• Korean Journal of Social Welfare
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• v.58 no.2
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• pp.119-141
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• 2006

This study aims to explore the status and characteristics of the working poor and to identify the major determinants of their statistic status. For this, longitudinal panel data (from 2nd wave(1999) data to 7th wave(2004) data) from Korean Labor and Income Panel Study (KLIPS), is used. The data is analyzed by adopting Hierarchical Generalized Linear Model (HGLM), which is known as an app.opriate data analysis method for the hierarchically structured data, to look at the factors that affect on the poverty status of the working people. The results show that 1) it is estimated that about 1 out of 10 working people (about 10.0%) are poor, and 2) sex, education level, marital status, region where they lives, employment status, occupation type, and industry type that they are working at are significant predictors in determining their poverty status. Unlike the results of the previous studies, however, the number of the household member, age are not influenced on their poverty status. Based on these results, several policy implications are presented at the end of this paper.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1169-1182
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• 2016

Cancer is a typical cause of death in Korea that becomes a major issue in health care. According to Cause of Death Statistics (2014) by National Statistical Office, SMRs (standardized mortality rates) in Busan were counted as the highest among all cities. In this paper, we used data of Busan Regional Cancer Center to estimate the extent of the cancer incidence rate and cancer mortality rate. The data are considered in small areas of administrative units such as Gu/Dong from years 2003 to 2009. All cancer including four major cancers (stomach cancer, colorectal cancer, lung cancer, liver cancer) have been analyzed. We carried out model selection and parameter estimation using spatial multi-level model incorporating a spatial correlation. For the spatial effects, CAR (conditional autoregressive model) has been assumed.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.146-173
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• 2014

Extant studies have explained that firm's innovations including technological product and process innovations contribute to its competitive advantage and growth, thereby supporting competitiveness and growth of industry. These studies, however, have focused mainly on the role and effect of technological change that is primarily measured by the patent numbers and R&D intensity. Aside from these traditional streams, there has been growing interest on the impact by various dimensions of innovation including non-technological innovations. Apart from the discussions on the dimensions and scope of innovation, stages or processes of innovation also have been studied. Extant studies on innovation process model, however, has limited its interests in the structure of the transformation of knowledge. This study have established a comprehensive model embracing operational and financial performance to investigate the causal paths between innovation and firm performance. Using multi-level generalized linear model with path analysis, this study have found results as follows: First, the processes from innovative activities to innovation output and outcomes including operational and financial performance at firm level were verified. Secondly, the influence of innovation decreases gradually as the distance away from the direct outputs of the innovation increase in the direction of financial outcomes. Third, the effect of innovation on the sales growth rate is higher for small businesses than for medium-sized businesses. The effect of innovation on the profit rate, however, is significant only for medium-sized businesses. For large businesses, innovation has no positive significant impact on any financial performance at all. Fourth, Fourth, the appropriability of innovation has positive impacts on innovative performance, patent applications, and operational performance.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Journal of the Korean Society of Child Welfare
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• no.55
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• pp.143-171
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• 2016

This study investigated the effects of individual characteristics, school factors, and community factors on adolescent school violence behaviors. Data from a total of 1,777 middle school students from 50 schools in the Seoul and Gyeonggi regions were used for analysis. A hierarchical generalized linear modeling was employed to conduct a two-level analysis. Results showed that adolescents' individual factors, including attitudes toward violence, parental attachment, child abuse experiences, and affiliation with delinquent peers, as well as school factors including teacher's abusive classroom discipline, affected adolescent school violence behaviors. In addition, neighborhood disorder was found to be significantly positively correlated with adolescents' school violence. The results of this study suggest that for an understanding of school violence and to prepare countermeasures accordingly, integrated consideration of various environmental contexts in adolescents' daily lives, such as family, school, and community environments, is necessary. A multidimensional, integrated intervention plan to effectively resolve school violence based on these research results is discussed.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.923-932
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• 2008

We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.