Page 128 - IJPS-11-5

International Journal of
Population Studies Regional disparities and fertility rates

disparities – measured by GRDP inequality and property level and GRDP data. Two representative indices, the Gini
value gaps – exert a significant negative influence. coefficient and the Theil coefficient, were used to measure
Nevertheless, the study does not explore how regional annual regional disparities in fertility rates and economic
economic development influences the nationwide total growth. The Gini coefficient has the advantage of not being
fertility rate, leaving room for further investigation into the affected by differences in population size across regions.
broader implications of regional disparities. However, as it is based on the overall distribution of
Consequently, this study not only analyzes the impact variables, different patterns of inequality can produce the
of economic development at the national and regional same Gini value. The Theil coefficient, on the other hand,
levels on fertility rates but also conducts empirical analyses can distinguish between within-region and between-
on the influence of regional disparities. To address these region inequality but is less effective when comparing two
regions of differing population sizes (Trapeznikova, 2019).
research questions empirically, the study is grounded Both coefficients range from 0 to 1, with values closer
in theoretical frameworks and prior empirical research, to 1 indicating greater regional disparities. The specific
leading to the formulation of the following two research formulas for calculating the regional disparity using these
questions. two indices are presented in Equations I and II below.
(a) Research question 1: Economic development and
fertility rates 1 n n
Economic development is positively correlated with GINI = n 2 µ ∑∑ y − y j (I)
i
2
household income levels, and an increase in income t i=1 j=1
levels has a positive impact on fertility rates. However, 1 n  y   y 
economic development and the subsequent rise in THEIL = ∑  i  log  i  (II)
=1
income levels may also negatively correlate with n i  µ t   µ t 
fertility rates due to increased opportunities beyond In the above equations, µ represents the average value
t
childbirth and intensified competition. “If all other of GRDP at time t, while y denotes the GRDP for region i,
conditions being equal,” what is the effect of rising and n is the number of regions (16 ).
i
2
income levels due to economic growth on childbirth?
(b) Research question 2: Regional disparity and fertility Table 1 provides descriptions of the controlled
rates independent variables used in the spatial panel model
Economic development is positively correlated with constructed to analyze the determinants of regional
household income levels, and increased income total fertility rates. The dependent variable is the log-
levels generally have a positive impact on fertility transformed total fertility rate by metropolitan level.
rates. However, economic development may also be The controlled independent variables include GRDP,
associated with greater regional disparities, which population density (as a measure of competition
have a negative impact on fertility rates. “If all other level), population size (representing opportunities
conditions being equal,” what is the effect of regional beyond childbirth), the proportion of the population of
disparities resulting from economic growth on fertility childbearing age (as an indicator of potential fertility),
rates? and the unemployment rate (as a proxy for labor market
stability). By controlling for these factors, the net effect
2. Data and methods of economic growth on fertility can be estimated, thus
answering research question 1.
2.1. Data and measurements
The primary objective of this study was to examine
The analyses in this study involve examining the the effects of economic growth and regional disparities
correlation between fertility rates, economic growth, and on fertility rates, rather than to identify all potential
regional disparities; analyzing the determinants of fertility determinants of fertility. Therefore, rather than including
at the regional level using various spatial panel models; and an extensive set of control variables, the study focused on
investigating the impact of macroeconomic growth and key macroeconomic indicators that capture the economic
regional disparities on fertility using time series models. and spatial dimensions relevant to fertility decisions.
Consequently, the variables employed in each model This approach helped maintain alignment with the core
exhibit heterogeneity.
research question, avoiding overfitting and unnecessary
To analyze the correlation between the total fertility complexity.
rate, economic growth, and regional disparities, data from
2000 to 2020 provided by Statistics Korea were utilized. 2 Throughout the entire period, Sejong was considered
This includes the total fertility rates at the metropolitan part of the Chungcheongnam-do region.

Volume 11 Issue 5 (2025) 122 https://doi.org/10.36922/ijps.8157