×

Permutation tests at nonparametric rates. (English) Zbl 07784949

Summary: Classical two-sample permutation tests for equality of distributions have exact size in finite samples, but they fail to control size for testing equality of parameters that summarize each distribution. This article proposes permutation tests for equality of parameters that are estimated at root-\(n\) or slower rates. Our general framework applies to both parametric and nonparametric models, with two samples or one sample split into two subsamples. Our tests have correct size asymptotically while preserving exact size in finite samples when distributions are equal. They have no loss in local asymptotic power compared to tests that use asymptotic critical values. We propose confidence sets with correct coverage in large samples that also have exact coverage in finite samples if distributions are equal up to a transformation. We apply our theory to four commonly-used hypothesis tests of nonparametric functions evaluated at a point. Lastly, simulations show good finite sample properties, and two empirical examples illustrate our tests in practice. Supplementary materials for this article are available online.

MSC:

62-XX Statistics

References:

[1] Abadie, A., and Imbens, G. W. (2006), “Large Sample Properties of Matching Estimators for Average Treatment Effects,” Econometrica, 74, 235-267. DOI: . · Zbl 1112.62042
[2] 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: .
[3] 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: . · Zbl 1405.91665
[4] Armstrong, T. B., and Kolesár, M. (2018), “Optimal Inference in a Class of Regression Models,” Econometrica, 86, 655-683. DOI: . · Zbl 1414.62150
[5] Bertanha, M., and Moreira, M. J. (2020), “Impossible Inference in Econometrics: Theory and Applications,” Journal of Econometrics, 218, 247-270. DOI: . · Zbl 1464.62494
[6] 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: . · Zbl 1464.62270
[7] Caetano, C. (2015), “A Test of Exogeneity without Instrumental Variables in Models with Bunching,” Econometrica, 83, 1581-1600. DOI: . · Zbl 1410.62176
[8] Calonico, S., Cattaneo, M. D., and Titiunik, R. (2014), “Robust Nonparametric Confidence Intervals for Regression-discontinuity Designs,” Econometrica, 82, 2295-2326. DOI: . · Zbl 1410.62066
[9] 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: . · Zbl 1409.62095
[10] Canay, I. A., Romano, J. P., and Shaikh, A. M. (2017), “Randomization Tests under an Approximate Symmetry Assumption,” Econometrica, 85, 1013-1030. DOI: . · Zbl 1410.62103
[11] Cao-Abad, R. (1991), “Rate of Convergence for the Wild Bootstrap in Nonparametric Regression,” The Annals of Statistics, 19, 2226-2231. DOI: . · Zbl 0745.62038
[12] 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: .
[13] Cattaneo, M. D., Jansson, M., and Ma, X. (2020), “Simple Local Polynomial Density Estimators,” Journal of the American Statistical Association, 115, 1449-1455. DOI: . · Zbl 1441.62091
[14] Chaudhuri, P. (1991), “Nonparametric Estimates of Regression Quantiles and Their Local Bahadur Representation,” The Annals of Statistics, 19, 760-777. DOI: . · Zbl 0728.62042
[15] Chung, E., and Olivares, M. (2021), “Permutation Test for Heterogeneous Treatment Effects with a Nuisance Parameter,” Journal of Econometrics, 225, 148-174. DOI: . · Zbl 07414287
[16] Chung, E., and Romano, J. P. (2013), “Exact and Asymptotically Robust Permutation Tests,” The Annals of Statistics, 41, 484-507. DOI: . · Zbl 1267.62064
[17] 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. · Zbl 1333.62124
[18] Chung, E., and Romano, J. P. (2016b) “Multivariate and Multiple Permutation Tests,” Journal of Econometrics, 193, 76-91. · Zbl 1420.62250
[19] 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: .
[20] 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.
[21] Fan, J., Hu, T.-C., and Truong, Y. K. (1994) “Robust Non-parametric Function Estimation,” Scandinavian Journal of Statistics, 21, 433-446. · Zbl 0810.62038
[22] Fogarty, C. B. (2021), “Prepivoted Permutation Tests,” arXiv preprint arXiv:2102.04423.
[23] 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: .
[24] 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: . · Zbl 0717.62037
[25] Imbens, G. W., and Kalyanaraman, K. (2012) “Optimal Bandwidth Choice for The Regression Discontinuity Estimator,” Review of Economic Studies, 79, 933-959. DOI: . · Zbl 1409.62089
[26] 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: . · Zbl 1101.62120
[27] Janssen, A. (1997), “Studentized Permutation Tests for Non-i.i.d. Hypotheses and the Generalized Behrens-Fisher Problem,” Statistics & Probability Letters, 36, 9-21. · Zbl 1064.62526
[28] Janssen, A. (2005) “Resampling Student’s t-type Statistics,” Annals of the Institute of Statistical Mathematics, 57, 507-529. · Zbl 1095.62050
[29] Kamat, V. (2018), “On Nonparametric Inference in the Regression Discontinuity Design,” Econometric Theory, 34, 694-703. DOI: . · Zbl 1390.62073
[30] Lee, D. S. (2008) “Randomized Experiments from Non-random Selection in U.S. House Elections,” Journal of Econometrics, 142, 675-697. DOI: . · Zbl 1418.62500
[31] Lehmann, E. L., and Romano, J. P. (2005) Testing Statistical Hypotheses, New York: Springer. · Zbl 1076.62018
[32] Li, Q., and Racine, J. S. (2007), Nonparametric Econometrics: Theory and Practice, Princeton: Princeton University Press. · Zbl 1183.62200
[33] 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: .
[34] 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: . · Zbl 0805.62046
[35] Neubert, K., and Brunner, E. (2007), “A Studentized Permutation Test for the Non-parametric Behrens-Fisher Problem,”Computational Statistics & Data Analysis, 51, 5192-5204. · Zbl 1162.62351
[36] Neuhaus, G. (1993), “Conditional Rank Tests for the Two-Sample Problem Under Random Censorship,” The Annals of Statistics, 21, 1760-1779. DOI: . · Zbl 0793.62027
[37] 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: . · Zbl 1414.62339
[38] Politis, D. N., Romano, J. P., and Wolf, M. (1999), Subsampling, New York: Springer. · Zbl 0931.62035
[39] Pollard, D. (1991), “Asymptotics for Least Absolute Deviation Regression Estimators,” Econometric Theory, 7, 186-199. DOI: .
[40] Racine, J. (2001), “Bias-Corrected Kernel Regression,” Journal of Quantitative Economics, 17, 25-42.
[41] 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: . · Zbl 0706.62047
[42] Saez, E. (2010) “Do Taxpayers Bunch at Kink Points?” American Economic Journal: Economic Policy, 2, 180-212. DOI: .
[43] 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: . · Zbl 1506.62254
[44] 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: .
[45] 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: .
[46] Zoorob, M. (2020), “Do Police Brutality Stories Reduce 911 Calls? Reassessing an Important Criminological Finding,” American Sociological Review, 85, 176-183. DOI: .
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.