Study on the Role of Foreign Affiliates in GVCs Trade

최명식,Serah Choi,Bongsuk Sung 국제인문사회연구학회 2024 Studies on Humanities and Social Sciences (SHSC) Vol.6 No.1

Study on the Role of Foreign Affiliates in GVCs Trade Myoungshik Choi,* Serah Choi,** & Bongsuk Sung*** Abstract: This study investigates the multinational affiliates play an important role in explaining the international trade and investment. It analyzes both the self-selective effect which explains why some firms operate in more than one country while others do not and the learning-by effect which explains why firms use vertical supply chains rather than simply use own foreign facilities. Our empirical results are: First, the high productivity of firms increases FDI. Second, the integration increases foreign affiliates. Third, value-added trade within global value chains increases the profits of both exporters and foreign affiliates. Fourth, intra-firm trade decreases the profits of exporters and foreign affiliates. Key implications stand out: One is that the higher productivity of firms can increase the network of FDI-international trade. The other is that global value chained trade can increase the profits more than interiorization of one firm. This study suggests that it could be more benefits for high productive firms to increase GVCs free trade. Key Words: Foreign Affiliates, Global Value Chains, Learning-by Effect, Self-selection Effect, Value-added Exports □ Received: Jan. 1, 2024, Revised: Feb. 13, 2024, Accepted: Feb. 20, 2024* First Author, Professor, Kyonggi Univ., Email: msc50355@gmail.com** Co-author 1, Graduate Student, Sungkyunkwan, Univ. *** Co-author 2, Professor, Kyonggi Univ.

Promoting the utilization of plant, animal and microbial genetic resources for research and development in biotechnology: evidence on researchers' preferences for specific attributes from Korean genebanks

Sung, Bongsuk,Hwang, Kyungyun Cambridge University Press 2017 Plant genetic resources Vol.15 No.3

<P>With regard to the survey data of Korean researchers using genetic resources from three genebanks administered by the Korea Research Institute of Bioscience and Biotechnology, we conducted conjoint and cluster analyses to estimate the relative importance of genetic resource (microbial, plant and animal) attributes among the researchers. Our results indicate that Korean researchers view price (cost of acquiring an accession), high new functionality (functional properties of germplasms for specific applications and uses) and completely uncovered genomic information (about mutation, genetic transformation, genomic function and pathways) as far more important in decision-making about R&D use of microbial, plant and animal genetic resources, respectively, than other attributes. Furthermore, this study shows that researchers conducting R&D in the microbial and plant genetic resource sectors especially prefer resources from specific domestic environments and Korean indigenous species, respectively. The study also sheds light on different patterns of researcher segments in terms of utilities of attributes and subgroups of researchers who have common needs in the three genetic resource sectors. We proposed some policy and strategic implications based on the results of this study.</P>

정책의 혁신효율성과 수출성과 간 동태관계 분석

성봉석 ( Bongsuk Sung ),이벽규 ( Byeouk-gyu Lee ),조원권 ( Won-guon Cho ) 경희대학교 사회과학연구원 2016 社會科學硏究 Vol.42 No.2

본 연구는 정책의 혁신효율성이 수출성과에 미치는 동태적 영향을 분석하였다. 분석은 1995년-2012년 사이의 OECD 16개 국가의 태양 및 풍력 에너지 산업 패널 자료를 이용하여 수행되었다. 동태패널 프레임워크 분석을 통해 실증분석을 위한 모형을 설정하고, 모형 의 내생성과 이분산성 등의 문제를 해결하기 위해 차분 GMM(difference generalized method of moments)을 추정하고, 그 계수에 대한 월드검정을 통해 인과관계를 파악하였다. 분석결과, 태양 및 풍력 에너지 산업 모두 정책의 혁신효율성과 수출성과 간에는 장기 및 단기적으로 직접적인 동태적 관계가 형성되어 있지 않은 것으로 나타났다. 그렇지만, 풍력에너지 산업의 경우 수출이 혁신효율성에 영향을 미치며, 이는 곧 GDP 제고에 기여하고 있는 것으로 나타났다. 태양에너지 산업의 경우 수출과 GDP 간 단기적으로 양방향 관계가 형성되고 있는 것으로 나타났지만, 정책의 효율성까지는 이르지 못하는 것으로 나타났다. The study is to test the dynamic relationship between innovative efficiency of policy and export performance in solar and wind energy technology industries using panel data for 16 OECD countries over the period, 1995-2012. We set up the model to test the question of how innovative efficiency of policy may affect export performance based on the results of panel framework analyses. To deal with the correlation and endogeneity problems, we estimate difference generalized method of moments, in which the coefficients are tested by performing Wald-tests. The results of the study show that in the two sectors, there is no dynamic bilateral casual relationships between innovative efficiency and export performance in the long and the short run. In wind energy technology sector, export has a positive effect on innovative efficiency of policy, which contributes to enhancement of GDP in the short run. In solar energy technology sector, the short-run bilateral casual relationship between export and GDP exists, which, but, does not lead to increase in innovative efficiency of policy.

재생에너지 산업에 있어서 정책지원의 동태적 효율성과 수출성과 간 관계분석: 동태패널접근

성봉석(Bongsuk Sung),송우용(WooYong Song) 한국무역연구원 2016 무역연구 Vol.12 No.1

This paper tests the relationship between dynamic (innovative and green-innovative) efficiencyof government policy and export of renewable energy technologies using the dynamic panelapproach. Panel data for 20 Organization for Economic Cooperation and Development (OECD)countries for the period covering 1994-2012 were used. Taking into account the results ofpanel framework analyses, the panel vector autoregression (VAR) model in the first differencewas used to test the relationship among the variables in question. Panel generalized method ofmoments (GMM) estimation was conducted, then on the basis of the difference in GMMestimation results, causality was determined by running Walt tests on the coefficients ofvariables. The results from the study show that there is no long-run linear causal relationshipbetween dynamic innovative or green-innovative efficiency of policy and export. Moreover,there is a short-run linear causal relationship running from dynamic innovative efficiency ofpolicy to export, and between dynamic green-innovative efficiency of policy and export

유전자변형생물체 및 제품의 시장접근 영향 요인

성봉석 ( Bongsuk Sung ),유승훈 ( Seunghun Yu ) 한국유통경영학회(구 한국유통정보학회) 2015 유통정보학회지 Vol.18 No.2

Purpose: Purpose - We investigate how the industrial use of GMOs is defined, what factors may affect firms’ industrial use of GMOs, and how firms’ industrial use of GMOs may influence their economic performance, taking into account the normative message that firms must do in a way of something that is sustainable development. Research design, data, and methodology: This study tested the links between the causes and effects of a firm’s industrial use of GMOs in the context of socially sustainable development using survey data from South Korean firms. The study used a structural equation modeling approach via PLS for data analysis. Results: The analysis aimed to compare food/beverage sector with medical/pharmaceutical sector. The empirical results show that sociopolitical and economic pressures vary across the two sectors and have positive effects on firm performance in the two sectors. The study also finds that activities to secure both social and economic legitimacy involve enhancing a firm’s economic performance. Conclusions: It was confirmed that there is a structural relationship between sociopolitical and economic forces, firms’ activities to secure social and economic legitimacy related to the industrial use of GMOs and their economic performance.

기업이질성에 근거한 수출 참여 예측: 딥러닝을 이용한 시계열 분류

성봉석 ( Bongsuk Sung ),서일정 ( Il-jung Seo ) 한국유통경영학회(구 한국유통정보학회) 2020 유통경영학회지 Vol.23 No.6

Purpose: This study is to predict firms’ export participation based on firm heterogeneity, considering the situation where many countries around the world try to promote firms’ entry to export markets from the perspective of heterogeneous firm trade framework these days. Research design, data, and methodology: We used the 13-year time series data from the business activity survey produced by the Statistics Korea. Total factor productivity, financial leverage, and R&D expenditure were used as input variables and export participation was used as an output variable for time series classification with deep learning. We have trained and compared the three deep learning models for time series classification: multi layer perceptron, fully convolutional network, and residual network. We implemented the models using the open source deep learning library Keras with the Tensorflow back-end. The models’ performance was evaluated using the mean of accuracy, precision, recall, and F1-score over the 10 runs on the testing data set. Results: The results showed that the fully convolutional network (FCN) architecture performs best for the time series classification task and the recall is higher than the precision. The accuracy of the best model is 0.86, the precision is 0.64, the recall is 0.80, and the F1-score is 0.71. Conclusions: This study contributes to promoting the understanding of deep learning approach to prediction of export participation in the context of heterogenous firm trade theory. The prediction focuses on the selection of non-exporting firms, from the perspective of policy orientation for excavating and making firms without exporting start exporting. We propose to be able to utilize the FCN for enhancing the effectiveness and efficiency of export promotion policies, in particular focused on increase in firms’ export participation, by interpreting three of the indicators being used for model evaluation, precision, recall, and F1-score, in the context of such policy.

재생에너지 기업의 수출에 대한 정책지원, 기업이질성과 기업 간 스필오버의 영향분석

성봉석 ( Bongsuk Sung ) 한국유통경영학회 2021 유통경영학회지 Vol.24 No.5

Purpose: Little attention has been paid to investigation of direct and indirect of policy and firm-specific factors on export in the renewable energy industry. To fill the gaps in the literature, this paper examines the relative importance of the effects of government supports, firm heterogeneity, and inter-firm spillovers on export. Research design, data, and methodology: A dynamic panel model is established to investigate the relationships between the variables in question. We use the panel data for solar energy technology firms in Korea to test the relationships. We conduct various diagnostic tests to see whether first-order autocorrelation, cross-sectional dependence, homoscedasticity, and unit-root exist. Considering the results of the diagnostic tests, the empirical model is established to test the nexus between the variables, which is estimated for the full sample of the data and two sub-samples of the data over 1980-2001 and 2002-2019 period, using system generalized method of moments(GMM). Results: For the full sample, R&D subsidy has a significant positive direct and indirect (spillover) effect on firms’ export. Non-R&D subsidy has a positive spillover effect on firms’ export, but does not directly affects. Total factor productivity has a direct and positive effect on firms’ export. Firms’ export is promoted by firm age, not inter-firm competition. Implications: Unlike the existing literature focusing on the direct effects of policy supports on export at the industry level, this study contributes to further extending our understanding of the direct and spillover effects of policy supports and firm heterogeneity on export at the firm level. The main results of the study, and policy implications is helpful for increasing realistic policy applicability, by applying them to firms that are actual beneficiaries of public subsidy.

환경에 대한 해외직접투자의 영향

성봉석(Bongsuk Sung),박상도(Sang-Do Park) 한국무역연구원 2017 무역연구 Vol.13 No.1

Currently, China is the second foreign direct investment (FDI) recipient behind the US, and the biggest emitter of greenhouse gases in the world. Moreover, the manufacturing industry in China is the largest contributor to its CO2 emissions, by accounting for more than 70% of the country’s energy-related CO2 emissions. In this context, the effects of FDI on the environmental in China have often been raised as a central issue. This study examines the FDI-environment nexus in China, using panel data for its manufacturing sub-sectors over the period, 2002 to 2015. We use System GMM estimator to test the relationship between FDI and CO2 emissions, taking into account the results from various panel framework analyses. The results show that FDI makes a contribution to reduction of CO2 emission in the China industry sector, supporting the pollution halo hypothesis, and industrial income has a positive effect on reducing CO2 emissions. However, the domestic capital stock although has a detrimental effect on the environmental. The study finds strong evidence of the persistence effect, showing that the level of carbon dioxide emissions in the previous period has a positive and highly significant effect on the current one. Some policy implications are suggested based on the results of this study.

기업의 지속가능한 성장에 대한 정부정책지원의 효과 분석

성봉석(Bongsuk Sung) 한국무역연구원 2018 무역연구 Vol.14 No.5

This article investigates the relationship between public policy and firms’ sustainable growth, using the unbalanced panel data for Korean renewable energy technology firms over the period 1993-2016. We conducted a variety of panel framework tests to confirm the characteristics of the data before establishing the empirical model. Pooled mean group (PMG) estimator is employed to test the long-run relationship between the variables examined in the study. The results of the study show that government support positively affects index of propensity to approach sustainable growth (SAGAP index), and that productivity, profitability, and knowledge assets have positive effects on the SAGAP index. However, leverage negatively influences the SAGAP index. We proposed policy implications based on the results of the study.

The relationship between export dynamics and technological capabilities in renewable energy technologies : A multi-sectoral analysis

Seunghun Yu,Bongsuk Sung,Kyungyun Hwang 한국무역연구원 2013 무역연구 Vol.9 No.2

This paper is to examine the dynamic relationship between export specialization and technological capabilities of renewable energy technology sectors, especially focusing on bio, wind and solar energy, using panel data from 21 OECD countries (1993-2008). Several panel unit root and cointegration tests are applied, and cross-sectional dependence is detected in the case of solar energy technologies. Subsequently, the long-run technological capacity elasticity is computed using the dynamic OLS and pooled mean group (PMG) techniques in the case of bio and wind energy technologies confirmed that there are co-movements among the variables. Panel system GMM estimations were conducted to avoid the correlation and endogeneity problems in the model. Then, based on the first difference GMM estimation results, causality is determined by running Wald tests on the coefficients of variables. There are solid and convincing evidence of a long-run relationship between export specialization and technological capabilities in bio and wind energy technologies. There is no causal relationship running from technological capabilities to export specialization but there is a positive causal relationship running from export specialization to technological capabilities in the case of bio and wind energy technology sectors. There is no bidirectional causal relationship between the two variables in solar energy technology. The results suggest that countries should instead set up long-run public policies to promote exports of renewable energy technologies. In particular, technological capabilities should continue to be directed toward creating reliable elasticity with regard to exports.