• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.123-132
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• 2016

We can achieve the principle of parsimony and efficiency if homogeneity for panel time series model is satisfied. We suggest a Rao test statistic and a Wald test statistic for the test of homogeneity for panel AR(1) and derived the limit distribution. We performed a simulation to examine statistics with the same chisquare distribution when number of the individual is small and in common with large. We also simulated to compare the empirical power of the statistics in a small panel. In application, we fit panel AR(1) model using regional monthly economical active population data and test homogeneity for panel AR(1). It is satisfied homogeneity, so it could be fitted AR(1) using the sample mean at the time point. We also compare the power of prediction between each individual and pooled model.

• International Area Studies Review
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• v.16 no.1
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• pp.3-27
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• 2012

This paper adopts recently developed panel unit root test that is cross-sectionally robust. Cointegration test is also used to find whether regional house prices are in line with gross regional domestic production (GRDP) in the long run in Korea during 1989-2009. Based on the panel VECM and the panel ARDL models, we examine causal relationships among the variables and estimate the long-run elasticity. We find evidence of cointegration and bidirectional causal relationships between regional house prices and GRDP. The results of long-run estimates, using both fixed effect and ARDL models, show that house prices positively and significantly influence on the GRDP and vice versa. Together with these results, the findings of ARDL-ECM imply that there exists a long-run equilibrium relationship between house prices and regional economic variables even if there is a possibility of short-run deviation from its long-run path.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.95-101
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• 2011

This study proposes the accident estimation model developed based on the time-series cross-sectional data at 50 intersections in Cheongju. The data were collected repeatedly and accumulated from 2004 to 2007. This study focused on deriving the optimal among the various models including TSCSREG(Time Series Cross Section Regression). Four different models utilizing various elements affecting accidents were developed. Through a statistical test, it was found that the t values of independent variables of the fixed effect models were less than those of the random effect models. Two variables were then found to be positive to the accidents: the number of crosswalks at an intersection and the number of intersections.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1163-1170
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• 2014

The concepts and structure of intermittent panel time series data are introduced. We suggest a Wald test statistic for the test of homogeneity for intermittent panel first order autoregressive model and its limit distribution is derived. We consider the fitting the model with pooling data using sample mean at the time point if homogeneity for intermittent panel AR(1) is satisfied. We performed simulations to examine the limit distribution of the homogeneity test statistic for intermittent panel AR(1). In application, we fit the intermittent panel AR(1) for panel Mumps data and investigate the test of homogeneity.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.185-212
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• 2011

The purpose of this paper is to show the empirical analysis way for measuring the seaport efficiency by using the previous radial model and the newly modified non-radial models( panel additive model, panel RAM model, and panel SBM model)with Spearman rank order correlation coefficient(SROCC) for 20 Korean ports during 11 years(1997-2007) for 1 inputs(port investment amount) and 4 outputs(Number of Ship Calls, Port Revenue, Customer Satisfaction Score for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, consistency ratio of SROCC in terms of efficiency scores between radial and panel Additive model was over about 76% and overall consistency ratio was about 71.6%. Second, an efficiency of panel RAM model was higher than that of radial model with similarity. However, panel SBM model shows the very similar efficiency scores with panel radial model. Third, the slack size of radial model is smaller compared to non-radial model. Models' ranking orders in terms of efficiency scores, number of efficient ports are panel RAM model, panel SBM model, and radial model. The order from the minimum efficiency scores was the same order like just before. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like non-radial models(panel additive model, panel RAM model, and panel SBM model) for measuring the port performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.263-264
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• 2012

본 논문은 여러 개의 독립적인 시계열로 구성된 시계열 패널 자료를 이용하여 비선형 모형인 GRCA모형과 신경망을 이용하여 예측값을 구하여 서로 비교 분석하고자 한다. 먼저 GRCA모형에 대하여 연구하고 신경망의 구조와 예측값을 구하기 위한 여러 가지 변환함수를 유도한다. 단기 예측에서는 신경망 방법의 예측값이 더 좋았고, 장기예측에서는 비선형모형을 이용한 예측값이 더 좋은 것으로 나타났다.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.133-143
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• 2014

The paper uses a panel gravity model to analyse the determinants of export via Gwangyang port for the period from 2000-2012. The gravity model includes export via Gwangyang port, GDP and population of trading partners, the distances between Korea and its partners, and Korea-ASEAN FTA dummy. Hausman test shows up which one is exactly appropriate between random effect estimation and fixed effect estimation to use panel dataset. It depends on whether or not existence or nonexistence of the correlation between unobserved omitted factors and variables. Fixed effect estimation is suitable for this paper by the rejection of null hypothesis. An Empirical analysis of this paper shows GDP influences positive effects and distance influences negative effects to Gwangyang port trading partners. In addition, the results strongly supported the effects of Korea-ASEAN FTA on the growth of Gwangyang port export.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.55-70
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• 2000

본 논문에서는 내포오차성분을 가지는 패널회귀모형에서 회귀계수에 대하여 다양한 추정량들을 유도하고, 추정량들의 효율성을 모의실험을 통하여 평균제곱오차의 기준에서 비교하였다. 모의실험 결과, 제안된 FGLS 추정량들은 GLS추정량과 효율성에서 서로 큰 차이를 보이지 않았으며, 계산상 더욱 복잡한 ML, REML 추정량 및 MIVQUE와 거의 비슷한 효율성을 보여주었다.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.349-361
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• 2008

There has been abundant empirical research undertaken on the technical efficiency of Korean ports. Most studies have focused on the use of parametric and non-parametric techniques to analyse overall technical efficiency. This paper utilizes data for the period 2000-07 to offer a heterogeneous perspective on the overall efficiency of Korean ports. The framework assumes that ports use one input to produce one output; the output and input include port export(import) and regional export(import). This paper also employs panel analysis and heteroscedastic Tobit model to show the effect of the explanatory variables on the port efficiencies. The panel analysis shows that the regional export/total export has negative effect on the export efficiency while the regional import/total import has not any relations with the import efficiency. The heteroskedastic Tobit model shows that both regional export ratio and regional import ratio have negative effects on the efficiency while the gross regional domestic product has not any significant relations with the import efficiency.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.467-484
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• 2024

Longitudinal data are measured repeatedly over time from the same subject, so there is a correlation from the repeated outcomes. Therefore, when analyzing this correlation, both serial correlation and between-subject variation must be considered in longitudinal data analysis. In this paper, we will focus on the marginalized models to estimate the population average effect of covariates among models for analyzing longitudinal binary data. Marginalized models for longitudinal binary data include marginalized random effects models, marginalized transition models, and marginalized transition random effect models, and in this paper, these models are first reviewed, and simulations are conducted using complete data and missing data to compare the performance of the models. When there were missing values in the data, there is a difference in performance depending on the model in which the data was generated. We analyze Korea Health Panel data using marginalized models. The Korean Medical Panel data considers subjective unhealthy responses as response variables as binary variables, compares models with several explanatory variables, and presents the most suitable model.