:605-64.
24. Heckman, James, and Richard Robb. 1985. Alternative methods for evaluating the impact of interventions in longitudinal analysis of labor market data. Cambridge: Cambridge University Press.
25. Heckman, James, Sergio Urzua, and Edward Vytlacil. 2006. Understanding instrumental variables in models with essential heterogeneity. Review of Economics and Statistics 88, no. 3:389-432.
26. Heckman, James, and Edward Vytlacil. 2005. Structural equations, treatment effects and econometric policy evaluation. Econometrica 73, no. 3: 669-738.
27. Heckman, James, and Edward Vytlacil. 2007. Econometric evaluation of social programs. Pts. 1 and 2. In Handbook of Econometrics, vol. 6B, ed. James Heckman and Edward Leamer. Amsterdam: Elsevier/North-Holland.
28. Horowitz, Joel, and Charles Manski. 2000. Nonparametric analysis of randomized experiments with missing covariate and outcome data. Journal of the American Statistical Association 95:77-84.
29. Hoxby, Caroline, and Sonali Murarka. 2009. Charter schools in New York City:Who enrolls and howthey affect their students' achievement. Working Paper no. 14852, National Bureau of Economic Research, Cambridge, MA.
30. Hoxby, Caroline, and Jonah Rockoff. 2005. The impact of charter schools on student achievement. Working paper, http://www.rand.org/content/dam/rand/www/external/labor/seminars/adp/pdfs/2005hoxby.pdf.
31. Imbens, Guido, and Charles Manski. 2004. Confidence intervals for partially identified parameters. Econometrica 72:1845-57.
32. Imberman, Scott. 2011. Achievement and behavior in charter schools: Drawing a more complete picture. Review of Economics and Statistics 93, no. 2:416-35.
33. Lee, David S. 2009. Training, wages, and sample selection: Estimating sharp bounds on treatment effects. Review of Economic Studies 76, no. 3:1071-1102.
34. Lee, Lung Fei. 1979. Identification and estimation in binary choice models with limited {eth}censored{Thorn} dependent variables. Econometrica 47:977-96.
35. Manski, Charles. 1990. Nonparametric bounds on treatment effects. American Economic Review Papers and Proceedings 80:319-23.
36. Moffitt, Robert. 2008. Estimating marginal treatment effects in heterogeneous populations. Annals of Economics and Statistics/Annales d'Économie et de Statistique, nos. 91/92:239-61.
37. Neyman, Jerzy. 1923/1990. On the application of probability theory to agricultural experiments: Essay on principles, section 9 [trans. from Polish]. Statistical Science 5:465-80.
38. Quandt, Richard. 1972. A new approach to estimating switching regression models. Journal of the American Statistical Association 67:306-10.
39. Rosenbaum, Paul, and Don Rubin. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41-55.
40. Rouse, Cecilia. 1998. Private school vouchers and student achievement: An evaluation of theMilwaukee Parental Choice Program. Quarterly Journal of Economics 113:553-602.
41. Rubin, Don. 1974. Estimating causal effects of treatment in randomized and nonrandomized studies. Journal of Educational Psychology 66:688-701.
42. Rubin, Don. 1976. Inference and missing data. Biometrika 63:581-92.
43. Rubin, Don. 1978. Bayesian inference for causal effects. Annals of Statistics 6: 34-58.
44. Zhang, Junni, and Don Rubin. 2003. Estimation of causal effects via principal stratification when some outcomes are truncated by "death." Journal of Educational and Behavioral Statistics 28:353-68.
45. Zhang, Junni, Don Rubin, and Fabrizia Mealli. 2009. Likelihood-based analysis of causal effects of job-training programs using principal stratification. Journal of the American Statistical Association 104:166-76.