• Journal of Korea Trade
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• 제25권1호
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• pp.18-33
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• 2021

Purpose - This paper investigates the causal relationship between logistics infrastructure development and the economic growth of Korea. Considering the industrial and economic structure of Korea, it is likely that logistics infrastructure is positively associated with the economic growth of the country. Design/methodology - The causal relationship between logistics infrastructure and economic development is estimated using Vector Autoregressive (VAR) and Vector Error Correction Model (VECM) considering long-run equilibrium between the two factors. To this end, a dataset consisting of 7 logistics infrastructure proxies and 5 economic growth indicators covering the period of 1990-2017 is used. Findings - It was found that causality, in general, runs from logistics infrastructure development to economic growth. Specifically, the results indicate that maritime transport is positively associated with the economic growth of Korea in terms of GDP and international trade. In addition, other modes of transport also have a positive impact on either the GDP or international trade of Korea. Originality/value - While existing studies in this area are based on either regional observations or a specific mode of transport, this study presents empirical evidence on causality between logistics infrastructure and the economic growth of Korea using a more comprehensive dataset. In addition, the findings in this paper can provide valuable implications for transport infrastructure development policies.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1657-1663
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• 2022

This study uses data from 1970 to 2016 to analyze the effect of nuclear energy use on CO₂ emissions and attempts to validate the EKC hypothesis using the Fourier Autoregressive Distributive Lag model in India for the first time. Because of India's rapidly rising population, the environment is being severely strained. However, with 22 operational nuclear reactors, India boasts tremendous nuclear energy potential to cut down on CO₂ emissions. The EKC is validated in India as the significant coefficients of GDP and GDP.² The short-run estimates also suggest that most environmental externalities are corrected within a year. Given the findings, some policy recommendations abound. The negative statistically significant coefficient of nuclear energy consumption is an indication that nuclear power expansion is essential to achieving clean and sustainable growth as a policy goal. Also, policymakers should enact new environmental laws that support the expansion and responsible use of nuclear energy as it is cleaner than fossil fuels and reduces the cost and over-dependence on oil, which ultimately leads to higher economic growth in the long run. Future research should consider studying the nonlinearities in the nuclear energy-CO₂ emissions nexus as the current study is examined in the linear sense.

• Smart Structures and Systems
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• 제31권2호
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• pp.183-197
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• 2023

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.235-243
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• 2022

To help the industry, outsourcing was found to be the most efficient method. An extensive literature analysis was done to assess the macroeconomic factors associated with outsourcing to supplement the anxious parties' decision-making process with evidence-based comprehensive tools. As a theoretical framework for evaluating these issues, transaction cost economies and resource-based perspective theories are investigated. Outsourcing is proven to be a result of energy crises and political instability. The advantages of outsourcing assist major industries in the economy. To discover the key drivers behind outsourcing, we used the vector autoregressive (VAR model) and step-wise regression techniques for the period 1992 to 2016. This research adds to the literature in that it not only explains the energy issue but also discusses the dilemma of political instability in the country in the context of outsourcing. The findings indicate that labor cost and export tendency have a positive impact on outsourcing strategy, which confirms the study's third and fourth hypotheses. Customs tax, inflation, and the unemployment rate, on the other hand, have a negative impact on textile outsourcing in Pakistan, according to the study's fifth, sixth, and seventh hypotheses.

• The Journal of Asian Finance, Economics and Business
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• 제9권3호
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• pp.33-42
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• 2022

Oil prices have become more volatile as a result of global economic contraction and control measures. Before and during the COVID-19 crisis, this study examines the relationship between oil price swings and daily stock returns in the power sector. The impact is investigated using a panel Vector Autoregressive (VAR) model. Granger causality tests are used to see if oil prices are effective in predicting returns. The dynamic impact of supply shocks is studied using Impulse Response Functions (IRFs). From January 2011 to May 2021, the study used daily data from all listed power sector enterprises on the Pakistan stock exchange. To investigate the differences in reactions between the Pre-COVID and COVID eras, the sample was separated into two groups. Oil shocks are inversely associated with daily firm stock returns. The conclusions are further supported by the lack of impact of stock prices on oil prices. The relationship, however, deteriorates during the COVID pandemic. We could not uncover any evidence of a significant relationship. In developing countries that rely on oil imports, the study sheds light on the utility of oil price shocks in daily stock return predictions.

• 유통과학연구
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• 제20권4호
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• pp.77-83
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• 2022

Purpose: This study aims to find the impact of international trade cooperation and distribution on foreign direct investment (FDI). The study also tests the impact of lag variables of trade cooperation and distribution on FDI in the future. Research design, data, and methodology: Autoregressive Distributed Lag model is applied to analyze the impact of chosen variables such as total trade (TRADE), trade openness (OPEN), the exchange rate (EXR), inflation (INF), and gross domestic growth (GDP) on FDI. Quarterly data is collected from Vietnam General Statistic Office, Vietnam General Department of Customs, International Monetary Fund, and The World Bank from 2006 to 2020. Stata 14 software is used to analyze the regression and test variables. Results: The findings indicate that TRADE, OPEN, INF, GDP, and their lags affect both positively and negatively on FDI in different periods. While OPEN still expresses an unclear impact on FDI. Moreover, this study proves that the FDI of a nation is influenced by international cooperation. Conclusions: This study indicates the importance of international trade cooperation and distribution in not only attracting foreign investment sources but also developing the economy. Findings are necessary bases for governments or authorities in signing international trade agreements in the future.

• The Journal of Asian Finance, Economics and Business
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• 제9권5호
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• pp.295-303
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• 2022

This study investigates the impact of globalization, coal consumption, and economic growth on CO₂ emissions in Malaysia by applying the Kuznets Environmental Curve model. The study employed the Autoregressive Distributed Lag modeling technique on time series data over the period of 1970-2018 to determine the short and long-run relationship between CO₂ emissions and a number of variables, including globalization, coal consumption, and economic growth. The results show that globalization increase CO₂ emissions in both the short and long run in Malaysia. Furthermore, the results reveal that economic growth and coal consumption degrade the environmental quality by accelerating the CO₂ emissions in the short-run and long run. As a result, the findings validate the Kuznets Environmental Curve hypothesis of an inverted U-shaped relationship between economic growth and CO₂ emissions in the long run for Malaysia. The findings of this study suggest that higher globalization levels and usage of coal consumption degrade the environmental quality in Malaysia. The findings also indicate the effect of economic growth on environmental degradation is positive at the initial stage but improves after the economy achieves a threshold level of income per capita in the economic development process with an inverted U-shaped pattern in the long run.

• The Journal of Asian Finance, Economics and Business
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• 제9권1호
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• pp.177-187
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• 2022

Theoretical literature agrees on the interaction between financial instability and economic activity but explains it's dynamic in two points of view: one is that the transmission mechanism occurs in one unique regime and the other reckons a shift of regime leads to the alteration of the transmission mechanism. This study aims to find evidence of the multi-regime transmission for ASEAN developing countries. The author employs the technique of Threshold vector auto regression using the financial stress index standing for financial instability. Monthly data is collected, covering a period long enough with many episodes of high stress in recent decades. There are two conclusions: (1) A financial shock has a negative and stronger impact on economic activity during a high-stress period than it does during a low-stress period; (2) the response of economic activity to a negative financial shock during high-stress periods is stronger than it is during normal times. The findings point to the importance of the financial stress index as an additional early warning indicator for the real economy sector, as well as the positive effect that a reduction in financial stress may have on economic activity, implying the importance of "unconventional" monetary policy in times of high financial stress.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.406-406
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• 2022

댐은 물을 담아두어 강수량에 따른 유량을 조절하거나, 하천의 물을 끌어와 사용할 수 있게 하는 역할 또는 모래, 자갈 등을 막아 걸러주는 역할 등을 수행한다. 우리나라의 경우 지역별, 계절별 강수량의 차이가 크며, 그로 인해 유량이 지역과 계절에 영향을 크게 받는다. 이런 변동성을 조절하기 위해 치수와 이수, 두 분야 모두에서 댐의 중요성이 크다. 이뿐만 아니라 기후변화로 인한 변동성의 극대화로 인해 그 중요성이 나날이 커지고 있다. 댐을 운영하기 위해서는 강수량에 따른 댐 유입량의 예측을 하여, 적절한 방류 시기 및 방류량을 결정하는 것이 가장 중요한 요소이다. 기후변화로 인한 변동성의 증대로 홍수와 가뭄과 같은 재해의 빈도와 심도가 커지면서 댐 유입량의 예측이 어려워지고 있다. 댐의 설계나 유지관리를 위해 홍수에 대해서는 많은 연구가 이루어졌던 것에 비해, 갈수기의 경우 물 부족으로 인해 유량이 적어져 댐 유입량에 대한 정확한 산정이 어려워 가뭄 시 댐 유입량에 관한 연구가 홍수 시에 비해 적게 연구된 것이 실정이다. 따라서 가뭄 시 댐 연구를 위해 갈수기의 댐 유입량에 대한 정확한 산정 및 예측의 필요성이 대두되고 있다. 이번 연구에서는 댐 주변의 지하수위와 하천수위의 관계성을 보이고 각각 다른 변량 간의 시간적 종속성을 고려하는 동시에 상호연관된 변량의 시간적 종속성을 동시에 고려한VARX(vector autoregressive-exogenous) 모델을 이용하여 정확한 댐의 유입량을 산정 및 예측하고 그에 대한 검증을 시행하여, 댐 분야에서 가뭄에 대비할 수 있는 근간을 마련하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 추계학술발표대회
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• pp.514-517
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• 2023

본 연구는 인 컨택스트 러닝 (In-Context Learning)을 오디오-언어 작업에 적용하기 위한 멀티모달 (Multi-Modal) 딥러닝 모델을 다룬다. 해당 모델을 통해 학습 단계에서 오디오와 텍스트의 소통 가능한 형태의 표현 (Representation)을 학습하고 여러가지 오디오-텍스트 작업을 수행할 수 있는 멀티모달 딥러닝 모델을 개발하는 것이 본 연구의 목적이다. 모델은 오디오 인코더와 언어 인코더가 연결된 구조를 가지고 있으며, 언어 모델은 6.7B, 30B 의 파라미터 수를 가진 자동회귀 (Autoregressive) 대형 언어 모델 (Large Language Model)을 사용한다 오디오 인코더는 자기지도학습 (Self-Supervised Learning)을 기반으로 사전학습 된 오디오 특징 추출 모델이다. 언어모델이 상대적으로 대용량이기 언어모델의 파라미터를 고정하고 오디오 인코더의 파라미터만 업데이트하는 프로즌 (Frozen) 방법으로 학습한다. 학습을 위한 과제는 음성인식 (Automatic Speech Recognition)과 요약 (Abstractive Summarization) 이다. 학습을 마친 후 질의응답 (Question Answering) 작업으로 테스트를 진행했다. 그 결과, 정답 문장을 생성하기 위해서는 추가적인 학습이 필요한 것으로 보였으나, 음성인식으로 사전학습 한 모델의 경우 정답과 유사한 키워드를 사용하는 문법적으로 올바른 문장을 생성함을 확인했다.