• Korea Trade Review
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• v.42 no.1
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• pp.217-236
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• 2017

The purpose of this study is to analyze the effects of IFDI on the regional growth of 16 subregions in Korea during 2000~2014 by applying the System GMM. As a result of the analysis, the IFDI flowed into Korea has showed a positive effect on regional economic growth such as capital formation, job creation, and export expansion. but import has showed a negative effect. and Human capital has showed a positive effect but not statistically significant. meanwhile, IFDI which was flowed in the regions has showed a positive effect on the GRDP of DK regions including Daegu and Kyongbuk, while the GRDP of Metropolitan including Seoul, Incheon and Gyeonggi and BUK regions including Busan, Ulsan, Kyongnam has showed a negative effect. there were observed similar trends in the complementarities between IFDI inflows and human capital. This study has confirmed that IFDI flows into Korea are an important factor for regional growth, but the growth effect on GRDP in the region differs according to regional characteristics. Therefore, this study has suggested that it is urgent to reorganize the industrial structure along with the IFDI attraction strategy suitable for regional characteristics in order to expand the growth effect of IFDI flowed into the regions.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.1-9
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• 2012

PURPOSES: A viscoelastic axisymmetric finite element analysis code has been developed for stress analysis of asphalt pavement structures. METHODS: Generalized Maxwell Model (GMM) and 4-node isoparametric element were employed for finite element formulation. The code was developed using $C^{+}^{+}$ computer program language and named as KICTPAVE. For the verification of the developed code, a structural model of a pavement system was constructed. The structural model was composed of three layers: asphalt layer, crushed stone layer, and soil subgrade. Two types of analysis were considered for the verification: (1)elastic static analysis, (2)viscoelastic time-dependent analysis. For the elastic static analysis, linear elastic material model was assigned to all the layers, and a static load was applied to the structural model. For the viscoelastic time-dependent analysis, GMM and linear elastic material model were assigned to the asphalt layer and all the other layers respectively, and a cyclic loading condition was applied to the structural model. RESULTS: The stresses and deformations from KICTPAVE were compared with those from ABAQUS. The analysis results obtained from the two codes showed good agreement in time-dependent response of the element under the loading area as well as the surface deformation of asphalt layer, and horizontal and vertical stresses along the axisymmetric axis. CONCLUSIONS: The validity of KICTPAVE was confirmed by showing the agreement of the analysis results from the two codes.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.419-429
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• 2022

The aim of this research is to examine how globalization affects coffee exports in the producing countries. This research used secondary data obtained from the International Coffee Organization, Pen World Table, World Bank, Food and Agricultural Organization, and KoF Globalization Index to achieve its goals. We used secondary data from 1990 to 2018 from various foreign databases. The research used a two-step system GMM (sys-GMM) to analyze the effect of globalization on coffee export in twenty-four producing countries. We found that export lag, gross domestic product (GDP), exchange rate, and the political globalization index (PGI) positively and significantly impact coffee exports. Meanwhile, coffee exports were unaffected by the level of export prices and the human capital index. Surprisingly, the trade globalization index has a negative impact on coffee exports. This demonstrates the unpreparedness of coffee-producing countries to face tough competition in trade globalization. The political globalization index, the final variable, has a positive impact on exports. With the opening up of world politics, it seems that the environment of democracy in producing countries is increasing. As a result, governments in these countries have adopted a policy of aggressively supporting coffee exports.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.81-92
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• 2022

The necessity for a theoretical explanation of the negative association between capital structure and company performance is identified in this study. By focusing on accounting metrics of business performance, this study is the first to investigate the moderating effects of firm size between these variables using logical reasoning. Due to the possibility of endogeneity, this study applies a two-step system GMM approach with data from 285 non-financial enterprises from PSX over a 21-year period. For robustness, we employed pooled OLS, fixed effect, and two-step difference GMM. Our data show that leverage has a detrimental impact on business performance, with size acting as a moderator in the same direction. Our analysis empirically supports some studies while refuting others due to inconsistent results in the literature, but no study has theoretically justified their negative link. We believe that because larger companies have more and easier access to capital markets, they focus primarily on the amount of return, even if the investment is inefficient in terms of the rate of return, but small businesses do not. As a result of this thinking, firm managers' performance suffers as a result of leverage.

• Journal of the Korean Regional Science Association
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• v.32 no.3
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• pp.45-62
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• 2016

The main purpose of this study is to investigate whether the gap of fiscal self-sufficiency rates of 16 provincial governments in Korea has been narrowed and to suggest some remedies based on the empirical results. The panel data set from 1998 to 2013 is used and pooled OLS and system GMM regression techniques are employed. The fiscal self-sufficiency rates show downward trend and ${\beta}-convergence$ exists in absolute and conditional convergence analysis. The speed of conditional convergence anlysis is proved to be faster than that of absolute analysis. Both metropolitan cities and prefectures show convergence of fiscal self-sufficiency rates. We have found out that in the case of metropolitan cities, the proportion of workers in the tertiary industry has positive effect on fiscal self-sufficiency rates and in the case of prefectures number of cars per capita has positive effect. And in both cases increase in old population has negative effect.

• Economic Analysis
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• v.17 no.4
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• pp.30-51
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• 2011

Since the previous studies on the effects of trade liberalization implicitly assume that trade liberalization affects economic performance only in any point in time, they inevitably are static. Static evaluations fail to account for cumulative dynamic effects of trade liberalization that affect continuously economic performance. This paper tries to fill this gap of the previous studies in this field, estimating cumulative effects of trade liberalization on economic performance by employing an dynamic version of empirical model. One of important empirical issue is controlling bias from endogeneity. To resolve this problem, this paper employes system GMM that uses lagged first-differences as instruments for level equations and lagged levels as instruments for first-differences equations. It improves upon cross-section estimators because it controls for the potential bias induced by the omission of industry-specific effects and the endogeneity of all regressors. This study investigates the effects of trade liberalization in Korean manufacturing for the period from 1988 to 2005 and finds that cumulative dynamic effects of trade liberalization are present and bigger than static effects.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.181-187
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• 2021

The purpose of this study is to examine empirically the short- and long-run determinants of entrepreneurial activity in a sample of 15 the Middle East and North African economies between 2006 and 2018. More specifically, four groups of determinants are considered in the analysis, namely economic, demographic, business environment, and institutional. Given the autoregressive feature of the entrepreneurial activity process, a dynamic panel data model is estimated using the system GMM estimator. Findings reveal that unemployment, trade openness, population density, and economic freedom are the main drivers of new business creation in the short-run, while the cost and number of procedures to start a new business negatively affect entrepreneurship. In the long-run, the same findings hold true. Moreover, education and political stability and the absence of violence/terrorism positively affect entrepreneurial activity. Policy recommendations are accordingly designed.

• The Journal of Economics, Marketing and Management
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• v.11 no.3
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• pp.25-35
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• 2023

Purpose: This paper examines whether foreign aid influences public sector efficiency in policy areas of administration, education, and stability. Research design, data and methodology: The study uses panel data of 77 aid recipient developing countries over the period 2000-2020 and employs various panel data techniques to estimate. Results: We found that a percentage change in foreign aid increases administrative efficiency by 0.02 to 0.04 on average ceteris paribus in the short run. On the other hand, a percentage increase in foreign aid decreases education efficiency by 0.005 to 0.006 on average. While the impact of foreign aid on the policy area of stability is insignificant. Conclusions: The empirical results of this study have important implications for both donors and aid recipient countries. It suggests that to get positive influence from foreign aid, in the area of education and stability, the recipient countries need to increase accessibility of secondary schools with quality education especially; technical and vocational. Also, the donor should provide a minimum threshold amount of foreign aid to developing countries for reforming the institutions' capacity building.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.9-16
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• 2005

This paper focuses on the study of the face authentication system and the robustness of fact authentication methods under illumination changes. Four different face authentication methods are tried. These methods are as fellows; PCA(Principal Component Analysis), GMM(Gaussian Mixture Modeis), 1D HMM(1 Dimensional Hidden Markov Models), Pseudo 2D HMM(Pseudo 2 Dimensional Hidden Markov Models). Experiment results involving an artificial illumination change to fate images are compared with each other. Face feature vector extraction based on the 2D DCT(2 Dimensional Discrete Cosine Transform) if used. Experiments to evaluate the above four different fate authentication methods are carried out on the ORL(Olivetti Research Laboratory) face database. Experiment results show the EER(Equal Error Rate) performance degrade in ail occasions for the varying ${\delta}$. For the non illumination changes, Pseudo 2D HMM is $2.54{\%}$,1D HMM is $3.18{\%}$, PCA is $11.7{\%}$, GMM is $13.38{\%}$. The 1D HMM have the bettor performance than PCA where there is no illumination changes. But the 1D HMM have worse performance than PCA where there is large illumination changes(${\delta}{\geq}40$). For the Pseudo 2D HMM, The best EER performance is observed regardless of the illumination changes.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.