References
- Abadie, A. (2005), “Semiparametric Difference-in-Differences Estimators,” Review of Economic Studies, 72, 1–19. DOI: https://doi.org/10.1111/0034-6527.00321.
- Abadie, A., and Cattaneo, M. D. (2018), “Econometric Methods for Program Evaluation,” Annual Review of Economics, 10, 465–503. DOI: https://doi.org/10.1146/annurev-economics-080217-053402.
- Angrist, J. D., Imbens, G. W., and Rubin, D. B. (1996), “Identification of Causal Effects Using Instrumental Variables,” Journal of the American Statistical Association, 91, 444–455. DOI: https://doi.org/10.1080/01621459.1996.10476902.
- Angrist, J. D., and Rokkanen, M. (2015), “Wanna Get Away? Regression Discontinuity Estimation of Exam School Effects Away From the Cutoff,” Journal of the American Statistical Association, 110, 1331–1344. DOI: https://doi.org/10.1080/01621459.2015.1012259.
- Bertanha, M. (2020), “Regression Discontinuity Design With Many Thresholds,” Journal of Econometrics (forthcoming). DOI: https://doi.org/10.1016/j.jeconom.2019.09.010.
- Bertanha, M., and Imbens, G. W. (2020), “External Validity in Fuzzy Regression Discontinuity Designs,” Journal of Business & Economic Statistics (forthcoming). DOI: https://doi.org/10.1080/07350015.2018.1546590.
- Calonico, S., Cattaneo, M. D., and Farrell, M. H. (2018), “On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference,” Journal of the American Statistical Association, 113, 767–779. DOI: https://doi.org/10.1080/01621459.2017.1285776.
- Calonico, S., Cattaneo, M. D., and Farrell, M. H. (2019), “nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference,” Journal of Statistical Software, 8, 1–33.
- Calonico, S., Cattaneo, M. D., and Farrell, M. H. (2020a), “Coverage Error Optimal Confidence Intervals for Local Polynomial Regression,” arXiv no. 1808.01398.
- Calonico, S., Cattaneo, M. D., and Farrell, M. H. (2020b), “Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs,” Econometrics Journal, 23, 192–210.
- Calonico, S., Cattaneo, M. D., Farrell, M. H., and Titiunik, R. (2017), “rdrobust: Software for Regression Discontinuity Designs,” Stata Journal, 17, 372–404. DOI: https://doi.org/10.1177/1536867X1701700208.
- Calonico, S., Cattaneo, M. D., Farrell, M. H., and Titiunik, R. (2019), “Regression Discontinuity Designs Using Covariates,” Review of Economics and Statistics, 101, 442–451.
- Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), “Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs,” Econometrica, 82, 2295–2326. DOI: https://doi.org/10.3982/ECTA11757.
- Calonico, S., Cattaneo, M. D., and Titiunik, R. (2015), “Optimal Data-Driven Regression Discontinuity Plots,” Journal of the American Statistical Association, 110, 1753–1769.
- Cattaneo, M. D., Frandsen, B., and Titiunik, R. (2015), “Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate,” Journal of Causal Inference, 3, 1–24. DOI: https://doi.org/10.1515/jci-2013-0010.
- Cattaneo, M. D., Idrobo, N., and Titiunik, R. (2019), A Practical Introduction to Regression Discontinuity Designs: Foundations, Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge: Cambridge University Press.
- Cattaneo, M. D., Idrobo, N., and Titiunik, R. (2020), A Practical Introduction to Regression Discontinuity Designs: Extensions, Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge: Cambridge University Press (to appear).
- Cattaneo, M. D., Keele, L., Titiunik, R., and Vazquez-Bare, G. (2016), “Interpreting Regression Discontinuity Designs With Multiple Cutoffs,” Journal of Politics, 78, 1229–1248. DOI: https://doi.org/10.1086/686802.
- Cattaneo, M. D., Titiunik, R., and Vazquez-Bare, G. (2017), “Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality,” Journal of Policy Analysis and Management, 36, 643–681. DOI: https://doi.org/10.1002/pam.21985.
- Cattaneo, M. D., Titiunik, R., and Vazquez-Bare, G. (2020a), “Analysis of Regression Discontinuity Designs With Multiple Cutoffs or Multiple Scores,” Stata Journal, forthcoming.
- Cattaneo, M. D., Titiunik, R., and Vazquez-Bare, G. (2020b), “The Regression Discontinuity Design,” in Handbook of Research Methods in Political Science and International Relations, eds. L. Curini and R. J. Franzese, Thousand Oaks, CA: SAGE Publications.
- Dong, Y., Lee, Y.-Y., and Gou, M. (2020), “Regression Discontinuity Designs With a Continuous Treatment,” SSRN Working Paper No. 3167541.
- Dong, Y., and Lewbel, A. (2015), “Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models,” Review of Economics and Statistics, 97, 1081–1092. DOI: https://doi.org/10.1162/REST_a_00510.
- Fan, J., and Gijbels, I. (1996), Local Polynomial Modelling and Its Applications, New York: Chapman & Hall/CRC.
- Ganong, P., and Jäger, S. (2018), “A Permutation Test for the Regression Kink Design,” Journal of the American Statistical Association, 113, 494–504. DOI: https://doi.org/10.1080/01621459.2017.1328356.
- Hyytinen, A., Meriläinen, J., Saarimaa, T., Toivanen, O., and Tukiainen, J. (2018), “When Does Regression Discontinuity Design Work? Evidence From Random Election Outcomes,” Quantitative Economics, 9, 1019–1051. DOI: https://doi.org/10.3982/QE864.
- Imbens, G. W., and Lemieux, T. (2008), “Regression Discontinuity Designs: A Guide to Practice,” Journal of Econometrics, 142, 615–635. DOI: https://doi.org/10.1016/j.jeconom.2007.05.001.
- Imbens, G. W., and Rubin, D. B. (2015), Causal Inference in Statistics, Social, and Biomedical Sciences, Cambridge: Cambridge University Press.
- Keele, L. J., and Titiunik, R. (2015), “Geographic Boundaries as Regression Discontinuities,” Political Analysis, 23, 127–155. DOI: https://doi.org/10.1093/pan/mpu014.
- Keele, L. J., Titiunik, R., and Zubizarreta, J. (2015), “Enhancing a Geographic Regression Discontinuity Design Through Matching to Estimate the Effect of Ballot Initiatives on Voter Turnout,” Journal of the Royal Statistical Society, Series A, 178, 223–239. DOI: https://doi.org/10.1111/rssa.12056.
- Li, F., Mattei, A., and Mealli, F. (2015), “Evaluating the Causal Effect of University Grants on Student Dropout: Evidence From a Regression Discontinuity Design Using Principal Stratification,” Annals of Applied Statistics, 9, 1906–1931. DOI: https://doi.org/10.1214/15-AOAS881.
- Mealli, F., and Rampichini, C. (2012), “Evaluating the Effects of University Grants by Using Regression Discontinuity Designs,” Journal of the Royal Statistical Society, Series A, 175, 775–798. DOI: https://doi.org/10.1111/j.1467-985X.2011.01022.x.
- Melguizo, T., Sanchez, F., and Velasco, T. (2016), “Credit for Low-Income Students and Access to and Academic Performance in Higher Education in Colombia: A Regression Discontinuity Approach,” World Development, 80, 61–77. DOI: https://doi.org/10.1016/j.worlddev.2015.11.018.
- Papay, J. P., Willett, J. B., and Murnane, R. J. (2011), “Extending the Regression-Discontinuity Approach to Multiple Assignment Variables,” Journal of Econometrics, 161, 203–207. DOI: https://doi.org/10.1016/j.jeconom.2010.12.008.
- Reardon, S. F., and Robinson, J. P. (2012), “Regression Discontinuity Designs With Multiple Rating-Score Variables,” Journal of Research on Educational Effectiveness, 5, 83–104. DOI: https://doi.org/10.1080/19345747.2011.609583.
- Rokkanen, M. (2015), “Exam Schools, Ability, and the Effects of Affirmative Action: Latent Factor Extrapolation in the Regression Discontinuity Design,” Unpublished Manuscript.
- Rosenbaum, P. R. (2010), Design of Observational Studies, New York: Springer.
- Sekhon, J. S., and Titiunik, R. (2016), “Understanding Regression Discontinuity Designs as Observational Studies,” Observational Studies, 2, 174–182.
- Sekhon, J. S., and Titiunik, R. (2017), “On Interpreting the Regression Discontinuity Design as a Local Experiment,” in Regression Discontinuity Designs: Theory and Applications, Advances in Econometrics (Vol. 38), eds. M. D. Cattaneo and J. C. Escanciano, Bingley: Emerald Group Publishing, pp. 1–28.
- Wing, C., and Cook, T. D. (2013), “Strengthening the Regression Discontinuity Design Using Additional Design Elements: A Within-Study Comparison,” Journal of Policy Analysis and Management, 32, 853–877. DOI: https://doi.org/10.1002/pam.21721.