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Spatial Variations in Fertility of South Korea: a Geographically Weighted Regression Approach

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Spatial Variations in Fertility of South Korea: a Geographically Weighted Regression Approach International Journal of Geo-Information Article Spatial Variations in Fertility of South Korea: A Geographically Weighted Regression Approach Myunggu Jung 1 , Woorim Ko 2, Yeohee Choi 3 and Youngtae Cho 2,* 1 Department of Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; [email protected] 2 Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea; [email protected] 3 Department of Social Welfare, Graduate School of Social Welfare, Ewha Womans University, Seoul 03760, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-2-880-2820 Received: 5 May 2019; Accepted: 4 June 2019; Published: 5 June 2019 Abstract: South Korea has witnessed a remarkable decline in birth rates in the last few decades. Although there has been a large volume of literature exploring the determinants of low fertility in South Korea, studies on spatial variations in fertility are scarce. This study compares the Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models to investigate the potential role of the spatially heterogeneous response of the total fertility rate (TFR) to sociodemographic factors. The study finds that the relationships between sociodemographic factors and TFRs in South Korea vary across 252 sub-administrative areas in terms of both magnitude and direction. This study therefore demonstrates the value of using spatial analysis for providing evidence-based local-population policy options in pursuit of a fertility rebound in South Korea. Keywords: low fertility; spatial analysis; GIS; regional fertility differentials; total fertility rate 1. Introduction In the last few decades, South Korea has witnessed a remarkable decline in birth rates. Despite the third round of the National Five-Year Plans in pursuit of addressing low-fertility levels since 2006, the total fertility rate (TFR) officially hit 0.98 in 2018 [1]. There has been a large volume of the literature exploring determinants of low fertility in South Korea [2–5]. However, results of previous studies have varied in terms of the major driving forces and the role of specific factors for fertility declines [6–10]. One reason for the inconsistent results may be derived from variations in the local contexts and characteristics. Although South Korea is known as a relatively homogeneous country, regional fertility levels have not been homogeneous. Figure1 depicts how local-level TFRs of the five highest, five middle, and the five lowest local areas in 2000 fluctuated until 2017. The figure reveals that changes in local fertility levels were not geographically homogeneous, as local-level TFRs in these areas fluctuated differently in terms of both degree of fluctuation and direction. Instead, it suggests that the fertility-decline process in South Korea is combined with local contexts in which similar sociodemographic factors may result in different fertility outcomes at different places. ISPRS Int. J. Geo-Inf. 2019, 8, 262; doi:10.3390/ijgi8060262 www.mdpi.com/journal/ijgi ISPRS Int. J. Geo-Inf. 2019, 8, 262 2 of 16 ISPRS Int. J. Geo-Inf. 2019, 8, 262 2 of 16 5 lowest areas 5 middle areas 5 higest areas 2.3 2.1 1.9 1.7 1.5 1.3 1.1 Total Fertility Rates Fertility Total 0.9 0.7 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Figure 1. Fluctuation of local-level total fertility rates (TFRs). Figure 1. Fluctuation of local-level total fertility rates (TFRs). In spite of various fertility theories to support fertility variations due to different geographical In spite of various fertility theories to support fertility variations due to different geographical settings [11], studies examining spatial heterogeneity of fertility in South Korea are scarce. Previous settings [11], studies examining spatial heterogeneity of fertility in South Korea are scarce. Previous research has shown the regional differences of fertility in South Korea on the basis of the underlying research has shown the regional differences of fertility in South Korea on the basis of the underlying assumption of demographic transition theory [2,12,13], reaching the overriding conclusion that fertility assumption of demographic transition theory [2,12,13], reaching the overriding conclusion that levelsfertility were levels significantly were significantly lower in urbanlower in areas urban than areas rural than areas rural [10 areas,14,15 [10,14,15].]. While urban–ruralWhile urban–rural analysis shedanalysis considerable shed considerable light on geographical light on geographical variations variations in fertility in behavior fertility inbehavior South Korea,in South the Korea, traditional the urban–ruraltraditional dichotomyurban–rural is criticizeddichotomy as is geographically criticized as crudegeographically [16]. Lutz crude further [16]. demonstrated Lutz further that demographicdemonstrated transition that demographic theory cannot transition anticipate theory the levelcannot of anticipate fertility in the countries level of at fertility or below in replacement countries fertility,at or below and he replacement remarked thatfertility, population and he remarked density in that particular population has density to be included in particular as a has variable to be in studiesincluded of regional as a variable variation in studies in human of regional fertility [variation17]. Alternately, in human social fertility interaction [17]. Alternately, theory argues social that fertilityinteraction and space theory are argues closely that related fertility because and space neighboring are closely locationsrelated because are likely neighboring to influence locations each are other throughlikely to shared influence cultural each andother social through norms shared [18, cultural19]. Their and argument social norms is that [18,19]. new Their ideas, argument innovations, is that and behaviorsnew ideas, are innovations, diffused over and space behaviors through are social diffused interactions over space such through as the social learning interactions and imitating such as process. the Therefore,learning suchand imitating a process process. takes place Therefore, in neighboring such a process areas to takes create place spatially in neighboring similar patterns areas to of create fertility, andspatially this process similar is oftenpatterns independent of fertility, of urban–ruraland this process characteristics is often [20independent]. Social interaction of urban–rural theory is alsocharacteristics consistent with [20]. Tobler’sSocial interaction first law theory of geography: is also consistent “Everything with isTobler’s related first to everythinglaw of geography: else, but near“Everything things are is more related related to everything than distant else, things” but near [21 things]. Although are more several related studies than distant have underscored things” [21]. the diffAlthoughusion effects several on fertility studies declinehave underscored in South Korea the diffusion [22–24], iteffects is far fromon fertility clear howdecline the in di ffSouthusion Korea process [22–24], it is far from clear how the diffusion process spatially occurred. Beyond these causal spatially occurred. Beyond these causal mechanisms, regional fertility patterns can be explained by mechanisms, regional fertility patterns can be explained by migration effects [25]. First, socialization migration effects [25]. First, socialization hypothesis says that the fertility behavior of migrants in hypothesis says that the fertility behavior of migrants in destination regions reflects fertility destination regions reflects fertility preferences in their original regions. Therefore, migrant fertility preferences in their original regions. Therefore, migrant fertility levels are similar to the fertility levels levels are similar to the fertility levels of the population at the origin regions. Second, adaptation of the population at the origin regions. Second, adaptation hypothesis states that migrants can be hypothesis states that migrants can be resocialized and adopt the dominant fertility behavior at the resocialized and adopt the dominant fertility behavior at the destination environment. Third, destinationselection hypothesis environment. explains Third, that selection people hypothesiswho are inclined explains to have that fewer people children who are possibly inclined migrate to have fewerto urban children areas possibly to enjoy the migrate greater to income urban areasopportunities to enjoy offered the greater by cities, income and people opportunities who are oinclinedffered by cities,to have and more people children who are possibly inclined move to haveto rural more areas children where possiblycosts of raising move children to rural areasare lower. where In costssum, of raisinggeographical children variations are lower. in In sum,fertility geographical cannot simply variations be explained in fertility by cannota single simply and universal be explained theory by a singlebecause and the universal interconnection theory because between the sociodemographic interconnection between factors and sociodemographic TFRs contains a factorscomplex and array TFRs containsof local a contexts complex [26]. array of local contexts [26]. TheThe development development ofof geographicalgeographical information information systems systems (GIS) (GIS) and and the theincreasing increasing availability availability of ofgeoreferencing georeferencing data data have have allowed allowed for for
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