The effect of economic complexity on income levels across countries: A dynamic panel quantile approach

Purpose — This study investigates the impact of economic complexity on income levels across countries at different stages of economic development, with particular emphasis on how these effects vary across the income distribution.
Method — A dynamic panel quantile regression approach is employed to analyse panel data from 115 countries over the period 1995–2020. GDP per capita is used as a proxy for income, allowing the analysis to capture heterogeneous effects across different quantiles of income distribution. The key control variables include human capital, population, trade openness, institutional quality, and inflation.
Findings — The results reveal significant heterogeneity in the effects of economic complexity across income levels. Economic complexity has a positive and significant impact on income at higher quantiles, indicating that more advanced economies benefit from increased productive capabilities. Conversely, at lower quantiles, the effect is negative, suggesting that less-developed countries are unable to fully capitalise on rising complexity.
Implications — The findings suggest that policy strategies should be tailored to different stages of development. Low-income countries need to enhance skill formation and structural transformation to benefit from complexity, while high-income countries should focus on innovation and diversification. Strengthening human capital and institutional quality is essential to mitigating the effects of inequality.
Originality — This study contributes to the literature by highlighting the heterogeneous effects of economic complexity using a dynamic panel quantile framework, offering new insights into income differences across development levels, an aspect largely overlooked in previous research.