Main Article Content
Abstract
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.
Keywords
Article Details
Copyright (c) 2026 Mohd Lokman Bin Hamdan, Wan Ngah Wan Azman-Saini, Yasmin Bani, Anitha Rosland

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References
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- Martins, P. S., & Pereira, P. T. (2004). Does education reduce wage inequality? Quantile regression evidence from 16 countries. Labour Economics, 11(3), 355–371. https://doi.org/10.1016/j.labeco.2003.05.003 DOI: https://doi.org/10.1016/j.labeco.2003.05.003
- Morais, M. B., Swart, J., & Jordaan, J. A. (2021). Economic complexity and inequality: does regional productive structure affect income inequality in brazilian states? Sustainability, 13(2), 1006. https://doi.org/10.3390/su13021006 DOI: https://doi.org/10.3390/su13021006
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References
Amarante, V., Lanzilotta, B., & Torres-Pérez, J. (2024). Income inequality and complexity of the productive structure: {New} evidence at the world level. Economic Analysis and Policy, 84, 628–645. https://doi.org/10.1016/j.eap.2024.09.014 DOI: https://doi.org/10.1016/j.eap.2024.09.014
Buchinsky, M. (1994). Changes in the US wage structure 1963–1987: Application of quantile regression. Econometrica, 62(2), 405–458. DOI: https://doi.org/10.2307/2951618
Chernozhukov, V., & Hansen, C. (2008). Instrumental variable quantile regression: A robust inference approach. Journal of Econometrics, 142(1), 379–398. https://doi.org/10.1016/j.jeconom.2007.06.005 DOI: https://doi.org/10.1016/j.jeconom.2007.06.005
Chu, K. L. (2023). Determinants of economic complexity revisited: Insightful understanding from panel quantile regression. Journal of Economic and Banking Studies, 5, 30–44. https://doi.org/10.59276/jebs.2023.06.2448 DOI: https://doi.org/10.59276/JEBS.2023.06.2448
Chu, L. K., & Hoang, D. P. (2020). How does economic complexity influence income inequality? {New} evidence from international data. Economic Analysis and Policy, 68, 44–57. https://doi.org/10.1016/j.eap.2020.08.004 DOI: https://doi.org/10.1016/j.eap.2020.08.004
Coad, A., & Rao, R. (2008). Innovation and firm growth in high-tech sectors: A quantile regression approach. Research Policy, 37(4), 633–648. https://doi.org/10.1016/j.respol.2008.01.003 DOI: https://doi.org/10.1016/j.respol.2008.01.003
Galvao, A. F. (2011). Quantile regression for dynamic panel data with fixed effects. Journal of Econometrics, 164(1), 142–157. https://doi.org/10.1016/j.jeconom.2011.02.016 DOI: https://doi.org/10.1016/j.jeconom.2011.02.016
Glawe, L., & Wagner, H. (2024). Inflation and inequality: new evidence from a dynamic panel threshold analysis. International Economics and Economic Policy, 21(2), 297–309. https://doi.org/10.1007/s10368-023-00580-x DOI: https://doi.org/10.1007/s10368-023-00580-x
Hartmann, D., Guevara, M. R., Jara-Figueroa, C., Aristarán, M., & Hidalgo, C. A. (2017). Linking economic complexity, institutions, and income inequality. World Development, 93, 75–93. https://doi.org/10.1016/j.worlddev.2016.12.020 DOI: https://doi.org/10.1016/j.worlddev.2016.12.020
Hartmann, D., Jara-Figueroa, C., Guevara, M., Simoes, A., & Hidalgo, C. A. (2017). The structural constraints of income inequality in Latin America. https://doi.org/10.48550/ARXIV.1701.03770
Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., & Simoes, A. (2014). The atlas of economic complexity: Mapping paths to prosperity. Mit Press. DOI: https://doi.org/10.7551/mitpress/9647.001.0001
Hidalgo, C. A. (2021). Economic complexity theory and applications. Nature Reviews Physics, 3(2), 92–113. https://doi.org/10.1038/s42254-020-00275-1 DOI: https://doi.org/10.1038/s42254-020-00275-1
Hidalgo, C. A., & Stojkoski, V. (2025). The theory of economic complexity. arXiv. https://doi.org/10.48550/ARXIV.2506.18829
Kamguia, B., Tadadjeu, S., Miamo, C., & Njangang, H. (2022). Does foreign aid impede economic complexity in developing countries? International Economics, 169, 71–88. https://doi.org/10.1016/j.inteco.2021.10.004 DOI: https://doi.org/10.1016/j.inteco.2021.10.004
Koenker, R., & Bassett, G. (1978). Regression quantiles. Econometrica, 46(1), 33. https://doi.org/10.2307/1913643 DOI: https://doi.org/10.2307/1913643
Koenker, R., & Hallock, K. F. (2001). Quantile regression. Journal of Economic Perspectives, 15(4), 143–156. https://doi.org/10.1257/jep.15.4.143 DOI: https://doi.org/10.1257/jep.15.4.143
Kottas, A., & Krnjajić, M. (2009). Bayesian semiparametric modelling in quantile regression. Scandinavian Journal of Statistics, 36(2), 297–319. https://doi.org/10.1111/j.1467-9469.2008.00626.x DOI: https://doi.org/10.1111/j.1467-9469.2008.00626.x
Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1), 1–28.
Law, S. H., & Azman-Saini, W. N. W. (2012). Institutional quality, governance, and financial development. Economics of Governance, 13(3), 217–236. https://doi.org/10.1007/s10101-012-0112-z DOI: https://doi.org/10.1007/s10101-012-0112-z
Lee, C.-C., & Wang, E.-Z. (2021). Economic complexity and income inequality: does country risk matter? Social Indicators Research, 154(1), 35–60. https://doi.org/10.1007/s11205-020-02543-0 DOI: https://doi.org/10.1007/s11205-020-02543-0
Lee, K.-K., & Vu, T. V. (2020). Economic complexity, human capital and income inequality: a cross-country analysis. The Japanese Economic Review, 71(4), 695–718. https://doi.org/10.1007/s42973-019-00026-7 DOI: https://doi.org/10.1007/s42973-019-00026-7
Lin, W. L., Lee, C., & Law, S. H. (2021). Asymmetric effects of corporate sustainability strategy on value creation among global automotive firms: {A} dynamic panel quantile regression approach. Business Strategy and the Environment, 30(2), 931–954. https://doi.org/10.1002/bse.2662 DOI: https://doi.org/10.1002/bse.2662
Machado, J. A. F., & Santos Silva, J. M. C. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145–173. https://doi.org/10.1016/j.jeconom.2019.04.009 DOI: https://doi.org/10.1016/j.jeconom.2019.04.009
Martins, P. S., & Pereira, P. T. (2004). Does education reduce wage inequality? Quantile regression evidence from 16 countries. Labour Economics, 11(3), 355–371. https://doi.org/10.1016/j.labeco.2003.05.003 DOI: https://doi.org/10.1016/j.labeco.2003.05.003
Morais, M. B., Swart, J., & Jordaan, J. A. (2021). Economic complexity and inequality: does regional productive structure affect income inequality in brazilian states? Sustainability, 13(2), 1006. https://doi.org/10.3390/su13021006 DOI: https://doi.org/10.3390/su13021006
Nolan, B., Roser, M., & Thewissen, S. (2019). Gdp per capita versus median household income: what gives rise to the divergence over time and how does this vary across oecd countries? Review of Income and Wealth, 65(3), 465–494. https://doi.org/10.1111/roiw.12362 DOI: https://doi.org/10.1111/roiw.12362
Pham, M. H., Truong, H. D. H., & Hoang, D. P. (2024). Economic complexity, shadow economy, and income inequality: fresh evidence from panel data. International Economic Journal, 38(2), 270–292. https://doi.org/10.1080/10168737.2024.2311704 DOI: https://doi.org/10.1080/10168737.2024.2311704
Sepehrdoust, H., Tartar, M., & Gholizadeh, A. (2022). Economic complexity, scientific productivity and income inequality in developing economies. Economics of Transition and Institutional Change, 30(4), 737–752. https://doi.org/10.1111/ecot.12309 DOI: https://doi.org/10.1111/ecot.12309
Solt, F. (2020). Measuring income inequality across countries and over time: The standardized world income inequality database. Social Science Quarterly, 101(3), 1183–1199. DOI: https://doi.org/10.1111/ssqu.12795
