Towards Improving Local Policy Responses to Food Insecurity: Exploratory and Predictive Analytics
Academic research and policy proposals that aim to alleviate food insecurity in the United States can benefit tremendously from new developments in analytics. Much academic literature has singled out predictors for food insecurity. However, the research so far often focuses on either the individual or the aggregated state or country level. Both levels of analysis are either too granular or too broad to inform public policy effectively. The research that does focus on medium-size units of analysis, on the other hand, lacks incorporation of non-linear effects at the community level. Our research aims at incorporating the literature of social capital to account for potential non-linearity. We propose a case study at the county level in North Carolina that can be extended to a national scale.
Tovar, Henning; Iyer, Lakshmi; and Chen, Charlie C., "Towards Improving Local Policy Responses to Food Insecurity: Exploratory and Predictive Analytics" (2019). Proceedings of the 2019 Pre-ICIS SIGDSA Symposium. 2.