Determinants of fishing grounds footprint: Evidence from dynamic spatial Durbin model.

Despite a growing literature on fishing grounds footprint, there is no study analyzing fishing footprint regarding spatial effects between neighboring countries. Thus, we explored whether the fishing grounds footprint of 156 countries is spatially correlated. For this purpose, we applied the dynamic spatial Durbin model to examine the direct and indirect effects of GDP per capita, biological capacity, trade openness, population, and urbanization on fishing grounds footprint in the short-term and the long-term during 2001–2021. The results revealed that: (1) there exists a positive and significant spatial dependence in fishing grounds footprint between countries; (2) inverted U-shaped environmental Kuznets curve hypothesis is valid in the short-term and the long-term; (3) fishing grounds footprint is negatively influenced by biocapacity and urbanization in neighboring countries, while population directly increases the fishing footprint. Finally, some suggestions were put forward to reduce fishing grounds footprint and to achieve a sustainable fisheries environment. [Display omitted] • The main determinants of fishing grounds footprint for 156 countries are investigated in this research. • Dynamic spatial Durbin model was applied to estimate the direct, indirect and total effects of fishing grounds footprint determinants. • There is a significant spatial dependence in fishing grounds footprint. • Inverted U-shaped EKC was found for the relationship between GDP per capita and fishing footprints. [ABSTRACT FROM AUTHOR]