Analyzing Forest Land and Environmental Degradation: Evidence From Land Management in Low‐Income, Degraded Ecosystem Economies

ABSTRACT The impact of economic growth on carbon emissions plays a crucial role in shaping national development strategies, particularly in low‐income Asian countries where economic transformation is driving employment, foreign exchange earnings, and overall development. This study explores the relationship between economic expansion and CO 2 emissions in low‐income Asian countries from 2001 to 2020, using advanced analytical methods including multiple regression, moment quantile regression, and wavelet analysis to identify threshold points for sustainable development. Key factors such as forest area, natural resource rents, foreign direct investment (FDI), population density, and GDP are analyzed for their influence on CO 2 emissions. The moment quantile regression results show that forest area and natural resource rents have a significant positive effect on CO 2 emissions, particularly at higher quantiles, indicating intensified environmental pressure with industrialization. The heterogeneous impacts of FDI, GDP, and population density across quantiles suggest that their influence varies by development stage. Further, wavelet transform coherence (WTC) analysis reveals strong co‐movements between emissions and economic indicators, especially FDI, while cross wavelet transform (XWT) results confirm that increases in FDI and GDP often precede higher emissions, underscoring the growth–emissions trade‐off in low‐income Asian economies. To mitigate these effects, the study proposes strategies such as promoting green infrastructure, fostering eco‐friendly development, and implementing carbon offset programs, complemented by robust regulations and digital technologies. These measures can help reduce environmental impact while supporting continued economic growth in these nations.