Countries in the Middle East and North Africa (MENA) have been facing serious environmental issues due to over-exploitation of natural resources. This paper analyzes the ecological footprint as a proxy of environmental degradation and determines its influencing factors in 18 MENA countries during 2000–2016. Despite the many studies on the relationship between the ecological footprint and its determinants in the region, the current study use spatial econometric models to take into account spatial dependence in the ecological footprint as well as its determinants. Using a spatial Durbin model, we revealed that neighbors’ behavior can significantly affect a country’s ecological footprint. Factors such as GDP per capita, trade openness, and financial development were found to increase environmental degradation, while the renewable energy consumption, urbanization, and quality of democracy effectively reduce the ecological footprint. These factors not only affect the ecological footprint in the host country, but also affect it in the adjacent countries in different ways. Due to the interdependence of the countries, we recommend development of a regional vision of the bio-economy such that the scope of the analysis goes beyond the country level to account for territorial effects. Furthermore, considering the great potential for renewable energy consumption in the region, we recommend MENA countries to develop use of renewable energy sources in order to reduce environmental degradation in the region.

The cultivation of saffron, which is one of the most expensive agricultural products in the world, is the main source of livelihood and economic wellbeing for the rural communities of Gonabad county in the eastern part of Iran. Nevertheless, farm monitoring in the region has shown that many saffron growers apply a high-density planting system for more profit. This practice results in the loss of land productivity after a six-year production cycle. As a consequence, farmers abandon the cultivated lands and move to plant saffron in available virgin lands. The purpose of this study is to analyse the technical efficiency of saffron farms and its determinants with an emphasis on the role of planting density. A survey was conducted in 2019, and a cross-sectional random sampling technique was used to select 110 saffron growers. We first assessed the technical efficiency of farms using a data envelopment analysis (DEA) model with input orientation. In the next step, efficiency scores were regressed on explanatory variables using OLS and bootstrapped truncated regression to identify efficiency related factors. We find that planting density negatively influenced technical efficiency, suggesting that it is necessary for saffron growers to be educated on the negative impacts of the dense planting system.