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A Complex Model of Consumer Food Acquisitions: Applying Machine Learning and Directed Acyclic Graphs to the National Household Food Acquisition and Purchase Survey (FoodAPS)

Mark C. Senia, Senarath Dharmasena and Jessica Todd ()

No 266536, 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida from Southern Agricultural Economics Association

Abstract: Complex causal relationships among a large set of variables that affect the U.S. households’ food acquisition and purchase decisions were estimated using machine learning algorithms and directed acyclic graphs. Asians and Hispanics live in an environment with high concentrations of fast- and non-fast food restaurants. Obesity is less prevalent among Asians. Being Hispanic makes one to be more food insecure. Those with higher incomes are food secure and obesity is less prevalent among them. Being Black positively causes to be a SNAP participant and food insecure. Obesity is positively caused by fair/poor health and diet status.

Keywords: Consumer/Household Economics; Food Consumption/Nutrition/Food Safety (search for similar items in EconPapers)
Date: 2018-01-15
New Economics Papers: this item is included in nep-big and nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:ags:saea18:266536

DOI: 10.22004/ag.econ.266536

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