The Risk and Severity of Food Insecurity in V4 Countries: Insight from the Fuzzy Approach

Abstract

Food Insecurity (FI) is a complex phenomenon, therefore the traditional approach to its analysis, based on the rigid dichotomization between the food-secure and the food-insecure can oversimplify the real picture. The study proposes to consider FI as a degree rather than as an attribute. To do this, it employs a fuzzy approach widely applied in multidimensional poverty analysis. The study aims to identify correlates of FI in the V4 countries using the zero-inflated beta regression model. This model enables to understand the mechanisms behind the risk and the severity of FI in V4. The analysis based on the FIES data collected in the Gallup World Poll for 2018 indicates the role of income, household composition, and social capital as important correlates of FI. The risk of FI was also affected by age, level of education, gender, marital and employment status. Moreover, the study finds that the food insecurity profile exhibits country-specific effects.