Abstract
Forest dynamics are changing at a local and global level, with multiple social and environmental implications. The current literature points to different theories and hypotheses to explain these forest dynamics. In this paper, we formalized some of those theories, the environmental Kuznets curve (EKC), the forest transition and the ecologically unequal exchange, into hypotheses tested with a panel dataset covering 111 countries during the period the period 1992–2015. Considering the nature of our data, we relied on cointegration techniques to assess both long- and short-run dynamics in forest change, avoiding possible spurious results. Moreover, we attempted to disentangle direct and indirect effects of our independent variables to uncover the mechanisms that underly forest change dynamics. The results show that there is a long-run dynamic equilibrium relationship between forest cover area, economic development, agricultural area and rural population density. Furthermore, our results confirmed an EKC for high-income countries and post-forest transition countries, while low- and middle-income economies are experiencing different paths. We showed the importance of government quality as a positive feedback mechanism for previous periods of deforestation when tested for all countries together as well as for pre-transition and middle-income economies. Moreover, in low-income economies, economic development affects forest mainly indirectly through the agricultural area.
Highlights
Under the current global context of rapid land use changes, deforestation is one of the main processes at stake [1]
The stationarity tests of the variables forest cover, GDP, GDP2, agricultural area, and rural population density for income and forest transition clusters, respectively (Tables 2 and 3), showed that the variables are non-stationary of order 1, I(1), for GDP, GDP2, and agricultural area
Concerning rural population density, the results suggest an I(0) variable but the visual inspection of the data suggests that it can be considered as a non-stationary variable (Appendix F, Figure A12, Figure A13, Figure A14)
Summary
Under the current global context of rapid land use changes, deforestation is one of the main processes at stake [1]. Deforestation, as other land use and cover changes, take place at the plot level over short time periods but those changes act as elementary building blocks of complex and structural processes that take place over broader extents and longer time scales [4]. Following this perspective, we focus on theories that explain forest changes from such a structural point of view. We focus on cross-country studies using different statistical techniques [2,5,6,7,8,9,10]. Most of these studies used the well-known [11] forest cover datasets—in particular, the Forest Resource
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