Migration is defined as the movement of people between residential places, and represents interactions between regions. Changes in migration involve changes in both the number of migrants toward/from regions and migration patterns across regions. However, most migration studies have focused only on the change in migrants, while no empirical study captures changes in migration patterns. In this paper, I present a function using the cosine similarity to measure changes in migration patterns, and apply it to 2001-2016 migration data of Korea. The results show that the migration patterns of Korea shifted in 2007, resulting in two distinct clusters. Local areas experienced various migration pattern changes despite few changes in the number of migrants.

Throughout the economic development era of Korea, migration occurred within a spatial hierarchy, with upward flows from rural areas to urban. The concept of step migration is a typical theory to explain these upward migration flows. Recent migration data and trends, however, indicate that migration-pattern regime shows strongly opposite-direction flows, with many of the major migration flowing downward on this national-spatial hierarchy, away from urban areas. In this study, we examine the most recent structure of migration flows up and down within the national-spatial hierarchy. We define seven tiers to tabulate origin-destination migration flows from population density of local administrative districts for the period 2001-2014, and then analyze the migration patterns between the tiers over time. The results show differentiated patterns of migration within the national-spatial hierarchy over time including specific states of migrants’ life cycles.

Recently many administrative institutes try to improve the viability of rural villages. For increasing the viability, not only infrastructures but internal vitality is necessary in rural villages. Nonetheless, most of governmental projects have been focused on infrastructures. For this reason, RDA(Rural Development Administration) designed and performed the RHL(Rural Healthy and Longevity village) project. This RHL project is not easy to evaluate the outcome because it consists of very intangible project items. In this paper, we developed a scoring model to evaluate the result of the RHL project. The scoring model based on DEA(Data Envelopment Analysis) was suggested to evaluate the quantity of personal activities in each village. Personal activities are classified into five categories: regional life, social life, productive life, outdoor life and indoor life. Evaluating indices of each category are developed and weighting values are evaluated by AHP(Analytic Hierarchy Process). The developed model was applied to Kumsan village and examined its applicability.

According to diverse studies in population migration, there has been a strong age-dependent population distribution in Korea. It is shown that a particular age-group tends to reside in a particular locale or community and the effect possesses usually statistical significance. We quantitatively address this issue: how certain division of age group resides in different region of the country, and investigate possible cause of this migration pattern for different age groups. In this study, population migration trend at age groups of 20s, 30s, 40s and 50s has been analyzed incorporating a spatial econometrics model that accounts for diverse statistical pitfalls such as spatial autocorrelation and spatial dependency. We found that migration trend for different age group corresponds to regional characteristics differently. The study concludes with some policy implications and suggests a need of further study.

This study tried to construct a direction in regional planning concerning the structural relationship between the ratio of aged population and the industrial characteristics. We investigated this structural relationship incorporating the aged population index and the number of classified companies. We applied diverse statistical analyses to understand the relationship. We classified the number of companies to reflect regional industrial characteristics using the principal component analysis. We applied a multiple regression model to understand the relationship between these two indices. The aged population index represents the degree of being old divided by the ratio of juvenile population and aged population. We found that such industries as manufacturing, service, and conveyance increase the ratio of juvenile population. However, industries such as tourism, waterworks, forestry, agriculture and etc. have a positive effect on the aged population index. In addition to these findings, we believe that the efficacy of this study is the possibility that can be used as the basic data when central or local autonomous entities need to adopt rural development planning.