This paper aims to test the existence of an unconditional hunger trap and to determine whether biofuel production is among the key long-term determinants of food insecurity. Therefore, we consider the Markov transition matrix and ergodic distribution to test the hypothesis of an unconditional hunger trap and then the conditional inference regression tree to identify the key drivers of food insecurity. We find that developing countries are not caught in a hunger trap. The result of the transition matrix shows that all countries with high levels of food insecurity can move to a lower level. Furthermore, given the characteristics of the countries, the conditional inference regression tree results show that the most important variable is gross domestic product (GDP) per capita. However, in addition to this variable, we need to include the level of age dependency ratio, precipitation, socioeconomic conditions, and corruption index for countries with high levels of food insecurity. Considering the overall sample and sub-samples of low and high food insecure countries, biofuel production is not part of the long-term determinants. The results of the boosting model and panel data quantile regression reveal that the influence of biofuels seems very weak, meaning that they can be a way to fight climate change without penalizing food security.