Abstract
Given that structural transformation plays an important role in countries' growth efforts, various reforms are required in many different areas to produce more technologically intensive, efficient and more information-intensive production patterns. The goal of this study is to explore the underlying nexus between structural transformation (economic-complexity) and income inequality. The empirical analysis tests the Kuznets curve hypothesis in a large country sample (65 countries), spanning the period 1990–2015 and employing the system-GMM (generalized method of moments) technique. For addressing the heterogeneity issues, we have classified the panel data sets into sub-panels based on income across the countries. The empirical outcomes demonstrate that economic complexity has a significant negative bearing on income inequality, indicating that increase in structural transformation tends to improve income distribution. The results further indicate that there is wide-ranging heterogeneity across country-groups as far as the impact of economic complexity on inequality of income distribution is concerned. The poorest sample set of countries have the highest impact of economic complexity on inequality of income distribution. The findings remain consistent across modelling specifications and income-levels. They also imply that production structure demonstrates a high-resolution illustration of a number of determinants, running from organizations to human capital, that evolves around the country’s production process and export diversification along with inclusiveness of the economic system. We argue that the economies with lesser levels of education and lower degrees of trade-openness fails to reduce the inequality in the distribution of income. The empirical outcomes of this study are appropriate for policy planners in tailor-making the policies towards reducing income inequality at the backdrop of the Sustainable Development Goal-10. Unarguably, the poorest set of countries in the sample set needs to put the structural transformation process foremost on the agenda.
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28 February 2023
A Correction to this paper has been published: https://doi.org/10.1007/s11135-023-01636-5
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Appendix: Country samples
Appendix: Country samples
1.1 Full country sample (Countries:65)
Australia, Algeria, Austria, Argentina, Bolivia, Belgium, Bulgaria, Brazil, Canada, Cameroon,Chile, China, Colombia, Costa Rica, Cote d'Ivoire, Denmark, Dominican Republic, Egypt, El Salvador, Finland, France, Germany, Ghana, Greece, Guatemala, Honduras, Hong Kong, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Madagascar, Malaysia, Mexico, Morocco, Netherlands, New Zealand, Nicaragua, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Singapore, South Africa, South Korea, Spain, Sri Lanka, Sweden, Switzerland, Thailand, Togo, Tanzania, Turkey, Tunisia, United Kingdom, United States, Uruguay,
1.2 Lower income countries
Madagascar, Togo, Tanzania,
1.3 Lower-middle income countries
Bolivia, Cote d’Ivoire, Cameroon, Egypt, El Salvador, Guatemala, Honduras, Ghana, Indonesia, India, Pakistan, Morocco, Philippines, Paraguay, Nicaragua, Sri Lanka.
1.4 Upper-middle income countries
Algeria, Argentia, Bulgaria, Brazil, Colombia, China, Dominican Republic, Costa Rica, Ecuador, Hungary, Mexico, Malaysia, Panama, Peru, Romania, Thailand, Tunisia, South Africa, Turkey.
1.5 High income countries
Austria, Australia, Belgium, Chile, Canada, Denmark, France, Finland, Greece, Hong Kong, Ireland, Israel, Germany, Japan, New Zealand Italy, Poland, Norway, Netherlands Singapore, Portugal, Sweden, Switzerland, Spain, South Korea, United Kingdom, Uruguay, United States.
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Ghosh, S., Doğan, B., Can, M. et al. Does economic structure matter for income inequality?. Qual Quant 57, 2507–2527 (2023). https://doi.org/10.1007/s11135-022-01462-1
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DOI: https://doi.org/10.1007/s11135-022-01462-1