• 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.

• International Commerce and Information Review
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• v.14 no.3
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• pp.307-322
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• 2012

The purpose of this paper is to examine determinants of export to the East Asia region, using panel unit root, panel cointegration framework, panel VECM (vector error correction model), panel FMOLS (fully modified OLS). Different panel unit root tests confirm that the data series are integrated processes with unit roots. When applying cointegration tests to long-run effect for aggregate panel data, a primary concern is to construct the estimators in a way that does not constrain the transitional dynamics to be similar among different countries of the panel. The regression equations are estimated by various panel cointegration estimators. The panel data causality results reveal that exchange rates has unidirectional effects on export and GDP, and there exists bidirectional causality between export and GDP. Also, the results from the panel FMOLS tests overwhelmingly reject the null hypothesis of zero coefficient. The panel cointegrating vectors show that the export has positive relationship with the GDP and ODI (overseas direct investment).

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.46-56
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• 2018

This paper aimed to identify main factors of community characters, which have an effect on the land surface temperature(LST) change and estimate the impacting coefficient(ratio) of factors in a significant level of statistics. Chungcheongbuk-do province was selected and then partitioned into city and county areas for the sake of convenience of modeling. LST time series data and the community character data were developed based on Terra Satellite MODIS data and collected from the National Statistical Office, respectively. By the cause and effect relationship between community characters and LST, regression coefficients were estimated using a penal model. In a panel modeling, LST and community characters were used as a dependent variable and explanatory variables, respectively. Panel modeling analysis was carried out using statistical package STATA14 and one-way fixed effect model was selected as the most suitable model to evaluate the regression coefficients in the study area. The impacting ratio of LST change by any explanatory variable derived from the regression coefficients of the panel model fixed. Impacting ratios for industrial areas, elevation ${\times}$ building, energy usage, average window speed, non-urban management area, agricultural, nature and environmental conservation, average precipitation were 3.746, 2.856, 2.742, 0.553, 0.102, 0.071 and 0.003, respectively.

• Environmental and Resource Economics Review
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• v.25 no.1
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• pp.89-112
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• 2016

In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

• Journal of Biomedical Engineering Research
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• v.38 no.5
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• pp.271-276
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• 2017

Cancer biomarkers are using in the diagnosis, staging, prognosis and prediction of disease progression. But, there are not sufficiently profiled and validated in early detection and risk classification of prostate cancer. In this study, we have devoted to finding a panel of serum biomarkers that are able to detect the diagnosis of prostate cancer. The serum samples were consisted of 111 prostate cancer and 343 control samples and examined. Eleven biomarkers were constructed in this study, and then nine biomarkers were relevant to candidate biomarkers by using t test. Finally, four biomarkers, PSA, ApoA2, CYFRA21.1 and TTR, were selected as the prostate cancer biomarker panel, logistic regression was used to identify algorithms for diagnostic biomarker combinations(AUC = 0.9697). A panel of combination biomarkers is less invasive and could supplement clinical diagnostic accuracy.

• 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.

• East Asian Economic Review
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• v.20 no.4
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• pp.493-517
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• 2016

This paper examines the persistent properties of 12 sectoral relative prices between Korea and Japan obtained following the Classification of Individual Consumption according to Purpose (COICOP) over the period of 1985-2016. Applying a new econometric method developed by Pesaran which controls for the cross-section dependence in a panel, we are not able to reject the hypothesis that the sectoral real exchange rates contain a common stochastic trend. On the other hand, the well-known panel unit root tests such as the IPS and LLC tests widely used by previous studies strongly reject the unit root hypothesis. Since the error term of the regression for our panel exhibits significant cross-section dependence, these opposite results justify that the use of the new econometric method is appropriate.

• Journal of Society of Preventive Korean Medicine
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• v.19 no.3
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• pp.57-66
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• 2015

Objective : Private health insurance coverage in Korean medicine has been reduced since October 2009 for preventing unnecessary utilization. The aim of this study is to identify how private health insurance coverage reduction affects on the Korean medicine utilization. Method : We analyzed the Korea Health Panel data from 2008 to 2012. Panel negative binominal regression model was used to analyze the relationship between private health insurance coverage reduction and utilization of outpatient service. Panel tobit regression analysis was used to identify the relationship between private health insurance coverage reduction and health expenditure of outpatient service. Results : Private health insurance coverage reduction significantly dropped both utilization and health expenditure of outpatient service by 9%, 9.22% respectively. In addition, therapeutic utilization significantly decreased up to 10%. Conclusion : Private health insurance coverage reduction seems to have an effect to reduce both utilization and the health expenditure of Korean medicine outpatient service. This effect was more noticeable in the therapeutic utilization. Thus, more elaborate policy will be needed to prevent unnecessary utilization of Korean medicine.

• Journal of Navigation and Port Research
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• v.44 no.5
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• pp.400-406
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• 2020

In this study, we first measured the malmquist productivity index by DEA among the Korean public firms. Second, there are 12 public corporations whose productivity (MPI) has decreased compared to 2014. This is mainly because of a decrease in productivity, as well as a decrease in the technical efficiency change index (TECI), impacted by the internal environment, and the increase in productivity because of an increase in the technology change index (TCI) impacted by the external environment. Finally, the analysis of the impact on the management assessment scores showed that the productivity (MPI), scale efficiency (CRS), size of sales, operating profitability, and total capital investment efficiency are significantly related (+), except for the asset turnover, which is a static financial ratio. Meanwhile, the management evaluation scores between the high-productivity public corporations and low-performing public corporations were significantly discriminating. Thus, it is confirmed that the nation's state-run companies must manage their MPIs in a time series to score high in management evaluation.

• Journal of Distribution Science
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• v.18 no.2
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• pp.59-67
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• 2020

Purpose: This study examines the relationship between formation of employment subcenters and regional industrial structures in Incheon. Research design, data, and methodology: We used the five-year panel data from 2012 to 2016 in 146 basic municipal units of Incheon to analyze panel regression models. Gross employment density and employment to population ratio were used as indicators of employment subcenters formation. The entropy index and Hachman index were used for analyzing the diversity and heterogeneity of industrial structures. Result: The analyses of two panel regression models showed that for the formation of employment subcenters, both the Entropy and Hachman index were significantly negative in most models. But tertiary industry was shown to have a significant positive relationship in all models. In the wholesale and retail sector, it was found that the average number of employees in the employment subcenters is significantly higher than that in the non-employment subcenters. Conclusions: The specialization of the industrial structure rather than the diversification contributes to the formation of the employment subcenters in Incheon. In particular, it can be considered that the wholesale and retail sector plays a very important role in forming the employment subcenters in many areas of Incheon.