IDEAS home Printed from https://ideas.repec.org/p/cen/wpaper/24-74.html
   My bibliography  Save this paper

The Privacy-Protected Gridded Environmental Impacts Frame

Author

Listed:
  • John Voorheis
  • Jonathan Colmer
  • Kendall Houghton
  • Eva Lyubich
  • Mary Munro
  • Cameron Scalera
  • Jennifer Withrow

Abstract

This paper introduces the Gridded Environmental Impacts Frame (Gridded EIF), a novel privacy-protected dataset derived from the U.S. Census Bureau’s confidential Environmental Impacts Frame (EIF) microdata infrastructure. The EIF combines comprehensive administrative records and survey data on the U.S. population with high-resolution geospatial information on environmental hazards. While access to the EIF is restricted due to the confidential nature of the underlying data, the Gridded EIF offers a broader research community the opportunity to glean insights from the data while preserving confidentiality. We describe the data and privacy protection process, and offer guidance on appropriate usage, presenting practical applications.

Suggested Citation

  • John Voorheis & Jonathan Colmer & Kendall Houghton & Eva Lyubich & Mary Munro & Cameron Scalera & Jennifer Withrow, 2024. "The Privacy-Protected Gridded Environmental Impacts Frame," Working Papers 24-74, Center for Economic Studies, U.S. Census Bureau.
    • Handle: RePEc:cen:wpaper:24-74
    as

    Download full text from publisher

    File URL: https://www2.census.gov/library/working-papers/2024/adrm/ces/CES-WP-24-74.pdf
    File Function: First version, 2024
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Illenin Kondo & Kevin Rinz & Natalie Gubbay & Brandon Hawkins & John Voorheis & Abigail Wozniak, 2024. "Granular Income Inequality and Mobility Using IDDA: Exploring Patterns across Race and Ethnicity," NBER Chapters, in: Race, Ethnicity, and Economic Statistics for the 21st Century, National Bureau of Economic Research, Inc.
    2. Raj Chetty & John N. Friedman, 2019. "A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 414-420, May.
    3. Jonathan M. Colmer & Suvy Qin & John L. Voorheis & Reed Walker, 2024. "Income, Wealth, and Environmental Inequality in the United States," NBER Working Papers 33050, National Bureau of Economic Research, Inc.
    4. John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Simson Garfinkel & Micah Heineck & Christine Heiss & Robert Johns & Daniel Kifer & Philip Leclerc & Ashwin Machanavajjhala & Brett Moran & William, 2022. "The 2020 Census Disclosure Avoidance System TopDown Algorithm," Papers 2204.08986, arXiv.org.
    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. Ron S. Jarmin & John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Nathan Goldschlag & Michael B. Hawes & Sallie Ann Keller & Daniel Kifer & Philip Leclerc & Jerome P. Reiter & Rolando A. Rodrígue, 2023. "An in-depth examination of requirements for disclosure risk assessment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(43), pages 2220558120-, October.
    2. Maggie R. Jones & Adam Bee & Amanda Eng & Kendall Houghton & Nikolas Pharris-Ciurej & Sonya R. Porter & Jonathan Rothbaum & John Voorheis, 2024. "Mobility, Opportunity, and Volatility Statistics (MOVS): Infrastructure Files and Public Use Data," Working Papers 24-23, Center for Economic Studies, U.S. Census Bureau.
    3. Braathen, Christian & Thorsen, Inge & Ubøe, Jan, 2022. "Adjusting for Cell Suppression in Commuting Trip Data," Discussion Papers 2022/13, Norwegian School of Economics, Department of Business and Management Science.
    4. Michler, Jeffrey D. & Josephson, Anna & Kilic, Talip & Murray, Siobhan, 2022. "Privacy protection, measurement error, and the integration of remote sensing and socioeconomic survey data," Journal of Development Economics, Elsevier, vol. 158(C).
    5. Vilhuber, Lars, 2023. "Reproducibility and transparency versus privacy and confidentiality: Reflections from a data editor," Journal of Econometrics, Elsevier, vol. 235(2), pages 2285-2294.
    6. Craig Wesley Carpenter & Anders Van Sandt & Scott Loveridge, 2022. "Measurement error in US regional economic data," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 57-80, January.
    7. Joshua Graff Zivin & Gregor Singer, 2024. "Disparities in Pollution Capitalization Rates: The Role of Direct & Systemic Discrimination," CESifo Working Paper Series 11555, CESifo.
    8. Atheendar S Venkataramani & Rourke O’Brien & Gregory L Whitehorn & Alexander C Tsai, 2020. "Economic influences on population health in the United States: Toward policymaking driven by data and evidence," PLOS Medicine, Public Library of Science, vol. 17(9), pages 1-17, September.
    9. Ian M. Schmutte & Nathan Yoder, 2022. "Information Design for Differential Privacy," Papers 2202.05452, arXiv.org, revised Jul 2024.
    10. Dionissi Aliprantis & Hal Martin, 2020. "Neighborhood Sorting Obscures Neighborhood Effects in the Opportunity Atlas," Working Papers 20-37, Federal Reserve Bank of Cleveland.
    11. Yue Lin & Ningchuan Xiao, 2023. "Assessing the Impact of Differential Privacy on Population Uniques in Geographically Aggregated Data: The Case of the 2020 U.S. Census," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 42(5), pages 1-20, October.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cen:wpaper:24-74. 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: Dawn Anderson (email available below). General contact details of provider: https://edirc.repec.org/data/cesgvus.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.