• 대한산업공학회지
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• 제36권3호
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• pp.203-211
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• 2010

This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.

• 해운물류연구
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• 제34권4호
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• pp.545-563
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• 2018

본 연구의 목적은 VLCC(Very Large Crude Oil Carrier) 운임에 영향을 미치는 주요 결정요인의 장기적 탄성치를 추정하는 것이다. 이를 위해 본 연구는 영국 해운 전문 기업인 클락슨이 공표하는 연간 VLCC 운임을 종속변수로, 원유(Crude oil) 물동량, VLCC 선복량, 벙커유 가격, Libor 금리를 설명변수로 사용하였다. 본 연구는 벡터오차수정모형(Vector Error Correction Model; VECM)을 사용하여 운임 결정 장기균형함수를 추정하였으며, 추정결과 물동량 1.0% 증가 시 운임 6.4% 증가, 선복량 1.0% 증가 시 운임 1.9% 감소, 벙커유 가격 1.0% 증가 시 운임 0.3% 감소, 금리 1.0% 증가 시 운임은 0.18% 증가하는 것으로 나타났다. 벙커유 가격의 경우 일반적인 직관과 반대되는 마이너스(-) 부호로 계수가 추정되었는데, 이는 설명변수 중 벙커유 가격이나 금리 등의 2차 변수가 운임에 미치는 영향력은 적은 반면 직접적인 수급 변수가 운임을 결정하는 주요 요인이기 때문인 것으로 이해된다. 후속연구에서 컨테이너선, 건화물선 등 다른 선종들을 대상으로 연구를 수행하고 다양한 선종별 운임의 결정요인을 비교 분석하는 것이 필요하다.

• 자원ㆍ환경경제연구
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• 제12권2호
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• pp.327-346
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• 2003

본고는 에너지소비와 경제성장의 관계를 밝히는 데 목적을 둔다. 먼저 에너지 소비, 물가, 실질소득으로 구성된 모형이 안정적임을 확인한 후, 오차수정모형을 이용하여 단기에 있어서 에너지 소비와 소득이 상호 영향을 미쳐 쌍방적 인과관계가 존재함을 보인다. 이와 더불어 예측오차의 분산분해와 충격반응함수를 도입하여 경제성장이 에너지소비를 증가시키나, 에너지소비증가가 경제성장에 미치는 효과는 단기적일 뿐 아니라 물가에 비교적 오랫동안 영향을 미친다는 것을 밝힌다. 이러한 사실은 우리나라의 경우 경제성장으로 에너지 소비가 증가하나, 증가한 에너지 소비가 인플레 등을 통해 경제성장의 장애요인으로 작용할 수 있음을 의미한다.

• The Journal of Asian Finance, Economics and Business
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• 제7권1호
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• pp.37-46
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• 2020

The paper examines the dynamic relationship of domestic credit and stock market liquidity on the economic growth of the Philippines from 1995 to 2018 applying the autoregressive distributed lag (ARDL) bounds testing approach to cointegration, together with Granger causality test based on vector error correction model (VECM). The ARDL model indicated a long-run relationship of domestic credit and stock market liquidity on GDP growth. When the GDP per capita is the dependent variable there is weak cointegration. Also, the Johansen cointegration test confirmed the existence of long-run relationship of domestic credit and stock market liquidity both on GDP growth and GDP per capita. The VECM concludes a long-run causality running from domestic credit and stock market liquidity to GDP growth. At levels, domestic credit has significant short-run causal relationship with GDP growth. As for stock market liquidity at first lag, has significant short-run causal relationship with GDP growth. With regards to VECM for GDP per capita, domestic credit and stock market liquidity indicates no significant dynamic adjustment to a new equilibrium if a disturbance occurs in the whole system. At levels, the results indicated the presence of short-run causality from stock market liquidity and GDP per capita. The CUSUMSQ plot complements the findings of the CUSUM plot that the estimated models for GDP growth and GDP per capita were stable.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.173-183
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• 2022

The objective of this research is to examine the influence of the COVID-19 pandemic on stock markets in a few developing and developed countries. This study uses daily data from January 2020 to May 2021 and obtained from World Health Organization and Thomson Reuters. The secondary data was evaluated through panel econometric methodology that includes different unit root tests, and to analyze the long-run relationship between variables, panel cointegration techniques were applied. The long-run causality among variables was examined through Panel Vector Error Correction Model. The overall findings of this study suggest a long-run association exists between several cases and death with the stock returns of the GCC and other stock markets. Furthermore, the VECM model also identified a long-run causality running from COVID cases and death towards the stock rerun of both sets of stock markets. However, a subsequent Wald test yielded mixed results, indicating no short-run causality between cases and deaths and stock returns in both groups; however, in the case of GCC, several COVID-19 cases are having a causal impact on stock markets, which is notable in light of the fact that the death rate in GCC is significantly lower than in many developed and developing countries.

• 자원ㆍ환경경제연구
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• 제11권3호
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• pp.397-414
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• 2002

This paper presents an empirical analysis of exchange rate volatility, petroleum's import price and industrial production on petroleum imports. The GARCH framework is used to measure the exchange rate volatility. One of the most appealing features of the GARCH model is that it captures the volatility clustering phenomenon. We found one long-run relationship between petroleum imports, import price, industrial production, and exchange rate volatility using Johansen's multivariate cointegration methodology. Since there exists a cointegrating vector, therefore, we employ an error correction model to examine the short-run dynamic linkage, finding that the exchange rate volatility performs a key role in the short-run. This paper also apply impulse-response functions to provide the dynamic responses of energy consumption to the exchange rate volatility. The results show that the response of energy consumption to exchange rate volatility declines at the first month and dies out very quickly.

• 통상정보연구
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• 제10권1호
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• pp.329-347
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• 2008

The purpose of this study is to examine the causal relationship between the exchange rate and economic growth, and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And we apply Granger causality based on an error correction model. The results indicate that uni-dierctional causality between exchange rate and economic growth is detected. Exchange rate impacts on economic growth, but economic growth don't impact on exchange rate. The analysis of impulse reaction function shows that the impulse of exchange rate impacts on Korean economic growth in negative direction. We can infer policy suggestion as follows: The fluctuation of exchange rate much affects economic growth, thus we must make a stable policy of exchange rate to continue economic growth.

• 지역연구
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• 제14권1호
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• pp.143-161
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• 1998

This paper applies dynamic versions of shift share models to a simple regional employment model. It tests for the existence of a long run interregional employment equilibrium and then estimates the impulse response functions for each employment series to determine which shocks are temporary and which are permanent.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• 한국디지털건축인테리어학회논문집
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• 제12권1호
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• pp.61-70
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• 2012

A construction project is very costly and takes a long time to make investment and yield profit. For this reason, financial institutions are cautious about financing construction projects. Meanwhile, a construction company needs financing from financial institutions to cover a large expense of a construction project. Thus, there is likely to be a close correlation between financing conditions and business operation of a construction company. To examine the relationship, variables were identified that are related to insolvency of a construction company and changes in financing conditions. The analysis period is between the second quarter of 2001 and the fourth quarter of 2010. Data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Office, and Construction Economy Research Institute of Korea (CERIK). In terms of methodology, VECM (Vector Error Correction Model) was used to analyze dynamic relationship between changes in financing conditions and insolvency of a construction company based on the identified variables. The hypothesis was that changes in financing conditions would significantly affect business of a construction company, but, the analysis did not find a close relation between the two factors. However, it was shown that poor business of a construction company affects financing conditions adversely.