IDEAS home Printed from https://ideas.repec.org/p/ags/uerstb/234905.html
   My bibliography  Save this paper

Understanding IRI Household-Based and Store-Based Scanner Data

Author

Listed:
  • Muth, Mary K.
  • Sweitzer, Megan
  • Brown, Derick
  • Capogrossi, Kristen
  • Karns, Shawn A.
  • Levin, David
  • Okrent, Abigail
  • Siegel, Peter
  • Zhen, Chen

Abstract

Commercial scanner data on retail food purchases are an integral resource for a broad range of food policy research. ERS has acquired proprietary household and retail scanner data from IRI, a market research firm, including novel data on nutrition information and health and wellness claims for a large number of products. This report provides a detailed description of the methodology, characteristics, and statistical properties of these datasets and summarizes the limitations and considerations for using these data for food economics research. The report shows that the IRI data are an extensive, complex data source and provides an introduction to the data for new users and important considerations for advanced users.

Suggested Citation

  • Muth, Mary K. & Sweitzer, Megan & Brown, Derick & Capogrossi, Kristen & Karns, Shawn A. & Levin, David & Okrent, Abigail & Siegel, Peter & Zhen, Chen, 2016. "Understanding IRI Household-Based and Store-Based Scanner Data," Technical Bulletins 234905, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uerstb:234905
    DOI: 10.22004/ag.econ.234905
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/234905/files/tb-1942.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.234905?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gary Solon & Steven J. Haider & Jeffrey M. Wooldridge, 2015. "What Are We Weighting For?," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 301-316.
    2. Leibtag, Ephraim S., 2006. "The Impact Of Big-Box Stores On Retail Food Prices And The Consumer Price Index," Economic Research Report 7238, United States Department of Agriculture, Economic Research Service.
    3. Chen Zhen & Eric A. Finkelstein & James M. Nonnemaker & Shawn A. Karns & Jessica E. Todd, 2014. "Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 1-25.
    4. Lin, Biing-Hwan & Smith, Travis A. & Lee, Jonq-Ying & Hall, Kevin D., 2011. "Measuring weight outcomes for obesity intervention strategies: The case of a sugar-sweetened beverage tax," Economics & Human Biology, Elsevier, vol. 9(4), pages 329-341.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dong, Diansheng & Stewart, Hayden & Dong, Xiao & Hahn, William, 2022. "Quantifying Consumer Welfare Impacts of Higher Meat Prices During the COVID-19 Pandemic," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, vol. 2022(Economic ), April.
    2. F. Kuchler & M. Bowman & M. Sweitzer & C. Greene, 2020. "Evidence from Retail Food Markets That Consumers Are Confused by Natural and Organic Food Labels," Journal of Consumer Policy, Springer, vol. 43(2), pages 379-395, June.
    3. Stewart, Hayden & Hyman, Jeffrey & McLaughlin, Patrick W. & Dong, Diansheng, 2019. "USDA Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): A New Look at Key Questions 10 Years After USDA Added Whole-Grain Bread to WIC Food Packages in 2009," Economic Research Report 335303, United States Department of Agriculture, Economic Research Service.
    4. Justin S White & Sanjay Basu & Scott Kaplan & Kristine A Madsen & Sofia B Villas-Boas & Dean Schillinger, 2023. "Evaluation of the sugar-sweetened beverage tax in Oakland, United States, 2015–2019: A quasi-experimental and cost-effectiveness study," PLOS Medicine, Public Library of Science, vol. 20(4), pages 1-20, April.
    5. Kirli, Desen & Couraud, Benoit & Robu, Valentin & Salgado-Bravo, Marcelo & Norbu, Sonam & Andoni, Merlinda & Antonopoulos, Ioannis & Negrete-Pincetic, Matias & Flynn, David & Kiprakis, Aristides, 2022. "Smart contracts in energy systems: A systematic review of fundamental approaches and implementations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    6. McLaughlin, Patrick W. & Stevens, Alexander & Dong, Xiao & Chelius, Carolyn & Marchesi, Keenan & MacLachlan, Matthew, 2022. "COVID-19 Working Paper National Trends in Food Retail Sales During the COVID-19 Pandemic: Findings from information Resources, Inc. (IRI) Retail-Based Scanner Data," USDA Miscellaneous 333527, United States Department of Agriculture.
    7. Matthew Freedman & Annemarie Kuhns, 2018. "Supply-side subsidies to improve food access and dietary outcomes: Evidence from the New Markets Tax Credit," Urban Studies, Urban Studies Journal Limited, vol. 55(14), pages 3234-3251, November.
    8. Elina T Page & Elizabeth Larimore & John A Kirlin & Mark Denbaly, 2019. "The National Household Food Acquisition and Purchase Survey: Innovations and Research Insights," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(2), pages 215-234, June.
    9. Chenarides, Lauren & Jaenicke, Edward C., 2016. "Store Choice and Consumer Behavior in Food Deserts: An Empirical Application of the Distance Metric Method," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235925, Agricultural and Applied Economics Association.
    10. Chenarides, Lauren & Jaenicke, Edward C. & Li, Jing, 2017. "Welfare Impacts from Store Attribute-Based Policy Interventions in an Urban Setting: An Application to Philadelphia," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258270, Agricultural and Applied Economics Association.
    11. Chen, Danhong & Jaenicke, Edward C., 2017. "Composition of Food-at-Home Expenditures and Childhood Obesity," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258343, Agricultural and Applied Economics Association.
    12. Ghazaryan, Armen & Bonanno, Alessandro & Carlson, Andrea, 2023. "I Say Milk, You Say Mylk. Demand Separability in a Broadened Milk Category," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 48(2), May.
    13. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    14. Carlson, Andrea C. & Waldrop, Megan, 2018. "Estimating Retail Organic Price Premiums for Snack Foods Using Scanner Data from 2013 to 2016," 2018 Annual Meeting, August 5-7, Washington, D.C. 274053, Agricultural and Applied Economics Association.
    15. Awad, Koroles & Ehmke, Mariah D. & McCluskey, Jill J. & Okrent, Abigail M., 2024. "Ultra-processed Food Demand across the Lifecycle: Implications for Obesity in the United States," 2024 Annual Meeting, July 28-30, New Orleans, LA 343976, Agricultural and Applied Economics Association.
    16. Lauren Chenarides & Edward C. Jaenicke, 2019. "Documenting the Link Between Poor Food Access and Less Healthy Product Assortment Across the U.S," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(3), pages 434-474, September.
    17. Cleary, Rebecca & Liu, Yizao & Carlson, Andrea C., 2022. "Differences in the Distribution of Nutrition Between Households Above and Below Poverty," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322267, Agricultural and Applied Economics Association.

    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. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    2. Juan Carlos Caro & Shu Wen Ng & Ricardo Bonilla & Jorge Tovar & Barry M Popkin, 2017. "Sugary drinks taxation, projected consumption and fiscal revenues in Colombia: Evidence from a QUAIDS model," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-16, December.
    3. Xiang, Di & Zhan, Lue & Bordignon, Massimo, 2020. "A reconsideration of the sugar sweetened beverage tax in a household production model," Food Policy, Elsevier, vol. 95(C).
    4. Lionel Cosnard, 2019. "Taxing Sugar and Sugary Products to Reduce Obesity: A CGE Assessment of Several Tax Policies," Post-Print hal-03148821, HAL.
    5. Alyssa J. Moran & Yuxuan Gu & Sasha Clynes & Attia Goheer & Christina A. Roberto & Anne Palmer, 2020. "Associations between Governmental Policies to Improve the Nutritional Quality of Supermarket Purchases and Individual, Retailer, and Community Health Outcomes: An Integrative Review," IJERPH, MDPI, vol. 17(20), pages 1-23, October.
    6. Cosnard, Lionel & Laborde, David, 2019. "Taxing Sugar and Sugary Products to Reduce Obesity: A CGE Assessment of Several Tax Policies," Conference papers 333067, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    7. Di Cosmo, Valeria & Tiezzi, Silvia, 2023. "Let them Eat Cake? The Net Consumer Welfare Impact of Sin Taxes," MPRA Paper 116214, University Library of Munich, Germany.
    8. Anurag Sharma & Katharina Hauck & Bruce Hollingsworth & Luigi Siciliani, 2014. "The Effects Of Taxing Sugar‐Sweetened Beverages Across Different Income Groups," Health Economics, John Wiley & Sons, Ltd., vol. 23(9), pages 1159-1184, September.
    9. Valeria di Cosmo & Silvia Tiezzi, 2025. "Fat vs. Sugar: The Case for a Saturated Fat Tax in Italy," Health Economics, John Wiley & Sons, Ltd., vol. 34(4), pages 727-740, April.
    10. Zhen, Chen & Chen, Yu & Lin, Biing-Hwan & Karns, Shawn & Mancino, Lisa & Ver Ploeg, Michele, 2021. "Do Obese and Nonobese Consumers Respond Differently to Price Changes? Implications of Preference Heterogeneity for Using Food Taxes and Subsidies to Reduce Obesity," MPRA Paper 112697, University Library of Munich, Germany.
    11. Massimo Bordignon & Di Xiang & Lue Zhan, 2018. "Predicting the Effects of a Sugar Sweetened Beverage Tax in a Household Production Model," DISCE - Working Papers del Dipartimento di Economia e Finanza def075, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    12. Li, Wenying & Dorfman, Jeffrey H., 2019. "The implications of heterogeneous habit in consumer beverage purchases on soda and sin taxes," Food Policy, Elsevier, vol. 84(C), pages 111-120.
    13. James Lake & Ding Liu, 2022. "Local Labor Market Effects of the 2002 Bush Steel Tariffs," CESifo Working Paper Series 9909, CESifo.
    14. David C. Ribar, 2015. "Is Leaving Home a Hardship?," Southern Economic Journal, John Wiley & Sons, vol. 81(3), pages 598-618, January.
    15. Greve, Jane & Heinesen, Eskil, 2015. "Evaluating the impact of a school-based health intervention using a randomized field experiment," Economics & Human Biology, Elsevier, vol. 18(C), pages 41-56.
    16. Sayeh S. Nikpay, 2020. "Entrepreneurship And Job Lock: The Interaction Between Tax Subsidies And Health Insurance Regulations," Contemporary Economic Policy, Western Economic Association International, vol. 38(1), pages 30-47, January.
    17. Rana, Pushpendra & Sills, Erin O., 2024. "Inviting oversight: Effects of forest certification on deforestation in the Brazilian Amazon," World Development, Elsevier, vol. 173(C).
    18. Andreas Lichter & Max Löffler & Sebastian Siegloch, 2021. "The Long-Term Costs of Government Surveillance: Insights from Stasi Spying in East Germany," Journal of the European Economic Association, European Economic Association, vol. 19(2), pages 741-789.
    19. Lindo, Jason M. & Swensen, Isaac D. & Waddell, Glen R., 2022. "Effects of violent media content: Evidence from the rise of the UFC," Journal of Health Economics, Elsevier, vol. 83(C).
    20. Jonathan Briody, 2020. "Parental Unemployment During the Great Recession and Childhood Adiposity," Working Papers 202002, Geary Institute, University College Dublin.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:ags:uerstb:234905. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/ersgvus.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.