• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Journal of Energy Engineering
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• v.26 no.2
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• pp.80-92
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• 2017

This paper attempts to estimate the diesel fuel demand function in Korea using panel data panel data of 16 major cities or provinces which consist of diesel demands, diesel market prices and gross value added from the year 1998 to 2015. I apply panel GLS(generalized least square) model, fixed effect model, random effect model and dynamic panel model to estimating the parameters of the diesel fuel demand function. The results show that short-run price elasticities of the diesel fuel demand are estimated to be -0.2146(panel GLS), -0.2886(fixed effect), -0.2854(random effect), -0.1905(dynamic panel) respectively. And short-run income elasticities of the diesel fuel demand are estimated to be 0.7379(panel GLS), 0.4119(fixed effect), 0.7260(random effect), 0.4166(dynamic panel) respectively. The short-run price and income elasticities explain that demand for diesel fuel is price- and income-inelastic. The long-run price and income elasticities are estimated to be -0.4784, 1.0461 by dynamic panel model, which means that demand for diesel fuel is price-inelastic but income-elastic in the long run. In addition I apply dummy variable model to estimate the effect of 16 major cities or provinces on diesel demands. The results show that diesel demands is affected 10 regions on the basis of Seoul.

• 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.

• Korea Trade Review
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• v.41 no.5
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• pp.373-389
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• 2016

This study mainly investigates the port SOC's impact on trade volume. In order to investigate the relationships between port SOC and trade volume, we did the empirical analysis using panel data regression and fixed effects model. The total period of 97 years and 1,082 ports' information were applied to panel data and regression model. According to the results, the coefficients of development of container berth, development of bulk berth, maintenance of port, the jetty facilities like breakwater have positive(+) impact on the dependent variable, the trade volume. Especially, the jetty facilities show a strongly positive impact on trade volume. On the other hand, the development of new port and navigation facilities like lighthouse have a negative(-) impact. In examining Hausman test and LR test, the fixed effect model is statistically more appropriate than the random effect model for this study.

• The Journal of Fisheries Business Administration
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• v.51 no.1
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• pp.81-96
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• 2020

The purpose of this paper is to analyze factors affecting the net income of regional and industrial fisheries cooperatives in South Korea using panel data. This paper utilizes linear or GLS regression models such as pooled OLS model, fixed effects model, and random effects model to estimate affecting factors of the net income of regional and industrial fisheries cooperatives. After reviewing various tests, we eventually select random effects model. The results, based on panel data between 2013 and 2018 year and 64 fisheries cooperatives, indicate that capital and area dummy variables have positive effects and employment has negative effect on the net income of regional and industrial fisheries cooperatives as predicted. However, debt are opposite with our predictions. Specifically, it turns out that debt has positive effect on the net income of regional and industrial fisheries cooperatives although it has been increased. Additionally, this paper shows that the member of confreres does not show any significant effect on the net income of regional and industrial fisheries cooperatives in South Korea. This study is significant in that it analyzes the major factors influencing changes in the net income that have not been conducted recently for the fisheries cooperatives by region and industry.

• 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.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.51-64
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• 2017

Objectives : This study examined the effect of private health insurance on medical care utilization by subscription type. Methods : The data used were the six waves of the Korea Health Panel (2009-2014), and 16,187 persons were the subjects of the analysis. We performed a panel regression with a fixed effects model. Results : Indemnity private health insurance was positively related to the number of physician visits, number of admissions, and total length of stays. However, fixed-benefit private health insurance was not related to medical care utilization. Conclusions : The result of this study, which shows the difference by subscription type in the effect of private health insurance on medical care utilization, suggests that continuous monitoring of indemnity private health insurance is needed in the future.

• International Commerce and Information Review
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• v.11 no.2
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• pp.111-126
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• 2009

This study analysed determinants of Foreign Direct Investment to ASEAN+ 3 member nations using panel data for which cross-sectional data are combined with time series data. The data for the analysis included the amount of FDI, GDP, and indexes of economic independence. This study collected data from six nations(Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) whose data were easily available, China and Japan from 2003 to 2007 and analysed them. The results are summarized as follows: Using the pooled OLS method, we found Model 2 had the highest explanatory power whose adjusted R-squared was 89.4%, which accounted for about 89% of foreign investment. Using the fixed effect model, Model 2 had the highest explanatory power whose adjusted R-squared was 96.8%, which accounted for about 97% of foreign investment. Using the probability effect model, Model 5 had the highest explanatory power, but in respect to its statistical significance, only GDP was 1% significant and the rest variables had no significance.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.769-782
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• 2020

Interest in fruit and vegetables has increased due to changes in consumer consumption patterns, socioeconomic status, and family structure. This study determined the factors influencing the demand for fruit and vegetables (strawberries, paprika, tomatoes and cherry tomatoes) using a panel of Rural Development Administration household-level purchases from 2010 to 2018 and compared the ability to the prediction performance. An artificial neural network model was constructed, linking household characteristics with final food expenditure. Comparing the analysis results of the artificial neural network with the results of the panel model showed that the artificial neural network accurately predicted the pattern of the consumer panel data rather than the fixed effect model. In addition, the prediction for strawberries was found to be heavily affected by the number of families, retail places and income, while the prediction for paprika was largely affected by income, age and retail conditions. In the case of the prediction for tomatoes, they were greatly affected by age, income and place of purchase, and the prediction for cherry tomatoes was found to be affected by age, number of families and retail conditions. Therefore, a more accurate analysis of the consumer consumption pattern was possible through the artificial neural network model, which could be used as basic data for decision making.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.153-170
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• 2020

The Educational Restitution Rate is an important parameter that determines the quality of university education. This paper analyzed data from 148 private universities over the 10 years from 2009 to 2018 using data mining techniques in Korea. A significant causal relationship is detected in the fixed effect model as a result of the panel estimation. And the scale of faculty expansion and fund management, which are the university evaluation indicators, and the size of basic funds, respectively, have a positive effect on the ERR, which is within the confidence interval. In the analysis, the more private universities improve the tuition dependence rate, the more decisively positive affecting ERR. As a result of nonparametric regression estimation, when the faculty expansion ratio is reinforced, the effect of economies of scale is detected in some sections, the improvement of the tuition dependence rate, and the result value is generated through the improvement that results are derived at a certain point in time. We hope that the university based on this study can be a basic Indicators for the diagnosis of basic competencies and policy of student-centered education.