Investigating the effects of climatic and economic variables on forest degradation of Iran

Abstract

In this study, in order to investigate the effects of climatic-economic variables on the degradation of forests in Iran, the Autoregressive Distributed-lagged model (ARDL) has been applied during the period from 1991 to 2014. The results of the short-term estimation revealed that the dependent variable is significant at the 10% level and also, according to the "Bannerji statistics", the long-term relationship between the variables is confirmed. Long-term model results reveal that the per capita income has a negative sign which is significant at 1% level. The second-power variable has a positive sign which is significant at 1% level, in other words, there is U-shaped relationship between the degradation of forest and per capita income, which means that Kuznets's environmental hypothesis is not in line with the degradation of forests in Iran. Moreover, the elasticity of per capita income reveals that with a one percent increase in per capita income, the degradation of forest will decline by 4.03 percent. Considering that per capita income is derived from GDP into the population, therefore, in order to achieve the least degradation in the relationship between per capita income and deforestation, it is recommended to pay attention to environmental considerations in domestic production. In other words, considering green accounting, in addition to importing forest income, forest degradation costs are also included. In case of harvesting, the conditions of planting and restoration should be considered. It is also suggested that in the field of population, demographic policies should also be oriented towards the proportionate populations with resources. Also, the variables of rainfall to temperature ratio and the second power of precipitation to temperature ratio have negative and positive signs respectively. In other words, there is a U-shaped relationship between forest degradation and precipitation to temperature.

Keywords

• auto regressive distributed lag
• deforestation
• economic-climate variables
• iranian forests.‌‌‌