Probit Model And Simulation Analysis Paper

1062 Words 4 Pages
Using probit modeling and simulation analysis this paper sought to answer two research questions: (1) What are the effects of changing demographic characteristics on SNAP participation among seniors? and (2) What are the effects of the differential geographic distribution in terms of exposure to economic conditions, food and non-food policy characteristics on SNAP among seniors? This paper finds that state economic conditions make up over 71.54% of the change in SNAP participation while state food policy conditions are not as important, comprising 3.54%, and state nonfood policy playing a moderate role, comprising 32.84% of participation, all three by dampening the growth in participation. Although seniors population is changing in composition …show more content…
This presents an opportunity think about further about geography as an important component in SNAP participation and food insecurity. There is a strong correlation between residing in the South and food insecurity for seniors. The South has 9 out of 10 states with the highest rate of food insecurity in the country. Alabama, Arkansas, District of Columbia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, and Texas have a considerably higher rate of food insecurity. Among seniors in Mississippi, the rate of food insecurity was between 10.3% and 16.8% in 2013, this was the highest rate in our country. Not far behind, Arkansas had a rate of 15.1% food insecurity among seniors. Other Southern states like Texas, Louisiana, Tennessee, Missouri, and North Carolina fall between 11% and 13.6% (Strickhouser, Wright & Donley, 2014). As the rates food insecurity have doubled for the aging and as some of the growing demographic characteristics of the aging population have the highest risks of food insecurity, the use of a nutrition program, like SNAP, is critical to …show more content…
There is a need for more research on how to more comprehensively understand why and how geographic and demographic characteristics are effecting senior participation. Understanding how geographic location, particularly State macroeconomics and policies, will be interesting to further examine as they are often not part of the local labor market and are frequently thought of as a more stable in their location. Additionally, the new senior population will have demographic characteristics much different to those in the past. Therefore, research on individual demographic characteristics of seniors and their participation rates in SNAP, like geography, will be critical in finding the best and most effective ways to target SNAP outreach and policies to reach this vulnerable

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