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Comparing distributions by multiple testing across quantiles

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  • David M. Kaplan & Matt Goldman, 2013. "Comparing distributions by multiple testing across quantiles," Working Papers 1319, Department of Economics, University of Missouri, revised Feb 2018.
  • Handle: RePEc:umc:wpaper:1319
    Note: Title change on 2018-02
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    1. Paolo Angelini & Andrea Generale, 2008. "On the Evolution of Firm Size Distributions," American Economic Review, American Economic Association, vol. 98(1), pages 426-438, March.
    2. Linton, Oliver & Song, Kyungchul & Whang, Yoon-Jae, 2010. "An improved bootstrap test of stochastic dominance," Journal of Econometrics, Elsevier, vol. 154(2), pages 186-202, February.
    3. David M. Kaplan & Matt Goldman, 2015. "Nonparametric inference on conditional quantile differences and linear combinations, using L-statistics," Working Papers 1503, Department of Economics, University of Missouri.
    4. Thomas MaCurdy & Xiaohong Chen & Han Hong, 2011. "Flexible Estimation of Treatment Effect Parameters," American Economic Review, American Economic Association, vol. 101(3), pages 544-551, May.
    5. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    6. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    7. Ivan A Canay & Vishal Kamat, 2018. "Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design," Review of Economic Studies, Oxford University Press, vol. 85(3), pages 1577-1608.
    8. Erica Field & Rohini Pande & John Papp & Natalia Rigol, 2013. "Does the Classic Microfinance Model Discourage Entrepreneurship among the Poor? Experimental Evidence from India," American Economic Review, American Economic Association, vol. 103(6), pages 2196-2226, October.
    9. Oriana Bandiera & Iwan Barankay & Imran Rasul, 2009. "Social Connections and Incentives in the Workplace: Evidence From Personnel Data," Econometrica, Econometric Society, vol. 77(4), pages 1047-1094, July.
    10. Jens M. Arnold & Katrin Hussinger, 2010. "Exports versus FDI in German Manufacturing: Firm Performance and Participation in International Markets," Review of International Economics, Wiley Blackwell, vol. 18(4), pages 595-606, September.
    11. John Wooders, 2010. "Does Experience Teach? Professionals and Minimax Play in the Lab," Econometrica, Econometric Society, vol. 78(3), pages 1143-1154, May.
    12. Jan Eeckhout, 2009. "Gibrat's Law for (All) Cities: Reply," American Economic Review, American Economic Association, vol. 99(4), pages 1676-1683, September.
    13. Armin Falk, 2007. "Gift Exchange in the Field," Econometrica, Econometric Society, vol. 75(5), pages 1501-1511, September.
    14. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    15. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    16. Bitler, Marianne P. & Gelbach, Jonah B. & Hoynes, Hilary W., 2008. "Distributional impacts of the Self-Sufficiency Project," Journal of Public Economics, Elsevier, vol. 92(3-4), pages 748-765, April.
    17. Uri Gneezy & John A List, 2006. "Putting Behavioral Economics to Work: Testing for Gift Exchange in Labor Markets Using Field Experiments," Econometrica, Econometric Society, vol. 74(5), pages 1365-1384, September.
    18. Russell Davidson & Jean-Yves Duclos, 2013. "Testing for Restricted Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 84-125, January.
    19. Peter Bossaerts & Charles Plott & William R. Zame, 2007. "Prices and Portfolio Choices in Financial Markets: Theory, Econometrics, Experiments," Econometrica, Econometric Society, vol. 75(4), pages 993-1038, July.
    20. R'emy Chicheportiche & Jean-Philippe Bouchaud, 2012. "Weighted Kolmogorov-Smirnov test: Accounting for the tails," Papers 1207.7308, arXiv.org, revised Oct 2012.
    21. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    22. David M. Kaplan & Longhao Zhuo, 2016. "Frequentist size of Bayesian inequality tests," Papers 1607.00393, arXiv.org, revised Feb 2018.
    23. Qi Li & Juan Lin & Jeffrey S. Racine, 2013. "Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 57-65, January.
    24. Djebbari, Habiba & Smith, Jeffrey, 2008. "Heterogeneous impacts in PROGRESA," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 64-80, July.
    25. Shih-Hsun Hsu & Chen-Ying Huang & Cheng-Tao Tang, 2007. "Minimax Play at Wimbledon: Comment," American Economic Review, American Economic Association, vol. 97(1), pages 517-523, March.
    26. Jan Eeckhout, 2004. "Gibrat's Law for (All) Cities," American Economic Review, American Economic Association, vol. 94(5), pages 1429-1451, December.
    27. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    28. Ferreira, Francisco H. G. & Firpo, Sergio & Galvao, Antonio F., 2017. "Estimation and Inference for Actual and Counterfactual Growth Incidence Curves," IZA Discussion Papers 10473, Institute of Labor Economics (IZA).
    29. Sokbae (Simon) Lee & Yoon-Jae Whang, 2009. "Nonparametric tests of conditional treatment effects," CeMMAP working papers CWP36/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    31. David M. Kaplan & Longhao Zhuo, 2015. "Bayesian and frequentist inequality tests," Working Papers 1516, Department of Economics, University of Missouri, revised Feb 2018.
    32. Shu Shen & Xiaohan Zhang, 2016. "Distributional Tests for Regression Discontinuity: Theory and Empirical Examples," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 685-700, October.
    33. David M. Kaplan & Matt Goldman, 2013. "IDEAL Quantile Inference via Interpolated Duals of Exact Analytic L-statistics," Working Papers 1315, Department of Economics, University of Missouri.
    34. Oriana Bandiera & Iwan Barankay & Imran Rasul, 2010. "Social Incentives in the Workplace," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 417-458.
    35. Moscovich, Amit & Nadler, Boaz, 2017. "Fast calculation of boundary crossing probabilities for Poisson processes," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 177-182.
    36. Mark Walker & John Wooders, 2001. "Minimax Play at Wimbledon," American Economic Review, American Economic Association, vol. 91(5), pages 1521-1538, December.
    37. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
    38. Stephen G. Donald & Yu-Chin Hsu, 2016. "Improving the Power of Tests of Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 35(4), pages 553-585, April.
    39. Marsaglia, George & Tsang, Wai Wan & Wang, Jingbo, 2003. "Evaluating Kolmogorov's Distribution," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i18).
    40. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 735-765.
    41. Jackson, Erika & Page, Marianne E., 2013. "Estimating the distributional effects of education reforms: A look at Project STAR," Economics of Education Review, Elsevier, vol. 32(C), pages 92-103.
    42. Moshe Levy, 2009. "Gibrat's Law for (All) Cities: Comment," American Economic Review, American Economic Association, vol. 99(4), pages 1672-1675, September.
    43. Sivan Aldor-Noiman & Lawrence D. Brown & Andreas Buja & Wolfgang Rolke & Robert A. Stine, 2013. "The Power to See: A New Graphical Test of Normality," The American Statistician, Taylor & Francis Journals, vol. 67(4), pages 249-260, November.
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    Cited by:

    1. Blemings, Benjamin T. & Bock, Margaret & Scarcioffolo, Alexandre, 2022. "Hoggin' the Road: Negative Road Externalities of Pork Slaughterhouses," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322466, Agricultural and Applied Economics Association.
    2. John Mullahy, 2020. "Discovering Treatment Effectiveness via Median Treatment Effects—Applications to COVID-19 Clinical Trials," NBER Working Papers 27895, National Bureau of Economic Research, Inc.
    3. Gedikli, Cigdem & Popli, Gurleen & Yilmaz, Okan, 2023. "The impact of intimate partner violence on women’s labour market outcomes," World Development, Elsevier, vol. 164(C).
    4. Matt Goldman & David M. Kaplan, 2018. "Non‐parametric inference on (conditional) quantile differences and interquantile ranges, using L‐statistics," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 136-169, June.
    5. Anastasios Evgenidis & Apostolos Fasianos, 2021. "Unconventional Monetary Policy and Wealth Inequalities in Great Britain," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 115-175, February.
    6. David M. Kaplan, 2019. "distcomp: Comparing distributions," Stata Journal, StataCorp LP, vol. 19(4), pages 832-848, December.
    7. David M. Kaplan & Longhao Zhuo, 2015. "Bayesian and frequentist inequality tests," Working Papers 1516, Department of Economics, University of Missouri, revised Feb 2018.
    8. Goldman, Matt & Kaplan, David M., 2017. "Fractional order statistic approximation for nonparametric conditional quantile inference," Journal of Econometrics, Elsevier, vol. 196(2), pages 331-346.
    9. Huang, Wei & Li, Teng & Pan, Yinghao & Ren, Jinyang, 2021. "Teacher Characteristics and Student Performance: Evidence from Random Teacher-Student Assignments in China," IZA Discussion Papers 14184, Institute of Labor Economics (IZA).
    10. David M. Kaplan, 2020. "Inference on Consensus Ranking of Distributions," Working Papers 2010, Department of Economics, University of Missouri.
    11. Cirera,Xavier & Comin,Diego Adolfo & Vargas Da Cruz,Marcio Jose & Lee,Kyungmin, 2020. "Technology Within and Across Firms," Policy Research Working Paper Series 9476, The World Bank.
    12. Chung, EunYi & Olivares, Mauricio, 2021. "Permutation test for heterogeneous treatment effects with a nuisance parameter," Journal of Econometrics, Elsevier, vol. 225(2), pages 148-174.
    13. Cirera, Xavi & Cruz, Marcio & Lee, Kyung Min, 2020. "Anatomy of Technology in the Firm," CEPR Discussion Papers 15427, C.E.P.R. Discussion Papers.
    14. Heyman, Fredrik & Norbäck, Pehr-Johan & Persson, Lars, 2017. "Talent, Career Choice and Competition: The Gender Wage Gap at the Top," Working Paper Series 1169, Research Institute of Industrial Economics, revised 06 Mar 2023.
    15. Bloem, Jeffrey R. & Liverpool-Tasie, Saweda & Adjognon, Serge G. & Dillon, Andrew, 2022. "Private Sector Promotion of Climate-Smart Technologies: Experimental Evidence from Nigeria," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322152, Agricultural and Applied Economics Association.
    16. Klenio Barbosa & Dakshina De Silva & Liyu Yang & Hisayuki Yoshimoto, 2020. "Bond Losses and Systemic Risk," Working Papers 288072615, Lancaster University Management School, Economics Department.
    17. Martin DeLuca & Roberto Pinheiro, 2023. "US Labor Market after COVID-19: An Interim Report," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(04), pages 1-7, February.
    18. John Mullahy, 2021. "Discovering treatment effectiveness via median treatment effects—Applications to COVID‐19 clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 30(5), pages 1050-1069, May.

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    More about this item

    Keywords

    Dirichlet; familywise error rate; Kolmogorov–Smirnov; probability integral transform; stepdown;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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