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Food environment in the United States as a complex economic system

Author

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  • Dharmasena, Senarath
  • Bessler, David A.
  • Capps, Oral

Abstract

The food environment in the United States is complex. Sixteen socio-economic-demographic variables from various public data sources are studied with a machine learning algorithm to ascertain the causality structure associated with the food environment in the United States. High levels of unemployment and poverty are direct causes of high levels of food insecurity, while low income causes high levels of food insecurity via increased levels of poverty. Unemployment is a common cause for both increased levels of food insecurity and poverty. We find that food insecurity and participation in Supplemental Nutrition Assistance Program (SNAP) are related, yet no direct causality is observed. Contrary to past studies which find that SNAP participation decreased the occurrences of poverty, in contemporaneous time, we find that poverty and SNAP participation are related through several back-door paths, via food insecurity, unemployment, race and food taxes. Obesity and SNAP participation are indirectly related via several back-door paths, namely, race income, poverty and food insecurity and unemployment. Also, food insecurity and obesity are related by several back-door paths. Low income, high food taxes, and race (being Black and non-Hispanic) are direct causes of obesity. The complex causality structure in the US food environment reveals that policy variables cannot be treated independently of their rich causal structure. Government agencies responsible for designing policies for food assistance, poverty alleviation, combating food insecurity and obesity need to consider the interrelationships among these variables.

Suggested Citation

  • Dharmasena, Senarath & Bessler, David A. & Capps, Oral, 2016. "Food environment in the United States as a complex economic system," Food Policy, Elsevier, vol. 61(C), pages 163-175.
    • Handle: RePEc:eee:jfpoli:v:61:y:2016:i:c:p:163-175
    DOI: 10.1016/j.foodpol.2016.03.003
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    3. Nayga, Jr., Rodolfo M. & Valizadeh, Pourya & Melo, Grace, 2022. "SNAP and well-being of low-income households with children before and during the pandemic," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322184, Agricultural and Applied Economics Association.
    4. Clare Y. Cho & Jill K. Clark, 2020. "Disparities in Access to Supplemental Nutrition Assistance Program Retailers Over Time and Space," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(1), pages 99-118, February.
    5. Galli, Francesca & Prosperi, Paolo & Favilli, Elena & D'Amico, Simona & Bartolini, Fabio & Brunori, Gianluca, 2020. "How can policy processes remove barriers to sustainable food systems in Europe? Contributing to a policy framework for agri-food transitions," Food Policy, Elsevier, vol. 96(C).
    6. Hawkins, Hannah & Dharmasena, Senarath, . "Price Discovery and Integration in U.S. Peanut Markets," Journal of Food Distribution Research, Food Distribution Research Society, vol. 51(1).
    7. Nathalie Mathieu‐Bolh, 2022. "The elusive link between income and obesity," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 935-968, September.
    8. Yongtong Shao & Tao Xiong & Minghao Li & Dermot Hayes & Wendong Zhang & Wei Xie, 2021. "China's Missing Pigs: Correcting China's Hog Inventory Data Using a Machine Learning Approach," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1082-1098, May.
    9. Seung Jin Cho, 2022. "The effect of aging out of the Women, Infants, and Children (WIC) program on food insecurity," Health Economics, John Wiley & Sons, Ltd., vol. 31(4), pages 664-685, April.
    10. Senia, Mark C. & Dharmasena, Senarath & Todd, Jessica E., 2018. "A Complex Model of Consumer Food Acquisitions: Applying Machine Learning and Directed Acyclic Graphs to the National Household Food Acquisition and Purchase Survey (FoodAPS)," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266536, Southern Agricultural Economics Association.

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    More about this item

    Keywords

    Food environment; Obesity; Poverty; Food insecurity; Food assistance; Directed acyclic graphs;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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