This paper studied balanced regional development focused on employment in Korea, by analyzing regional disparity between regional and industrial employment. A Gini-coefficient decomposition method and Panel Granger causality test were conducted, using raw data of the Census on Establishments reported by the Statistics Korea. The regional and industrial disparity of employment, based on the Gini-coefficient decomposition method, have increased by year. However, the growth rates of disparity are on the decrease. Most of employment disparity occurred from regional disparity between SMA (Seoul Metropolitan Area) and Non-SMA. Industrial disparity are occurred mainly by the service industry. The amount of contribution to the whole disparity of inter/intra regional employment was differed by each industrial sector. Also the causal relationship between employment growth of manufacture and that of service industry was analyzed by Panel Granger causality test. In national level, the employment growth in manufacture industry has conduced that in service industry. On the other hand, in the Non-SMA, only the employment growth in manufacture industry has augmented that in service industry. In conclusion, to reduce employment disparity, the strategy for balanced regional development should be emphasized. Different strategies are needed across regions and industries. Basically creating new job in the Non-SMA is inevitable. In view of stable employment, manufacture industry is more desirable rather than service industry.

This paper analyzed the disparity and causality between regional and industrial employment to invigorate balanced regional development of employment-side. This paper conducted of a Gini-coefficient decomposition method and Panel Granger causality test using the row-data of the Census on Establishments that were obtained from Statistics Korea. As a result of Gini-coefficient decomposition, although the growth rates of Gini-coefficient of employment are on the decrease, Gini-coefficient still increase in Korea. Most of employment disparity occurred from regional disparity between SMA (Seoul Metropolitan Area) and Non-SMA and from industrial disparity within the service industry. The amount of contribution to total disparity of inter/intra regional on employment were differed by industry. The causal relationship between an employment growths in the manufacture industry and an employment growths in the service industry were analyzed using a Panel Granger causality test. As a result, mutually causality were estimated in the analysis of national dimension. However, when limited region to the Non-SMA, only the employment growth in manufacture industry increases the employment growth in service industry. In order to reduce an employment disparity, strategies for resolving the regional disparity by industry are needed. For regional employment growths, strategies for the service industry in the SMA, and for the manufacture industry in the Non-SMA are needed.

기상은 인간의 삶에 있어 많은 부분에 영향을 미치고 있다. 그 중에서 기상 현상으로 인한 재해는 인간의 삶을 유지함에 있어 큰 위협으로 다가오고 있다. 소방방재청의 재해연보에 의하면 기상 현상으로 인한 재해 피해의 횟수는 매년 조금씩 증가하고 있으며, 피해액 또한 증가하는 추세를 보이고 있다. 이러한 기상재해와 관련하여 기상청은 특보 기준을 정하고 기상 현상에 대해 주의보 및 경보를 발표하고 있다. 그러나 동일한 기상현상이 일어나더라도 각 지역의 위치와 기반시설의 차이에 따라서 위험지역일수도, 위험지역이 아닐 수도 있으므로 동일한 기준을 모든 지역에 적용시키는 것은 문제의 소지가 있다.하여 본 연구에서는 여러 자연재해 중에서 특히 큰 피해를 입고 있는 태풍과 관련하여 소방방재청에서 매년 발행하는 재해연보와 일본 태풍센터에서 제공하는 Best Track 자료의 태풍의 이동경로, 태풍의 강도 등 여러 변수 및 지역 특성과 피해액을 분석하여 태풍 재해의 취약지역을 구분하고자 한다.

Daily living area can be delimited differently depending on what area is to be focused. Based on regional interaction, the present study empirically analyzed the difference between living areas focusing on rural area and ones relying on urban area. We established two types of living areas in Busan-Ulsan mega city with different focus areas (rural versus urban), using travel OD data (2006). According to the result, the fonn of spatial clusters in urban living area differed from that of spatial clusters in rural area; the boundaries of living area were not fit to those of administrative areas in both types; and living areas in both types tended to extend over more than two administrative areas. The results cast some implications concerning spatial planning and policy for living area delimitation. First, since the spatial structure and interconnection of urban area differs to those of rural area, it is required to delimit living areas discriminatively depending on the objectives of the spatial plan. Additionally, the living area should be established more specifically and systematically by further subdividing the form of spaces depending on the objectives and types of the plan. Second, the administrative areas should be consolidated now that the difference of boundaries of administrative and living areas lead to inconvenience of residents, increased administration costs and scale diseconomy. Lastly, the living areas should be delimited by the metropolitan or mega city planning and thus be reflected to its offsprings.

As people get aged, we need to pay more attention to the elderly living condition with respect to welfare policy. The present study focuses on housing condition of elderly people living in rural area, and analyzes its determinants, periodical difference, and regional disparities, incorporating an index of minimum housing standard. This study applies multi-level logit model that has a strong statistical advantage that can take random aspects of household and regional context into account. We found that married couple household, presence of economically-active family members, higher education, specialized profession, migration and higher level of land price tend to lower the probability of residing in substandard housings. We also found that housing conditions for elderly people prove to be different by regions and it is particularly noticeable in mountainous rural areas in Gyeongsangnam-do and Gyeongsangbuk-do with the poorest elderly housing conditions. Results also implies that housing welfare policies should be implemented differently considering the target groups based on regional differences. We conclude with some additional policy implications for the elderly living in rural areas.