• Journal of Labour Economics
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• v.32 no.2
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• pp.95-124
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• 2009

In this article, I were trying to analyze the listed manufacturing companies' trend of productivity and the corporate education & training effect after the financial crisis. According to the analysis, the listed manufacturing companies have decreased their productivity since financial crisis, and from such declining trend. jobless growth and a growth without physical and human capital investment has been observed. Furthermore, there is no efficient labor force coordination within the manufacturing industry; In order to analyze the effect of education & training investment on productivity more deeply, I have practiced the dynamic panel data analysis from constructing the micro panel data which consists of company level information 1997~2008. According to the consequences, dynamic panel data analysis solved the problem of the overestimating education & training effect fairly well.

• Journal of Information Technology Applications and Management
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• v.25 no.4
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• pp.185-196
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• 2018

This study investigates the social network among authors to improve the quality of Panel researches. Korea Health Panel (KHP), implemented by the collaborative work between KIHASA (Korea Institute for Health and Social Affairs) and NHIC (National Health Insurance Service) since 2008, provides a critical infrastructure for policy making and management for insurance system and healthcare service. Using bibliographic data extracted from academic databases, eighty articles were extracted in domestic and international journals from 2008 to 2014, April. Data were analyzed by NetMiner 4.0, social network analysis software, to identify the extent to which authors are involved in healthcare use research and the patterns of collaboration between them. Analysis reveals that most authors publish a very small number of articles and collaborate within tightly knit circles. Centrality measures confirm these findings by revealing that only a small percentage of the authors are structurally dominant, and influence the flow of communication among others. It leads to the discovery of dependencies between the elements of the co-author network such as affiliates in health panel communities. Based on these findings, we recommend that Korea Health Panel could benefit from cultivating a wider base of influential authors and promoting broader collaborations.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.99-109
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• 2021

This study aims to examine the causal links between the fiscal components, i.e., government expenditures (GE) and government revenues (GR), and their impact on the economic growth of the Association of Southeast Asian Nations (ASEAN) region. This analysis considered secondary panel data from 1990 to 2019 at an annual frequency. The data is obtained from the Asian Development Bank (ADB) and World Bank Database. A panel cointegration and panel DH causality (Dumitrescu and Hurlin) approach was employed on financial data at an annual frequency from 1990 to 2019. The findings from panel unit root and panel cointegration tests demonstrate that, at first, all the variables are stationary and cointegrated. The panel ARDL disclosed that GE has a long-run connection with GDP, is significantly and positively associated with economic growth in the long run, whereas GR is significant in the short run. The contribution of GE is high in sustaining economic growth as compared to GR. Also, cointegration regression disclosed that GE is more sensitive toward GDP, while GR is less elastic. Lastly, the findings reveal that bidirectional causality exists between GE and GR variables. These results have policy implications for sustainable economic growth in the ASEAN region.

• Health Policy and Management
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• v.25 no.4
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• pp.295-306
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• 2015

This study aims to examine the performance of public municipal hospitals through the analysis of data envelopment analysis, efficiency, profitability, and publicness by using panel data during period from 2006 to 2010. The main findings of the study are as follows. First, as a result of efficiency analysis during the period from 2006 to 2010, it was revealed that the number of staff by each job category, labor cost ratio, the number of operating beds need to be decreased. Second, the performance data represented by the indicators of efficiency, profitability and publicness were complementary and showed a tendency of being increased or decreased in same direction. Third, from the result of panel analysis, the efficiency was mainly influenced by the structural factors, while the profitability was influenced by managerial factors, and the publicness by medical environment. In conclusion, in order to enhance the performance of public municipal hospitals in Korea, it is important to harmonize the effort for efficiency, financial and policy support by central and local government, and the continuous participation of community residents.

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.53-60
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• 2021

Foreign direct investment (FDI) is especially important for developing countries. This study investigates the determinants of FDI in the case of Indonesia. Most empirical researches in this field used time series data of a single country or panel data of several countries. Although panel data analysis is more comprehensive, however results taken from cross-country analysis cannot be directly applied to any specific country in the dataset and therefore lacks practicality. In this research, panel data analysis of a single country is performed to overcome the aforementioned shortcomings. Five determinants of FDI are tested using panel data of 33 Indonesian provinces over 10-year period of time. Two methodologies are adopted, random/fixed effects model and Granger Causality. The results show that only market size significantly affects FDI when tested using both methodologies. Human capital and financial market development show significant result in one of the two methodologies. While, economic growth and infrastructure did not show any significant results at all. This research stresses the importance of comprehensive single country analysis since only one out of five commonly discussed determinants is applicable in the case of Indonesia. Governments should therefore carefully reconsider the use of cross-country analysis as a basis of their policy formulations.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.1-8
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• 2011

In panel studies in which the same respondents are interviewed repeatedly over the long term, panel attrition may cause the problems in the reliability of the result and the representativeness of the sample in panel study. In this article, we explore the risk factors of sample attrition in the first 11 waves of the Korean Labor and Income Panel Study (KLIPS) data covering the years 1998-2008, for which the survival analysis techniques such as life-table method and Cox proportional hazard model based on the time to the attrition of each respondent as the survival time of the respondent are applied.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.933-945
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• 2012

In this paper we used the KLIPS(Korean Labor and Income Panel tudy) data that surveyed from 2006(wave 9) to 2009(wave 12). Other previous studies are concerned with the panel attrition in the early wave, but this study classifies the response pattern and investigates some factors that influence panel attrition when the panel tends to stabilize. It was revealed that panel attrition was influenced by relocation and housing type through the logit model. Besides it was appeared that panel attrition was affected by the monthly living expenses and the overall household income through the decision tree.

• Korean Journal of Legislative Studies
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• v.23 no.2
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• pp.147-177
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• 2017

Although a number of empirical studies found that political ideology plays a significant role in Korean elections, they entirely rely on cross-sectional data analysis. In contrast to previous research, this study investigates the effects of ideology in the 2012 Korean presidential election through standard panel data analysis. Specifically, using "EAI Panel Study, 2012", the effects of ideology on both candidate evaluation and vote choice were examined via fixed effects, random effects, and pooled regression analysis. And the results from applying the two most popular models of ideological voting, the proximity model and the directional change model were also compared. The results show that candidate evaluations and vote choice during the election (April, 2012- December, 2012) were significantly influenced by the ideological difference between voters and candidates, independent from partisanship and other standard socio-demographic factors. And this ideological voting during the election seems better captured by the directional change model than by the proximity model.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.145-150
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• 2017

This study aims to analyze panel data using OECD Health data of 34 years to examine how significant the inequality of income is to the inequality of health. The data was from OECD's pooled Health data of 32 countries from 1980 to 2013. The process of determining analysis model was as follows; First, through the descriptive statistics, we examined averages and standard deviation of variables. Second, Lagrange multiplier test has done. Third, through the F-test, we compared Least squares method and Fixed effect model. Lastly, by Hausman test, we determined proper model and examined effective factor using the model. As a result, rather than Pooled OLS Model, Fixed Effect Model was shown as effective in order to consider the characteristics of individual in the panel. The results are as follows: First, as relative poverty rate(${\beta}=-19.264$, p<.01) grows, people's life expectancy decreases. Second, as the rate of smoking(${\beta}=-.125$, p<.05) and the rate of unemployment (${\beta}=-.081$, p<.01) grows, people's life expectancy decreases. Third, as health expenditure(${\beta}=.414$, p<.01) shares more amount of GDP and as the number of hospital beds(${\beta}=-.190$, p<.05) grows, people's life expectancy increases.