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Fishing grounds footprint and economic freedom indexes: Evidence from Asia-Pacific.

Sajjad AminChuang LiYousaf Ali KhanAmina Bibi
Published in: PloS one (2022)
Environmental challenges are as wide as the universe so that its different dimensions can be the subject of diverse studies. In this research, using 17 data from Asia-Pacific during the period 2000 to 2017, an attempt has been made to investigate the economic factors responsible for the ecological footprint in the fishing sector. The main contribution of the present study is to investigate the effects of nine economic freedom indicators along with other control variables on environmental pressure on the status of fishery resources. Based on the results, the Kuznets curve hypothesis was confirmed in the fishing grounds footprint, so that the growth of GDP per capita shows a positive and significant effect, while its squared form coefficient is negative. Other control variables including natural resource rents, urbanization, and energy intensity, do not show significant effects on the fishing footprint. The different components of economic freedom show different effects, while their cumulative effects in the form of the total economic freedom index have a positive effect on the footprint of fishing and lead to increased extraction from fishing resources. The results show that the Government Integrity, Tax Burden, Business Freedom, Monetary Freedom indices increase the fishing footprint, while the indices of trade freedom and investment freedom, by revealing the negative effects on the fishing footprint, have beneficial environmental effects in reducing the pressure on the aquatic resources of countries. The results of the present study reveal the need to examine how the various dimensions of economic freedom affect to provide the proper management of fishery resources.
Keyphrases
  • life cycle
  • human health
  • risk assessment
  • climate change
  • gene expression
  • electronic health record
  • genome wide
  • magnetic resonance
  • big data
  • machine learning
  • single cell
  • dna methylation
  • case control