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Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors
National circumstances should be considered in establishing and adjusting forest reference emission levels (FRELs/FRLs) under the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+ Programme). Myanmar, one of the world’s least developed countries may face accelerating deforestation under an open and democratic political system that desires rapid economic development. This research analyzes the impacts of population growth and economic development on forest areas in Myanmar by using panel data analysis, an econometrics approach based on panel data of forest areas, population, and gross domestic product (GDP) by states and regions in 2005, 2010, and 2015. This research revealed that per capita GDP and population density gave statistically significant negative impacts on forest areas. Using the regression model obtained above, medium population growth projections, and three GDP development scenarios, annual forest areas from 2016 to 2020 were forecast. The forecasting results showed possible higher deforestation under higher economic development. Finally, this research showed the necessity of adjusting the current average deforestation for RELs in the REDD+ scheme in Myanmar and the direction in which the adjustment should go.
Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors
National circumstances should be considered in establishing and adjusting forest reference emission levels (FRELs/FRLs) under the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+ Programme). Myanmar, one of the world’s least developed countries may face accelerating deforestation under an open and democratic political system that desires rapid economic development. This research analyzes the impacts of population growth and economic development on forest areas in Myanmar by using panel data analysis, an econometrics approach based on panel data of forest areas, population, and gross domestic product (GDP) by states and regions in 2005, 2010, and 2015. This research revealed that per capita GDP and population density gave statistically significant negative impacts on forest areas. Using the regression model obtained above, medium population growth projections, and three GDP development scenarios, annual forest areas from 2016 to 2020 were forecast. The forecasting results showed possible higher deforestation under higher economic development. Finally, this research showed the necessity of adjusting the current average deforestation for RELs in the REDD+ scheme in Myanmar and the direction in which the adjustment should go.
Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors
Tetsuya Michinaka (author) / Ei Ei Swe Hlaing (author) / Thaung Naing Oo (author) / Myat Su Mon (author) / Tamotsu Sato (author)
2020
Article (Journal)
Electronic Resource
Unknown
deforestation , gdp , population , myanmar , panel data analysis , forecast , Plant ecology , QK900-989
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