Income Convergence Research Articles (Page 1)

The problem of gender inequality in the labor market remains as the most important factor limiting the use of human capital and the potential for sustainable economic growth. The aim of the study is to assess the dynamics of the gender wage gap and empirically verify its relationship with GDP and inflation for 2019-2023. The methodological framework includes descriptive and comparative statistical analysis, calculation of the gender pay gap coefficient (hereinafter – GPG), as well as correlation and regression analysis aimed at identifying the relationship between the gap level and macroeconomic indicators. The data from the Bureau of National Statistics of the Republic of Kazakhstan, official collections and open sources on average salaries of men and women by sector and region were used as initial data. The results of the study show that, on average, women earned 24- 27% less than men in 2019, while by 2023 the gap had narrowed to 21%, indicating a partial convergence of incomes. However, in a number of industries (construction, industry, finance) A gap of over 30% remains, while in education and healthcare it is decreasing to 15-18%. The analysis revealed a moderate negative correlation between the dynamics of GDP and the level of the gender gap (r ≈ -0.45), which indicates a partial dependence of income equality on the general state of the economy. Thus, despite the positive trends, eliminating gender inequality requires comprehensive measures aimed at increasing wage transparency, increasing women's access to high-paying sectors, and fostering an inclusive corporate culture.

Abstract This study investigates conditional income convergence among 26 European Union member states from 1995 to 2022, focusing on GDP per capita growth and complemented by an analysis of unemployment dynamics. Three advanced heterogeneous panel estimators are employed: the pooled mean group autoregressive distributed lag (PMG-ARDL) and dynamic common correlated effects ARDL (CS-ARDL) to capture linear relationships, and the pooled mean group nonlinear ARDL (PMG-NARDL) to account for potential asymmetric adjustments. These methods address slope heterogeneity, cross-sectional dependence, and nonstationarity. Panel unit-root and cointegration tests confirm long-run relationships, and Dumitrescu–Hurlin tests assess causality. In the linear PMG and CS-ARDL models for GDP per capita growth, inflation and gross capital formation hinder long-run growth, while government spending, labor force participation, and trade openness have positive effects. In the unemployment models, GDP growth, trade openness, and government spending reduce unemployment, whereas inflation and gross capital formation increase it. The nonlinear PMG-NARDL results reveal that the direction of change in variables such as government debt, capital formation, inflation, and trade openness matters, with positive and negative shocks often having different long-run effects. Error correction terms across models indicate stable adjustment, in some cases with damped oscillations. Policy implications show the need to maintain price stability, improve the efficiency of public investment, sustain trade openness, and promote labor force participation alongside prudent debt management. Convergence patterns remain heterogeneous across member states, reflecting differences in structural and policy characteristics.

This paper examines income growth dynamics in BRICS economies (1991–2022) using panel data and random-effects estimation. It tests the income convergence hypothesis by analyzing GDP per capita growth and key drivers such as investment, FDI, technology, trade, and education expenditure. Contrary to β-convergence theory, findings show income divergence: higher-income BRICS countries, especially China and India, grow faster than their lower-income peers. The study quantifies divergence speed and illustrates widening income gaps, underscoring the need for structural reforms, innovation-driven investment, and regional cooperation. It also calls for further research accounting for cross-sectional dependence and country- specific heterogeneity.

Research originality: Women tend to be chosen as the non-labor force, even though they are potential workers who can contribute directly to the economy. Their level of education influences this contribution. Research objectives: This research examined the impact of female labor force participation on regional economic and income convergence. Research methods: Pooled Least Squares (PLS) and panel data estimation were conducted using cross-sectional data on 472 cities/districts across Indonesia between 2016 and 2022. Empirical result: The findings reveal that female labor force participation significantly enhances regional economic growth only when women have at least a senior high school education. However, their contribution to accelerating economic convergence remains suboptimal, as most female workers are elementary school graduates. Implications: To improve the contribution of the female workforce to the economy, the government should extend compulsory education from 9 to 12 years, expand access to non-formal education for women, and establish a female-friendly labor market through job flexibility and improved childcare access. JEL Classification: I25, J21, E12, J20

ABSTRACT In this paper we study regional income per capita convergence in Visegrad-4 countries using the novel approach proposed by Phillips and Sul (2007a) that has not been so far employed in the context of their regions. Our study employs data at the NUTS-3 regional classification for the period 1993-2023. Our results indicate that the income convergence hypothesis among all Visegrad-4 regions is rejected both for the whole region and particular countries. At the same time, our results show the presence of a club convergence between particular regions of Visegrad-4 countries. In particular, among all Visegrad-4 regions, we identify three convergence clubs and Prague as the non-convergent region. The first convergence club includes major metropolitan areas while the second club consists of less developed areas that are located next to metropolitan areas. The third club includes the least developed and peripheral parts of each country. However, the number of convergence clubs within each country varies greatly across countries. There are two or three convergence clubs in in smaller Visegrad-4 countries that include: Czechia, Slovakia and Hungary while in Poland we identify six convergence clubs. Our results suggest that a new division between the richer metropolitan and the poorer agricultural areas has been emerging.

ABSTRACTThis paper examines income convergence among the ten‐member Association of Southeast Asian Nations (ASEAN) for the period 1970–2019, spanning the establishment of the ASEAN Economic Community (AEC) in 2015. We employ the novel log t test developed by Phillips and Sul which is robust to heterogeneity and nonlinearity in the data. Our study uniquely analyses convergence using both per capita income and national GDP aggregates. We find evidence of an ongoing process of convergence in GDP per capita among ASEAN members, with convergence rates ranging from 0.003% to 0.22% annually. However, our analysis of national GDP aggregates reveals potential divergence and the emergence of a ‘two‐tier ASEAN’. We attribute the slow convergence to insufficient capital accumulation and technological progress across member states. Our findings highlight the complex dynamics of economic integration in ASEAN and underscore the need for targeted policies to promote inclusive growth and prevent the formation of a two‐tier economic structure within the bloc. This research contributes to the literature on regional economic integration and provides valuable insights for policymakers in ASEAN and other regional economic communities.

This paper investigates convergence across China’s 31 provinces over the 1990–2019 period, focusing on economic output measured primarily through per‑capita gross regional product (PGRP). The analysis applies a two‑step convergence methodology, making use of both linear and nonlinear econometric frameworks. First, an Arellano–Bond dynamic panel model controls for structural heterogeneity and extracts province‑specific residuals after accounting for a vector of economic and demographic controls. Second, the Phillips & Sul (2007) log t test is used on both raw PGRP data and the residual series to assess unconditional and conditional convergence and identify club convergence. Unconditional results reveal statistically significant evidence of income convergence across Chinese provinces, with convergence speeds averaging δ ≈ 0.30. However, conditional analyses show that short‑run deviations persist when local policy implementation and regional structural differences are not accounted for. Using a Hodrick‑Prescott filter, a trend is extracted from the residuals, revealing an indication of long‑run convergence. Club clustering tests further show that multiple diverging groups in the 1990s collapse into a unified convergence path after 2001 with the implementation of the Western Development Strategy (WDS). These results highlight the importance of targeted place‑based policies and long‑term infrastructure investment in facilitating balanced regional development.

IntroductionAgricultural modernization and sustainable development face significant challenges from persistent urban-rural income disparities, which constrain agricultural transformation and rural revitalization. This study investigates the comprehensive impact mechanism of agricultural technological innovation on urban-rural income disparities through a multi-dimensional analytical framework integrating productivity enhancement, structural transformation, and spatial heterogeneity effects.MethodsUsing panel data from 280 Chinese cities during 2008 - 2021, we employ two-way fixed effects panel regression models to examine the relationship between agricultural technological innovation (measured by patent applications) and urban–rural income gaps (measured by the Theil index). The analysis includes robustness tests, heterogeneity analysis across regions and institutional contexts, mechanism testing through mediation analysis, and threshold effect analysis using Hansen’s threshold regression technique.ResultsThe integrated analysis reveals that agricultural technological innovation serves as a fundamental driver for narrowing urban-rural income gaps through interconnected pathways of employment structure optimization, factor allocation improvement, and production efficiency enhancement. Agricultural technological innovation effectively reduces the urban-rural income gap, with invention patents showing particularly significant effects. Heterogeneity analysis indicates stronger effects in eastern and western regions, and in cities with higher administrative levels, greater innovation vitality, stronger intellectual property protection, and better information accessibility. The empirical evidence reveals non-linear threshold effects, where innovation impact strengthens systematically as urbanization rates, education attention, and information accessibility increase.DiscussionThe findings form a cohesive framework for understanding innovation-driven rural development and validate agricultural technological innovation as a critical mechanism for achieving income convergence. Policy recommendations include strengthening agricultural technological innovation support, optimizing rural labor structure, promoting urbanization and information infrastructure development, and enhancing policy coordination to maximize the equalizing effects of agricultural innovation across diverse regional contexts.

The factors and mechanisms of the dynamics of global economic growth at the present stage have been analyzed and summarized. Over the past decades, many determinants have increased uncertainty in the global economy development, affecting the decline in aggregate factor productivity through various channels. The purpose of the study is to assess the mechanisms of deceleration and divergence of global economic growth, which significantly limit sustainable social and economic development in the global economy, as well as to discuss scenarios and ways to prevent a slowdown in global growth. The challenges of this slowdown for the sustainability of the global economy have been discussed, and new growth trends that emerged in 2022-2024 have been systematized. An additional aspect of the study was the assessment of the negative risks of global economic growth in the future, related to the current concerns about ongoing inflation and recession. The mechanisms that determine the growth divergence and uncertainty have been identified, including using the example of the dynamics observed in individual countries and assessing economic policies implemented in these states (including in terms of countering inflation). Several scenarios of global economic growth for the medium term have been presented, suggesting the opportunities implementation to prevent a slowdown in growth. If growth slows down in the medium term, it will have a negative impact on income convergence between states, as it will become increasingly difficult for poor countries to catch up with rich ones. There are distributional consequences of a slowdown in growth in the medium term for global inequality and wellfare.

During a major crisis, the transitional dynamics of conditional convergence are unlikely to apply. In this paper, we introduce a Markov chain approach which integrates the study of crises and convergence. We allow upwards and downwards mobility to change when a country enters a crisis regime. We find that conflict and debt crises help to explain the persistence of low relative income, and that the convergence process has changed over time. Faster global convergence in the early 2000s can be attributed partly to fewer and shorter crises, so the multiple shocks after 2020 are likely to have slowed income convergence.

Income dynamics of different districts of Kerala have been studied using per capita income derived from the agricultural sector by Markov chain analysis. Transition probabilities and steady states have shown high level of income dynamics for majority of districts. Most of the districts have shown a high retention probability in high and low-income states. The districts Palakkad and Kollam exhibited high instability in high-income states. The steady state probabilities revealed a polarising nature of agricultural income towards the low-income category for many districts. The convergence of the agricultural income across the districts has been analyzed using unit root tests (Phillips-Perron test) for pairwise differences of income across the districts, illustrated that the majority of the districts have converged in pairs to establish a similar nature of income dynamics over time. The income dynamics of the districts have shown an inclusive growth pattern in agricultural income of Kerala. While the income of Wayanad has shown a divergence with all other districts, Idukki has shown a divergence nature with all districts except Thrissur district. The Phillips-Perron (PP) test of the districts with the state average exhibited convergence of income with all the districts except for Ernakulam, Wayanad, and Idukki districts. These findings can assist policymakers to formulate agricultural development plans specific to a given region in order to reduce income inequality and foster balanced growth across the districts of Kerala.

This study analyses convergence in income inequality among districts/municipalities in South Sulawesi. The method used is quantitative analysis with panel data regression involving 24 districts/cities. The results show that there is no sigma convergence. However, beta convergence is identified with an initial GRDP per capita regression coefficient of 0.461231. This study concludes that although income inequality still exists, there are indications of convergence influenced by certain factors such as government expenditure (Gi) and the Human Development Index (HDI).

Income is one of the most popular dimensions for measuring welfare and development; hence, comparing welfare and well-being among countries can be conducted by comparing their per capita income. While income convergence is a certain implication in neoclassical growth theory, it does not always occur empirically. This study aims to investigate whether income convergence occurs among economies. Employing data from 93 countries from 1980 to 2022 obtained from the World Bank, the two-way fixed effect panel model is implemented to verify the existence of β-convergence. The result shows that the initial per capita gross domestic product, representing income, negatively affects income growth, indicating that β-convergence occurs in terms of global and club convergence. This implies that poor countries grew faster than affluent countries. After β-convergence is confirmed, σ-convergence is analyzed by measuring the income dispersion across countries over time. σ-convergence exists if the dispersion declines as time passes. The result shows that σ-convergence exists only among G20, OECD, lower-middle-income, higher-middle-income, and high-income countries. This fact implies that the income gap between poor and rich countries within those groups shrinks over time. In contrast, the income gap among low-income countries did not experience a significant decline during the period. Therefore, international organizations and partnerships must pay more attention to and assist lower-income countries to achieve higher growth rates.

Research Originality: This study takes a novel approach to analyzing the impact of human capital on income convergence in ASEAN-8 countries by comparing three indicators. This comparative analysis provides a more comprehensive understanding of human capital dynamics in ASEAN's economic convergence.Research Objectives: This study investigates the impact of human capital on income convergence by applying the concept of β-convergence to the ASEAN-8 countries.Research Methods: The analysis of β-convergence is based on the basic and augmented Solow growth models. The estimation is conducted using static and dynamic panel data regression from 1995 to 2019.Empirical Result: The results reveal the existence of absolute and conditional β-convergence in ASEAN-8 countries, suggesting that poor countries grow faster than rich countries, with human capital playing a crucial role in this process. Human capital, measured by average years of schooling, tertiary gross enrolment ratio, and HCI, are important factors that significantly increase income convergence.Implications: ASEAN-8 governments need to establish policies that enhance human capital, particularly in education, by increasing educational attainment and the rate of return to education.JEL Classification: E24, O47, C13How to Cite:Suprayitno, A. W., & Gitaharie, B. Y. (2025). Human capital as a Catalyst for Income Convergence: Evidence from ASEAN-8 Countries. Etikonomi, 24(1), 265 – 284. https://doi.org/10.15408/etk.v24i1.41571.

PurposeThis study examines the convergence of energy diversification, financial development and per-capita income in OECD countries.Design/methodology/approachThe research employs the club convergence test to assess convergence among OECD countries and uses Granger causality tests and panel regressions to identify the determinants of convergence, using data from 1997 to 2021.FindingsThe convergence tests showed no overall convergence but revealed convergence clubs for each factor. Granger causality tests indicated short-run bi-directional relationships between the variables. Long-run panel regression analysis confirmed that technological progress significantly improves per capita income and energy diversification. Additionally, it revealed bi-directional relationships between energy diversification and financial development, a uni-directional relationship from financial development to per capita income and a U-shaped effect of per capita income on energy diversification, with a turning point at $67,112.8 per year.Practical implicationsThe findings suggest that within each convergence club, implementing microeconomic incentives for technology development and diffusion in energy, production and financial services could help lagging countries catch up.Originality/valueThis study pioneers the testing of convergence in energy diversification, financial development and per capita income in OECD countries and identifies the determinants of this convergence.

Regional disparities are usually monitored in terms of economic performance. But as pointed out by many scholars, research has to look beyond GDP, investments, unemployment, and focus also on regional inequality in measures of well-being, for example, the disposable income of households. Therefore, this article examines the income disparities among the regions of Central European countries. We apply the probabilistic definition of convergence that is tested by the time series cointegration analysis. However, in our analysis, convergence criteria are tightened to increase robustness. In particular, we propose to require meeting of both criteria, i.e., stationary and absence of unit root, instead of one for the acceptance of the cointegration condition of regional convergence. Empirical analysis shows that despite the application of stricter conditions, the hypothesis of income convergence between Central European regions in 2003–2022 cannot be rejected. In particular, we found inner-country convergence in most countries. However, the involvement of individual regions in cross-country convergence varies widely. The results suggest that convergence intensity in the easternmost and westernmost regions is weak. However, we identified a “belt of convergence” along the border of the former Iron Curtain. These findings support the hypothesis of club convergence suggested by some scholars in the region of Central and Eastern Europe. On the other hand, our results significantly challenge previous research that claimed Central European transition economies are converging, especially towards German regions. Instead, our results indicate that convergence towards German regions is weak, while convergence towards Austrian regions is much more pronounced. Finally, uncovering how regions are converging at different rates and towards different steady-states can help to optimize the allocation of EU funding.

In this work we analyze the evolution of productivity, in terms of the convergence of per capita income, of all the Spanish provinces, based on data from the previous decade. On the one hand, a cluster analysis allows us to group the Spanish provinces according to four income levels (low, medium-low, medium-high and high), which can be determined from the quartiles of the distribution, and, on the other hand, Markov chains make it possible to study the long-term evolution of productivity and convergence between the provinces, as well as the speed of convergence towards the equilibrium situation. Moreover, we can obtain the average time to return to an income level in which a province was previously. With the above, predictions of future income levels are made for the provinces, both in the current situation, and if the pandemic caused by COVID-19 had not existed, which leads us to evaluate the impact of the health emergency.

We investigate trends in income inequality in the European Union (EU) from 2007 to 2019. Using EU-SILC data, we find that EU-wide inequality declined between 9 and 20%, depending on the inequality measure applied, despite rising within-country income inequality during the same period. Applying a series of decomposition techniques, we find that between-country convergence in pre-tax/transfer incomes fully explains the declining EU-wide inequality. Changes in tax and transfer systems, in contrast, contributed to marginally higher inequality in 2019 compared to 2007. Nonetheless, the 10th percentile of the EU-wide income distribution grew six times the rate of the 90th percentile, a product of widespread earnings gains among residents of lower-income EU Member States. Re-centered influence functions and Kitigawa-Oaxaca-Blinder analyses reveal that those earnings gains are not due to specific compositional or employment changes but rather are due to rising earnings returns to employment in lower-income Member States. Despite the contribution of between-country income convergence in reducing EU-wide inequality between 2007 and 2019, however, within-country income disparities continue to explain the larger share of EU-wide inequality levels in 2019. Thus, reducing within-country economic disparities is increasingly important for achieving further reductions in EU-wide inequality moving forward.

The allocation of wealth in society has been a fundamental question and challenge in economics. Concentrating most wealth in a small segment of society while leaving the rest with a smaller portion can lead to income inequality and social issues. Income inequality varies across cultures, historical periods, economic structures, and economic systems. Our study tests and analyzes comparative income convergence in Eastern Europe, Western Europe, Central Europe, and the Baltic regions. It is important to note that our model is region-specific rather than country-specific. Our study asserts that income levels converge at an average level and within states, promoting income distribution convergence. The analysis was conducted to examine stochastic convergence in Europe within the panel stationarity (Fourier KPSS) test, revealing that regional economic inequalities in Europe are likely to either persist or even widen.

Regional Income Convergence: Brazil, the European Union and China