IDEAS home Printed from https://ideas.repec.org/p/ags/uersrr/327182.html
   My bibliography  Save this paper

Understanding the Components of U.S. Food Expenditures During Recessionary and Non-Recessionary Periods

Author

Listed:
  • Zeballos, Eliana
  • Sinclair, Wilson
  • Park, Timothy

Abstract

ERS analysis shows that during the COVID-19 Recession, while total food expenditures fell, food spending at places like grocery stores and supercenters increased. This increase in food-at-home spending was mostly driven by a shift away from food spending at places like restaurants and fast-food places.

Suggested Citation

  • Zeballos, Eliana & Sinclair, Wilson & Park, Timothy, 2021. "Understanding the Components of U.S. Food Expenditures During Recessionary and Non-Recessionary Periods," Economic Research Report 327182, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uersrr:327182
    DOI: 10.22004/ag.econ.327182
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/327182/files/err-301.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.327182?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Greg Kaplan & Guido Menzio, 2015. "The Morphology Of Price Dispersion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(4), pages 1165-1206, November.
    2. Aviv Nevo & Arlene Wong, 2019. "The Elasticity Of Substitution Between Time And Market Goods: Evidence From The Great Recession," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(1), pages 25-51, February.
    3. Wei Li & Xifeng Wang & Jiahong Liu & Yangwen Jia & Yaqin Qiu, 2019. "Decomposing the Driving Factors of Water Use in China," Sustainability, MDPI, vol. 11(8), pages 1-13, April.
    4. Greg Kaplan & Guido Menzio, 2015. "The Morphology Of Price Dispersion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1165-1206, November.
    5. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    6. Saksena, Michelle J. & Okrent, Abigail M. & Anekwe, Tobenna D. & Cho, Clare & Dicken, Christopher & Effland, Anne & Elitzak, Howard & Guthrie, Joanne & Hamrick, Karen S. & Hyman, Jeffrey & Jo, Young &, 2018. "America’s Eating Habits:Food Away From Home," Economic Information Bulletin 281119, United States Department of Agriculture, Economic Research Service.
    7. Zhang, Youguo, 2009. "Structural decomposition analysis of sources of decarbonizing economic development in China; 1992-2006," Ecological Economics, Elsevier, vol. 68(8-9), pages 2399-2405, June.
    8. ZAHlD SAEED, 1976. "Growth of Crop Output in Pakistan-An Analysis by Component Elements," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 15(3), pages 319-329.
    9. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    10. Munksgaard, Jesper & Pedersen, Klaus Alsted & Wien, Mette, 2000. "Impact of household consumption on CO2 emissions," Energy Economics, Elsevier, vol. 22(4), pages 423-440, August.
    11. Ang, B.W. & Liu, F.L. & Chung, Hyun-Sik, 2004. "A generalized Fisher index approach to energy decomposition analysis," Energy Economics, Elsevier, vol. 26(5), pages 757-763, September.
    12. Betts, Julian R., 1989. "Two exact, non-arbitrary and general methods of decomposing temporal change," Economics Letters, Elsevier, vol. 30(2), pages 151-156, August.
    13. Okrent, Abigail M. & Elitzak, Howard & Park, Timothy & Rehkamp, Sarah, 2018. "Measuring the Value of the U.S. Food System: Revisions to the Food Expenditure Series," Technical Bulletins 277568, United States Department of Agriculture, Economic Research Service.
    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. Patrick W. McLaughlin & Alexander Stevens & Shawn Arita & Xiao Dong, 2023. "Stocking up and stocking out: Food retail stock‐outs, consumer demand, and prices during the COVID‐19 pandemic in 2020," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1618-1633, September.
    2. Zeballos, Eliana & Sinclair, Wilson J. & Marchesi, Keenan, 2023. "The Effect of COVID-19 on Food Sales at the State Level," 2023 Annual Meeting, July 23-25, Washington D.C. 335543, Agricultural and Applied Economics Association.
    3. Clement O. Codjia & Sayed H. Saghaian, 2022. "Determinants of Food Expenditure Patterns: Evidence from U.S. Consumers in the Context of the COVID-19 Price Shocks," Sustainability, MDPI, vol. 14(13), pages 1-17, July.
    4. Okrent, Abigail & Zeballos, Eliana, 2022. "COVID-19 Working Paper: Consumer Food Spending Changes During the COVID-19 Pandemic," USDA Miscellaneous 333545, United States Department of Agriculture.

    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. Gui, Shusen & Mu, Hailin & Li, Nan, 2014. "Analysis of impact factors on China's CO2 emissions from the view of supply chain paths," Energy, Elsevier, vol. 74(C), pages 405-416.
    2. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    3. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    4. Wu, Sanmang & Li, Shantong & Lei, Yalin & Li, Li, 2020. "Temporal changes in China's production and consumption-based CO2 emissions and the factors contributing to changes," Energy Economics, Elsevier, vol. 89(C).
    5. Xie, Rui & Wang, Fangfang & Chevallier, Julien & Zhu, Bangzhu & Zhao, Guomei, 2018. "Supply-side structural effects of air pollutant emissions in China: A comparative analysis," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 89-95.
    6. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    7. Wang, Qiang & Han, Xinyu, 2021. "Is decoupling embodied carbon emissions from economic output in Sino-US trade possible?," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    8. Hu, Yi & Yin, Zhifeng & Ma, Jian & Du, Wencui & Liu, Danhe & Sun, Luxi, 2017. "Determinants of GHG emissions for a municipal economy: Structural decomposition analysis of Chongqing," Applied Energy, Elsevier, vol. 196(C), pages 162-169.
    9. Luigi Paciello & Andrea Pozzi & Nicholas Trachter, 2019. "Price Dynamics With Customer Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(1), pages 413-446, February.
    10. Su, Bin & Ang, B.W., 2014. "Attribution of changes in the generalized Fisher index with application to embodied emission studies," Energy, Elsevier, vol. 69(C), pages 778-786.
    11. Banie Naser Outchiri, 2020. "Contributing to better energy and environmental analyses: how accurate are decomposition analysis results?," Cahiers de recherche 20-11, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    12. Fernando Bermejo & Raúl del Pozo & Pablo Moya, 2021. "Main Factors Determining the Economic Production Sustained by Public Long-Term Care Spending in Spain," IJERPH, MDPI, vol. 18(17), pages 1-18, August.
    13. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    14. Tan, Ruipeng & Lin, Boqiang, 2018. "What factors lead to the decline of energy intensity in China's energy intensive industries?," Energy Economics, Elsevier, vol. 71(C), pages 213-221.
    15. Das, Aparna & Paul, Saikat Kumar, 2014. "CO2 emissions from household consumption in India between 1993–94 and 2006–07: A decomposition analysis," Energy Economics, Elsevier, vol. 41(C), pages 90-105.
    16. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    17. Wang, Zhenguo & Su, Bin & Xie, Rui & Long, Haiyu, 2020. "China’s aggregate embodied CO2 emission intensity from 2007 to 2012: A multi-region multiplicative structural decomposition analysis," Energy Economics, Elsevier, vol. 85(C).
    18. Zhu, Bangzhu & Su, Bin & Li, Yingzhu, 2018. "Input-output and structural decomposition analysis of India’s carbon emissions and intensity, 2007/08 – 2013/14," Applied Energy, Elsevier, vol. 230(C), pages 1545-1556.
    19. Messner, Teresa & Rumler, Fabio & Strasser, Georg, 2022. "Cross-country price and inflation dispersion: Retail network or national border," Single Market Economics Papers WP2022/11, Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (European Commission), Chief Economist Team.
    20. Lin Boqiang & Kui Liu, 2017. "Using LMDI to Analyze the Decoupling of Carbon Dioxide Emissions from China’s Heavy Industry," Sustainability, MDPI, vol. 9(7), pages 1-16, July.

    More about this item

    Keywords

    Consumer/Household Economics;

    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:uersrr:327182. 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.