South Korea has experienced rapid economic development since the 1960s. However, pronounced regional disparities have concurrently emerged. Amid the escalating regional inequalities and persistent demographic challenges characterized by low fertility rates, regional decline has become a pressing issue. Therefore, the feasibility of expanding transportation networks as a countermeasure to regional decline has been proposed. This study utilizes the synthetic control method and spatial difference-in-differences methodologies to assess the impact of the 2017 opening of Seoul–Yangyang Expressway on economic development and population inflow within Hongcheon-gun, Inje-gun, and Yangyang-gun. The purpose of this study is to evaluate the effectiveness of highway development as a policy instrument to mitigate regional decline. Findings from the synthetic control method analysis suggest a positive impact of the opening of the expressway on Hongcheon-gun’s Gross Regional Domestic Product (GRDP) in 2018, as well as Yangyang-gun’s net migration rates from 2017 to 2019. Conversely, the spatial difference-in-differences analysis, designed to identify spillover effects, reveals negative impacts of the highway on the GRDP and net migration rates of adjacent regions. Consequently, although targeted transportation infrastructure development in key non Seoul Metropolitan cities may contribute to ameliorating regional imbalances, results indicate that such measures alone are unlikely to suffice in attracting population to small- and medium-sized cities outside the Seoul Metropolitan Area.
Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.
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