Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors

Tetsuya Michinaka,Thaung Oo,Ei Hlaing,Myat Mon,Tamotsu Sato

doi:10.3390/f11010100

Abstract

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.

Highlights

As a partner country in the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD Programme), Myanmar submitted and revised a proposed national forest reference level (FRL) to the United Nations Framework Convention on Climate Change (UNFCCC) in 2018, and the report of the technical assessment to the submission was issued in 2019 [1,2].The proposed FRL reflected an annual average level of emissions from deforestation from 2005 to2015
According to the results in items (2) and (3), both fixed effects (FE) and random effects (RE) models are better than the pooled model at the 1%
A high standard error and p-value but a low z-score for POP in model 1 failed to reject the null hypothesis that the coefficient is different from zero

Summary

Introduction

As a partner country in the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD Programme), Myanmar submitted and revised a proposed national forest reference level (FRL) to the United Nations Framework Convention on Climate Change (UNFCCC) in 2018, and the report of the technical assessment to the submission was issued in 2019 [1,2].The proposed FRL reflected an annual average level of emissions from deforestation from 2005 to2015. As a partner country in the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD Programme), Myanmar submitted and revised a proposed national forest reference level (FRL) to the United Nations Framework Convention on Climate Change (UNFCCC) in 2018, and the report of the technical assessment to the submission was issued in 2019 [1,2]. The proposed FRL reflected an annual average level of emissions from deforestation from 2005 to. The national circumstances of socioeconomic development were not considered in the proposed FRL. Deforestation is a phenomenon that takes place under specific national circumstances. This research tries to provide scenarios of forest resources for the near future by considering this socioeconomic development

Methods

Results

Discussion

Conclusion