Forecasting forest areas and carbon stocks in Cambodia based on socio-economic factors

Michinaka, Tetsuya; Maeda, Mitsuo; Miyamoto, Motoe; Yokota, Yozo; Sokh, Heng; Lao, Sethaphal; Tsukada, Naoko; Matsuura, T.; Ma, Vuthy

doi:10.1505/146554815814725103

Cited by 2 publications

(3 citation statements)

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“…As a result of the deeper deforestation from 2010 to 2014, the actual forest area is lower than the forecast, and the error is 9.56% for 2014 based on the 2014 forecast. This is a large error even though the actual values are within the range of the FI at the 95% level calculated in the forecast [31]. The forecast deforestation between 2014 and 2016 is 0.22 million ha and the actual deforestation in the same period is 0.25 million ha, leading to a small error of 0.33% based on the 2014 actual forest areas.…”

Section: Discussionmentioning

confidence: 82%

“…Among the small amount of literature on forecasting forest areas, Michinaka et al forecasted forest areas for Cambodia from 2011 through 2018 by using the provincial panel data in 2002, 2006, and 2010 [31]. The forecasts for 2014 and 2016 were, respectively, 9.94 and 9.72 million ha, but the actual forest areas were 8.99 and 8.74 million ha in the corresponding years.…”

Section: Discussionmentioning

confidence: 99%

“…Panel data analysis, an econometrics approach, was adopted in the research. Panel data analysis has been widely used in analyzing deforestation issues (e.g., [20,30,31,47]). For developing countries, long time-series data are usually not available.…”

Section: Methodsmentioning

confidence: 99%

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Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors

Michinaka

Hlaing

et al. 2020

Forests

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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.

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Section: Discussionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%