IDEAS home Printed from https://ideas.repec.org/h/nbr/nberch/14958.html
   My bibliography  Save this book chapter

Quantifying the Uncertainty of Imputed Demographic Disparity Estimates: The Dual Bootstrap

In: Race, Ethnicity, and Economic Statistics for the 21st Century

Author

Listed:
  • Benjamin Lu
  • Jia Wan
  • Derek Ouyang
  • Jacob Goldin
  • Daniel E. Ho

Abstract

No abstract is available for this item.

Suggested Citation

  • Benjamin Lu & Jia Wan & Derek Ouyang & Jacob Goldin & Daniel E. Ho, 2024. "Quantifying the Uncertainty of Imputed Demographic Disparity Estimates: The Dual Bootstrap," NBER Chapters, in: Race, Ethnicity, and Economic Statistics for the 21st Century, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:14958
    as

    Download full text from publisher

    File URL: http://www.nber.org/chapters/c14958.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carlos F Avenancio-León & Troup Howard, 2022. "The Assessment Gap: Racial Inequalities in Property Taxation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(3), pages 1383-1434.
    2. Ji-Sung Kim & Xin Gao & Andrey Rzhetsky, 2018. "RIDDLE: Race and ethnicity Imputation from Disease history with Deep LEarning," PLOS Computational Biology, Public Library of Science, vol. 14(4), pages 1-15, April.
    3. Vaart,A. W. van der, 2000. "Asymptotic Statistics," Cambridge Books, Cambridge University Press, number 9780521784504, November.
    4. Miratrix, Luke W. & Sekhon, Jasjeet S. & Theodoridis, Alexander G. & Campos, Luis F., 2018. "Worth Weighting? How to Think About and Use Weights in Survey Experiments," Political Analysis, Cambridge University Press, vol. 26(3), pages 275-291, July.
    5. Nathan Kallus & Xiaojie Mao & Angela Zhou, 2022. "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination," Management Science, INFORMS, vol. 68(3), pages 1959-1981, March.
    6. Ariel Kleiner & Ameet Talwalkar & Purnamrita Sarkar & Michael I. Jordan, 2014. "A scalable bootstrap for massive data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(4), pages 795-816, September.
    7. Di Shu & Jessica G. Young & Sengwee Toh & Rui Wang, 2021. "Variance estimation in inverse probability weighted Cox models," Biometrics, The International Biometric Society, vol. 77(3), pages 1101-1117, September.
    8. Angrist, Joshua D & Krueger, Alan B, 1995. "Split-Sample Instrumental Variables Estimates of the Return to Schooling," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 225-235, April.
    9. Fong, Christian & Tyler, Matthew, 2021. "Machine Learning Predictions as Regression Covariates," Political Analysis, Cambridge University Press, vol. 29(4), pages 467-484, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius, 2022. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 138-155, October.
    2. Felix Chopras & Ingar Haaland & Christopher Roth, 2024. "The Demand for News: Accuracy Concerns Versus Belief Confirmation Motives," The Economic Journal, Royal Economic Society, vol. 134(661), pages 1806-1834.
    3. Kasy, Maximilian, 2011. "A nonparametric test for path dependence in discrete panel data," Economics Letters, Elsevier, vol. 113(2), pages 172-175.
    4. Pablo Lavado & Gonzalo Rivera, 2016. "Identifying Treatment Effects with Data Combination and Unobserved Heterogeneity," Working Papers 79, Peruvian Economic Association.
    5. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    6. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    7. Marco Manacorda & Andrea Tesei, 2020. "Liberation Technology: Mobile Phones and Political Mobilization in Africa," Econometrica, Econometric Society, vol. 88(2), pages 533-567, March.
    8. Lemos Sara, 2005. "Political Variables as Instruments for the Minimum Wage," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 4(1), pages 1-31, December.
    9. Cruces, Guillermo & Galiani, Sebastian, 2007. "Fertility and female labor supply in Latin America: New causal evidence," Labour Economics, Elsevier, vol. 14(3), pages 565-573, June.
    10. Doko Tchatoka, Firmin & Dufour, Jean-Marie, 2020. "Exogeneity tests, incomplete models, weak identification and non-Gaussian distributions: Invariance and finite-sample distributional theory," Journal of Econometrics, Elsevier, vol. 218(2), pages 390-418.
    11. Yoici Arai & Taisuke Otsu & Mengshan Xu, 2022. "GLS under monotone heteroskedasticity," STICERD - Econometrics Paper Series 625, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. Bénédicte Apouey & Gabriel Picone, 2014. "Social Interactions And Malaria Preventive Behaviors In Sub‐Saharan Africa," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 994-1012, September.
    13. Ashesh Rambachan & Jonathan Roth, 2020. "Design-Based Uncertainty for Quasi-Experiments," Papers 2008.00602, arXiv.org, revised Oct 2024.
    14. Cantarella, Michele & Strozzi, Chiara, 2019. "Workers in the Crowd: The Labour Market Impact of the Online Platform Economy," IZA Discussion Papers 12327, Institute of Labor Economics (IZA).
    15. Debashis Ghosh, 2004. "Semiparametric methods for the binormal model with multiple biomarkers," The University of Michigan Department of Biostatistics Working Paper Series 1046, Berkeley Electronic Press.
    16. Megan T Stevenson, 2018. "Distortion of Justice: How the Inability to Pay Bail Affects Case Outcomes," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 34(4), pages 511-542.
    17. Brian D. Williamson & Peter B. Gilbert & Marco Carone & Noah Simon, 2021. "Nonparametric variable importance assessment using machine learning techniques," Biometrics, The International Biometric Society, vol. 77(1), pages 9-22, March.
    18. Arie Beresteanu & Francesca Molinari, 2008. "Asymptotic Properties for a Class of Partially Identified Models," Econometrica, Econometric Society, vol. 76(4), pages 763-814, July.
    19. Patrick Bayer & Fernando Ferreira & Stephen L. Ross, 2018. "What Drives Racial and Ethnic Differences in High-Cost Mortgages? The Role of High-Risk Lenders," The Review of Financial Studies, Society for Financial Studies, vol. 31(1), pages 175-205.
    20. Laurent Davezies & Xavier D'Haultfoeuille & Yannick Guyonvarch, 2018. "Asymptotic results under multiway clustering," Papers 1807.07925, arXiv.org, revised Aug 2018.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberch:14958. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.