Urbanization can help reduce income inequality

Income inequality represents one of the most challenging issues confronted by the global community today. Nevertheless, little that is new has been proposed or implemented to tackle worsening distributions prevailing in both developing and developed economies. Even the renowned economist Thomas Piketty (2014) took to task efforts into the conventional wisdom of fiscal measures used to address inequality for thorough distribution, both of which has costs and distortions. Most importantly, fiscal research are vastly limited, even in affluent industrialized world, where its effects have been proven insufficient to reverse or contain an rising inequality.

It should be stressed that the distributional problem is more urgent and important in developing countries, particularly least developed countries (LDCs). This is because (1) they account for approximately 85% of the global population; (2) it is simply infeasible for them to allocate enough fiscal resources for redistribution, even in economies with a middle-income-level development status. As shown below, on average, upper-middle and high-income countries spend 4.60% of Gross domestic product (GDP) on social programs in the latest year whereas this percentage is only 1.54% for other countries; (3) with a lower development status (a smaller pie), a same level of inequality (how the pie is divided) will push many more into abject poverty in developing countries than in developed economies; and (4) worse still, inequality is expected to rise further as the countries take off or continue to grow.

Clearly, it is of utmost importance and urgency for developing countries to contain rising inequality, at least for reducing poverty, hunger, and malnutrition. Otherwise, the world will risk a further worsening of income distribution, ultimately leading to failure of Sustainable Development Goals (SDGs) in terms of the first goal of “No Poverty” and the tenth goal of “Reduced inequalities”.

The infeasibility of conventional wisdoms to address the inequality problem appeals for a fundamental rethinking beyond secondary distribution as a major tool for managing income distribution.

This paper focuses on income inequality in developing countries. First, we demonstrate the infeasibility of relying on fiscal transfers to address income inequality. Second, we show that, to a significant extent, inequality in developing countries can be accounted for by the urban-rural gap—an important finding we have noticed despite little attention to date. Third, we develop a new technique to bridge the benign impacts of urbanization on the urban-rural gap and propose an alternative to the conventional wisdom of managing income inequality—this being well-managed urbanization. Fourth, we point out a misperception that may have contributed to the neglect of the urban-rural gap in constituting national inequality by developing economies. This, as we further argue, has possibly led to anti-urbanization mentalities and practices, with adverse distributional consequences. Finally, we conclude with policy suggestions.

The paper situates its contribution against several strands of prior work. Kuznets (1955) posited an inverted U-shaped relationship between inequality and industrialization/urbanization, implying that urbanization initially worsens income distribution; however, this classic view overlooked the urban-rural income gap as a component of national inequality, likely due to data limitations. Shorrocks and Wan (2005) and Wan (2013) emphasized decomposition methods and the value of Theil-index-based breakdowns into within-sector inequalities and between-sector (urban-rural) gaps, motivating the current paper’s focus on the gap component. Lewis (1954) highlighted the dual economy model, where labor movement from low-productivity agriculture to higher-productivity industry drives development, a mechanism consistent with urbanization reducing the urban-rural gap. Piketty (2014) critiqued reliance on fiscal redistribution for addressing inequality, noting costs and limited effectiveness—an observation that aligns with this paper’s argument about the infeasibility of fiscal measures in developing countries.

The study uses a decomposition of national income inequality employing the Theil index (T), splitting national inequality into three components: within-rural inequality (Tr), within-urban inequality (Tu), and the between-sector urban-rural income gap. Following Shorrocks and Wan (2005), the Theil index allows exact additive decomposition into within and between components. The authors present formulas expressing national inequality as the sum of these components and derive the marginal impact of urbanization (urban population share) on national inequality as the sum of the effects on the within component and on the urban-rural gap.

Empirical implementation relies on constructing measures of average rural and urban incomes using sectoral GDP: rural income approximated by agricultural GDP divided by rural population and urban income by non-agricultural GDP divided by urban population. The urbanization rate (urban population share) is taken from the World Bank’s World Development Indicators (WDI). National inequality (Theil-L) is converted from Gini ratios using the Standardized World Income Inequality Database (SWIID, v7.1). Social protection expenditure data come from the IMF Government Finance Statistics (GFS). The analysis covers panels of countries over 1990–2017: up to 100 countries for descriptive plots (social protection and urbanization vs. GDP per capita), and 90 economies for the core analysis of urbanization’s marginal impact on the urban-rural gap and national inequality.

The authors estimate the contribution of the urban-rural gap to national inequality by applying their decomposition to the latest year available, producing cross-country comparisons. They then compute the marginal effect of urbanization on the urban-rural gap across countries and over time, identifying threshold effects with respect to the urbanization rate and GDP per capita.

To assess how urbanization policy stance moderates the relationship between urbanization and inequality, they estimate a regression model where national inequality (Theil) is regressed on the urbanization rate, a policy stance dummy (1 = pro-urbanization; 0 = anti-urbanization, based on United Nations 2016 “Policies on Spatial Distribution and Urbanization”), the interaction of urbanization and policy stance, GDP per capita, and other controls (including fiscal generosity, government expenditure share of GDP, and tax revenue share of GDP), with country and year fixed effects.

Data sources: SWIID (v7.1) for Gini, WDI for urbanization rates and GDP per capita, IMF GFS for social protection expenditure. The study also uses UN classifications for urbanization policy stance. Visual analyses cover 1990–2017; figures focus on 90 economies for core results and 100 countries for broader descriptive trends.

• Fiscal redistribution is generally infeasible/insufficient in developing countries: social protection spending is negligible until GDP per capita reaches about USD 5000 (2011 PPP, constant 2017 international $). Upper‑middle and high‑income countries spend about 4.60% of GDP on social programs on average, versus only 1.54% for other countries, implying a narrow and shallow tax base and limited redistribution capacity.
• Redistribution’s impact on reducing inequality (change in Gini pre- vs post-transfer) is modest in lower- and lower-middle-income countries, indicating limited potency of fiscal transfers for inequality reduction in LDCs.
• The urban-rural income gap constitutes a large share of national inequality in developing economies. Excluding highly urbanized Latin America, this component is 30% or more of national inequality; in China it reaches 50% or more.
• Urbanization reduces national inequality primarily by narrowing the urban-rural gap. The beneficial impact becomes evident once the urbanization rate reaches roughly 30% (about 40% in many African countries). By 2017, 81 of 90 economies analyzed had surpassed the 30% urbanization threshold.
• With respect to income levels, after GDP per capita exceeds about USD 2000 (2011 PPP), urbanization generally helps narrow the urban-rural gap; as of 2017, 78 of the 90 economies exceeded this threshold. The Discussion highlights a closely related key threshold of around USD 3000.
• The relationship between GDP per capita and inequality shows an inverted-U within urban and rural areas separately, but the urban-rural gap declines with GDP per capita; accounting for the gap alters the classic Kuznets narrative for total inequality.
• The beneficial effect of urbanization is stronger in rapidly urbanizing countries than in moderate- or slow-urbanizing ones, suggesting that restricting rural-to-urban migration can worsen distributional outcomes.
• Policy stance matters: shifting from anti- to pro-urbanization policies increases the benign effect of urbanization on national inequality by approximately 30% (2011–2015 evidence across 90 economies).

The study addresses the core question of how developing countries can effectively contain rising income inequality despite limited fiscal capacity. By decomposing national inequality, the authors show that the urban-rural gap is a major and previously underemphasized driver of overall inequality. They demonstrate that well-managed urbanization—by facilitating rural-to-urban migration and enabling productivity gains, remittance flows, and nonfarm diversification—can narrow the urban-rural gap and thereby reduce national inequality. This reframes the policy approach away from sole reliance on redistribution toward structural transformation and spatial reallocation as a feasible equity-enhancing strategy.

The findings also reinterpret the Kuznets hypothesis when the between-sector gap is explicitly considered: while within-sector inequality may follow an inverted U with development, the between-sector urban-rural gap declines with GDP per capita, so overall inequality can fall as urbanization proceeds. The evidence suggests particularly strong benefits in rapidly urbanizing contexts and under pro-urbanization policy regimes. These insights have direct implications for achieving SDGs related to poverty reduction and inequality, especially in LDCs where fiscal redistribution is constrained.

Urbanization, when well managed, offers a practical and effective pathway for developing countries to reduce national income inequality by narrowing the urban-rural gap. Given the limited scope for impactful fiscal redistribution in many LDCs, policymakers should adopt pro-urbanization strategies that facilitate rural-to-urban migration and ensure equitable access to urban opportunities and services. Recommended actions include: setting and enforcing minimum wages for migrant workers; prioritizing job creation in urban development; leveraging digital platforms to provide employment information; designing housing, health, education, and job-training policies inclusive of recent migrants; reducing living costs; and guaranteeing equal access to affordable housing, education, and healthcare. International organizations (e.g., UN‑Habitat) can support knowledge sharing on effective urban planning and development practices.

Future research should explore unresolved issues such as whether and how urbanization affects within-city inequality, the prevention of slum formation and spatial segregation, and the causal interplay between urbanization and industrialization.

• Data and measurement approximations: Urban and rural average incomes are proxied using non‑agricultural and agricultural GDP divided by urban and rural populations, respectively, which may introduce measurement error. Conversion from Gini to Theil indices (via SWIID) also relies on standard transformations and comparability assumptions.
• Sample coverage and period: Core analyses focus on 90 economies over 1990–2017; results may not generalize outside this set or to earlier periods.
• Assumptions about within-sector inequality dynamics: The approach notes that within-urban and within-rural inequality change slowly over time, an assumption that may not hold in all contexts and could affect decomposition results.
• Policy stance classification: The pro- vs anti-urbanization policy dummy is based on UN (2016) categorization, which may not capture nuances in implementation or policy changes within the study period.
• Unresolved theoretical and empirical questions: The mechanisms by which urbanization influences within-city inequality, slum formation, and the causal relationship between urbanization and industrialization remain open and could affect interpretation and policy design.