Carbon dioxide emissions, forest area, and economic growth of SAARC countries: Evidence from FMOLS approach
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Author(s)Yadav Mani UpadhyayaLink to ORCID Index: https://orcid.org/0000-0003-3089-3615
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Khom Raj KharelLink to ORCID Index: https://orcid.org/0000-0002-9806-7224
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Omkar PaudelLink to ORCID Index: https://orcid.org/0000-0001-9678-4943
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Pramshu NepalLink to ORCID Index: https://orcid.org/0009-0009-7116-636X
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DOIhttp://dx.doi.org/10.21511/ee.16(1).2025.02
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Article InfoVolume 16 2025, Issue #1, pp. 13-29
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Creative Commons Attribution 4.0 International License
This study aims to examine the relationship between CO2 emissions, forest area, and GDP in each South Asian Association for Regional Cooperation (SAARC) country. This study uses a panel dataset that spans South Asian countries from 1990 to 2020 for econometric analysis. The Fully Modified Least Squares (FMOLS) method adds annual forested area to the regression model. The study results show that India, Nepal, Pakistan, and Sri Lanka must prioritize decoupling CO2 emissions from economic growth, as their strong correlation shows significant environmental costs of development. Although Bangladesh, Bhutan, and the Maldives are in a slightly better position, they need strategies to manage emissions as they progress economically. The study once again revealed a relationship between a 1% increase in GDP and a 0.68% rise in CO2 emissions, whereas a 1% increase in forest area led to a slightly higher 0.79% rise in CO2 over the period. The hypotheses testing results confirm a positive correlation between economic growth and carbon dioxide emissions in SAARC countries, indicating that emissions rise as economies expand. Additionally, a negative relationship was found between forest area and carbon dioxide emissions, where larger forest coverage is linked to lower emissions. The conclusion is that an increase in forest area is associated with a relatively small increase in CO2 emissions, indicating that the relationship between forest area and CO2 emissions is less pronounced compared to GDP.
- Keywords
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JEL Classification (Paper profile tab)Q56, Q54, O13, O53
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References50
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Tables7
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Figures0
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- Table 1. Country’s GDP and CO2 emissions relationship
- Table 2. Panel unit root test results for key variables
- Table 3. Unrestricted cointegration rank test (Trace and maximum eigenvalue)
- Table 4. Pairwise Granger causality tests with lags 1
- Table 5. Regression analysis results for the impact of GDP and foreign assets on the dependent variable
- Table 6. Regression analysis results for LNGDP and LNFA as predictors of the dependent variable
- Table A1. CO2, forest area, and economic growth of SAARC countries
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