A Spatial Analysis of Neighborhood-Level Fertility Rates and Policy Incentives in South Korea

Background: South Korea has recorded the lowest fertility rate globally, constantly declining to 0.72 in 2024 . This demographic crisis stems from multiple challenges, including rising living costs, childcare burdens, and widening social/economic inequality. Policymakers and researchers have warned of the rapid drop in fertility rates as a social problem, calling for immediate macro-level solutions. Over the past two decades, the Korean government has implemented various fertility support policies to address record-low birth rates. While individual-level characteristics and perspectives are widely examined, little is known about the role of macro-level factors, particularly fertility promotion initiatives, in shaping fertility trends. Moreover, fertility rates vary across geographic regions. Therefore, this study aims to analyze the spatial distribution of fertility rates and fertility support policies at the neighborhood level in South Korea.

Method: This study utilized two macro-level data sources. In South Korea, local governments design and implement diverse fertility support initiatives based on regional needs and their budget within their administrative regions (hereafter neighborhoods). We compiled neighborhood-level data on fertility rates and fertility-support policies across 229 neighborhoods nationwide. First, fertility rate data were obtained from Statistics Korea’s 2023 dataset, providing the total fertility rates (TFR) for each neighborhood, calculated as the total number of children born to women aged 15–49 years divided by the total number of women in that age group. Second, fertility support policy data were obtained from the 2023 Local Government Fertility Support Policy Casebook, which details fertility support programs and financial incentives, including cash benefits, in-kind assistance, and vouchers. We created three binary indicators to determine whether a neighborhood provided each type of support. To examine the spatial distribution of fertility rates and fertility support policies, we conducted (1) a spatial mapping analysis using the quantile method and (2) a spatial autocorrelation to assess the geographic clustering of fertility rates and policies. We ran all analyses using ArcGIS Pro 3.0.1, and GeoDa 1.22.

Results: Fertility rates varied widely across 229 neighborhoods from 0.32 to 1.65. Spatial mapping revealed notably lower fertility rates in most densely populated urban areas, such as Seoul, Busan, and Daegu. The spatial autocorrelation analysis suggested a significant spatial dependency (clustering) of fertility rates and fertility support policies respectively. Moran’s I values were 0.467 (p = 0.001) for the fertility rate, 0.182 (p = 0.001) for cash benefits, 0.086 (p = 0.017) for in-kind assistance, and 0.078 (p = 0.037) for vouchers. These findings indicate that fertility trends and policy incentives tend to be spatially correlated, with similar patterns emerging in neighborhood areas.

Conclusion/Implications: This study underscores the importance of neighborhood-level policy factors in shaping fertility behaviors and suggest that policy incentives may generate spillover effects in adjacent areas. The findings highlight the need for regionally tailored policies to address the fertility crisis and emphasize the importance for coordinated efforts among local governments to enhance policy effectiveness. We will discuss that social workers can play a critical role in supporting families and advocating for more equitable fertility policies.