References
- Abadie, A., and Imbens, G. W. (2006), “Large Sample Properties of Matching Estimators for Average Treatment Effects,” Econometrica, 74, 235–267. DOI: 10.1111/j.1468-0262.2006.00655.x.
- Abou-Chadi, T., and Krause, W. (2020), “The Causal Effect of Radical Right Success on Mainstream Parties’ Policy Positions: A Regression Discontinuity Approach,” British Journal of Political Science, 50, 829–847. DOI: 10.1017/S0007123418000029.
- Agarwal, S., Chomsisengphet, S., Mahoney, N., and Stroebel, J. (2017), “Do Banks Pass Through Credit Expansions to Consumers Who Want to Borrow?” Quarterly Journal of Economics, 133, 129–190. DOI: 10.1093/qje/qjx027.
- Armstrong, T. B., and Kolesár, M. (2018), “Optimal Inference in a Class of Regression Models,” Econometrica, 86, 655–683. DOI: 10.3982/ECTA14434.
- Bertanha, M., and Moreira, M. J. (2020), “Impossible Inference in Econometrics: Theory and Applications,” Journal of Econometrics, 218, 247–270. DOI: 10.1016/j.jeconom.2020.04.016.
- Bugni, F. A., and Canay, I. A. (2021), “Testing Continuity of a Density via g-Order Statistics in the Regression Discontinuity Design,” Journal of Econometrics, 221, 138–159. DOI: 10.1016/j.jeconom.2020.02.004.
- Caetano, C. (2015), “A Test of Exogeneity without Instrumental Variables in Models with Bunching,” Econometrica, 83, 1581–1600. DOI: 10.3982/ECTA11231.
- Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), “Robust Nonparametric Confidence Intervals for Regression-discontinuity Designs,” Econometrica, 82, 2295–2326. DOI: 10.3982/ECTA11757.
- Canay, I. A., and Kamat, V. (2018), “Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design,” Review of Economic Studies, 85, 1577–1608. DOI: 10.1093/restud/rdx062.
- Canay, I. A., Romano, J. P., and Shaikh, A. M. (2017), “Randomization Tests under an Approximate Symmetry Assumption,” Econometrica, 85, 1013–1030. DOI: 10.3982/ECTA13081.
- Cao-Abad, R. (1991), “Rate of Convergence for the Wild Bootstrap in Nonparametric Regression,” The Annals of Statistics, 19, 2226–2231. DOI: 10.1214/aos/1176348394.
- Cattaneo, M. D., Frandsen, B. R., 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: 10.1515/jci-2013-0010.
- Cattaneo, M. D., Jansson, M., and Ma, X. (2020), “Simple Local Polynomial Density Estimators,” Journal of the American Statistical Association, 115, 1449–1455. DOI: 10.1080/01621459.2019.1635480.
- Chaudhuri, P. (1991), “Nonparametric Estimates of Regression Quantiles and Their Local Bahadur Representation,” The Annals of Statistics, 19, 760–777. DOI: 10.1214/aos/1176348119.
- Chung, E., and Olivares, M. (2021), “Permutation Test for Heterogeneous Treatment Effects with a Nuisance Parameter,” Journal of Econometrics, 225, 148–174. DOI: 10.1016/j.jeconom.2020.09.015.
- Chung, E., and Romano, J. P. (2013), “Exact and Asymptotically Robust Permutation Tests,” The Annals of Statistics, 41, 484–507. DOI: 10.1214/13-AOS1090.
- Chung, E., and Romano, J. P. (2016a), “Asymptotically Valid and Exact Permutation Tests Based on Two-sample U-statistics,” Journal of Statistical Planning and Inference, 168, 97–105.
- Chung, E., and Romano, J. P. (2016b) “Multivariate and Multiple Permutation Tests,” Journal of Econometrics, 193, 76–91.
- DiCiccio, C. J., and Romano, J. P. (2017), “Robust Permutation Tests for Correlation and Regression Coefficients,” Journal of the American Statistical Association, 112, 1211–1220. DOI: 10.1080/01621459.2016.1202117.
- Fan, J., and Gijbels, I. (1996), Local Polynomial Modelling and its Applications, 66 of Monographs on Statistics and Applied Probability, Boca Raton, FL: CRC Press.
- Fan, J., Hu, T.-C., and Truong, Y. K. (1994) “Robust Non-parametric Function Estimation,” Scandinavian Journal of Statistics, 21, 433–446.
- Fogarty, C. B. (2021), “Prepivoted Permutation Tests,” arXiv preprint arXiv:2102.04423.
- Hahn, J., Todd, P., and Van der Klaauw, W. (2001), “Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design,” Econometrica, 69, 201–209. DOI: 10.1111/1468-0262.00183.
- Hall, P., and Hart, J. D. (1990) “Bootstrap Test for Difference Between Means in Nonparametric Regression,” Journal of the American Statistical Association, 85, 1039–1049. DOI: 10.1080/01621459.1990.10474974.
- Imbens, G. W., and Kalyanaraman, K. (2012) “Optimal Bandwidth Choice for The Regression Discontinuity Estimator,” Review of Economic Studies, 79, 933–959. DOI: 10.1093/restud/rdr043.
- Imbens, G. W., and Rosenbaum, P. R. (2005), “Robust, Accurate Confidence Intervals with a Weak Instrument: Quarter of Birth and Education,” Journal of the Royal Statistical Society, Series A, 168, 109–126. DOI: 10.1111/j.1467-985X.2004.00339.x.
- Janssen, A. (1997), “Studentized Permutation Tests for Non-i.i.d. Hypotheses and the Generalized Behrens-Fisher Problem,” Statistics & Probability Letters, 36, 9–21.
- Janssen, A. (2005) “Resampling Student’s t-type Statistics,” Annals of the Institute of Statistical Mathematics, 57, 507–529.
- Kamat, V. (2018), “On Nonparametric Inference in the Regression Discontinuity Design,” Econometric Theory, 34, 694–703. DOI: 10.1017/S0266466617000196.
- Lee, D. S. (2008) “Randomized Experiments from Non-random Selection in U.S. House Elections,” Journal of Econometrics, 142, 675–697. DOI: 10.1016/j.jeconom.2007.05.004.
- Lehmann, E. L., and Romano, J. P. (2005) Testing Statistical Hypotheses, New York: Springer.
- Li, Q., and Racine, J. S. (2007), Nonparametric Econometrics: Theory and Practice, Princeton: Princeton University Press.
- Ludwig, J., and Miller, D. (2007) “Does Head Start Improve Children’s Life Chances? Evidence From a Regression Discontinuity Design,” Quarterly Journal of Economics, 122, 159–208. DOI: 10.1162/qjec.122.1.159.
- Marron, J. S., and Ruppert, D. (1994), “Transformations to Reduce Boundary Bias in Kernel Density Estimation,” Journal of the Royal Statistical Society, Series B, 56, 653–671. DOI: 10.1111/j.2517-6161.1994.tb02006.x.
- Neubert, K., and Brunner, E. (2007), “A Studentized Permutation Test for the Non-parametric Behrens-Fisher Problem,” Computational Statistics & Data Analysis, 51, 5192–5204.
- Neuhaus, G. (1993), “Conditional Rank Tests for the Two-Sample Problem Under Random Censorship,” The Annals of Statistics, 21, 1760–1779. DOI: 10.1214/aos/1176349396.
- Pauly, M., Brunner, E., and Konietschke, F. (2015) “Asymptotic Permutation Tests in General Factorial Designs,” Journal of the Royal Statistical Society, Series B, 77, 461–473. DOI: 10.1111/rssb.12073.
- Politis, D. N., Romano, J. P., and Wolf, M. (1999), Subsampling, New York: Springer.
- Pollard, D. (1991), “Asymptotics for Least Absolute Deviation Regression Estimators,” Econometric Theory, 7, 186–199. DOI: 10.1017/S0266466600004394.
- Racine, J. (2001), “Bias-Corrected Kernel Regression,” Journal of Quantitative Economics, 17, 25–42.
- Romano, J. P. (1990) “On the Behavior of Randomization Tests Without a Group Invariance Assumption,” Journal of the American Statistical Association, 85, 686–692. DOI: 10.1080/01621459.1990.10474928.
- Saez, E. (2010) “Do Taxpayers Bunch at Kink Points?” American Economic Journal: Economic Policy, 2, 180–212. DOI: 10.1257/pol.2.3.180.
- Shaikh, A. M., and Toulis, P. (2021) “Randomization Tests in Observational Studies with Staggered Adoption of Treatment,” Journal of the American Statistical Association, 116, 1835–1848. DOI: 10.1080/01621459.2021.1974458.
- Thistlethwaite, D. L., and Campbell, D. T. (1960), “Regression-discontinuity Analysis: An Alternative to the Ex Post Facto Experiment,” Journal of Educational Psychology, 51, 309–317. DOI: 10.1037/h0044319.
- Valentine, J. C., Konstantopoulos, S., and Goldrick-Rab, S. (2017) “What Happens to Students Placed into Developmental Education? A Meta-analysis of Regression Discontinuity Studies,” Review of Educational Research, 87, 806–833. DOI: 10.3102/0034654317709237.
- Zoorob, M. (2020), “Do Police Brutality Stories Reduce 911 Calls? Reassessing an Important Criminological Finding,” American Sociological Review, 85, 176–183. DOI: 10.1177/0003122419895254.