Green Trade, Economic Complexity and Green Indicators: Evidence in Asia Countries with PPML Fixed Effects Model

This study investigates the relationship between green trade, economic complexity, and green indicators in Asian countries using a Poisson Pseudo Maximum Likelihood (PPML) fixed effects model. This study uses panel data from 33 countries in the Asia region, focusing on the national level of each country from 2010 to 2023. The analysis explores how economic sophistication and environmental indicators influence the capacity of economies to engage in sustainable trade. The findings reveal that economic complexity significantly enhances green trade, underscoring the role of knowledge-intensive production structures in fostering environmentally friendly export performance. Among the green indicators, green economic opportunities demonstrate a positive and significant effect on green trade, which indicates that economies allocating greater financial resources to renewable energy and sustainable infrastructure are better positioned to expand their participation in eco-friendly markets. This signals strong trade readiness and market-driven incentives. Conversely, green innovation shows a negative and significant effect, indicating that innovation is not yet translating into export competitiveness, is still costly, and is in an early phase. Moreover, economic complexity and renewable energy show positive and significant effects, reflecting that higher complexity enables the adoption of green technologies, the embedding of sustainability in value chains, and the export of high-value green products. These results suggest that green economic opportunities and regional dynamics play a complementary role in shaping outcomes, with proximity to innovation hubs amplifying the capacity for sustainable trade. The study contributes to the literature by linking economic complexity with green trade in the Asian context, offering evidence-based recommendations to enhance sustainability-driven growth.