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Structural change and the Kuznets hypothesis

Structural change and the Kuznets hypothesis

Oyvat, Cem (2015) Structural change and the Kuznets hypothesis. [Working Paper]

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This study takes a fresh look at how the structural changes within developing economies lead to an inverted U relationship between income per capita and income inequality. In lower income countries, economic growth raises income inequality because the gains of growth are restricted to a small group of households due to the urban-rural, formal-informal divides and existing skill gaps. In the latter phases of development, the labor markets become more homogenous; labor becomes mainly medium/higher-skilled and moves towards the urban formal sector. Thereafter, the benefits of economic growth spread to the wider population, and the income Gini coefficient declines. This paper first theoretically discusses how these changes are mediated by a) urbanization; b) changes in the level of informality; and c) changes in education inequality.

The paper then tests the validity of the Kuznets hypothesis using panel data techniques and a cross-country dataset. The results show that an inverted U relationship between income per capita and income inequality only exists in the developing economies. The empirical findings also support the claim that income per capita affects income inequality through sectoral shares and informal employment. However, the evidence is weaker on income per capita's influence through education inequality.

Item Type: Working Paper
Uncontrolled Keywords: inequality; urbanization; education; informality; economic development;
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / Department / Research Group: Faculty of Business > Greenwich Political Economy Research Centre (GPERC)
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA) > Greenwich Political Economy Research Centre (GPERC)
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Last Modified: 19 Nov 2015 15:20
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None

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