• International Commerce and Information Review
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• v.12 no.4
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• pp.111-126
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• 2010

This paper provides an empirical investigation of the determinants of current accounts utilizing an exchange rate (ER), terms of trade (NET), industrial activity (IPI), world import volume (WIM), trade share of the China and Japan (CHJP), proportion of service trade (SERV). The period examined is 1991:1 through 2010:2. It is tested under different cases such as whether variables were cointegrated and whether there was an equilibrium relationship. The result showed that the hypothesis of no cointegrated vector could be rejected at the 5 percent level. The estimated error correction model showed that adjustment speed is fast. This paper also applies impulse-response functions to get additional information by considering the responses of the current account to the shocks of economic variables. The results indicate that current account responds negatively to industrial activity and proportion of service trade, and then decays very quickly.

• The Korean Journal of Financial Management
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• v.26 no.1
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• pp.127-163
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• 2009

This paper examines the results of survey that the foreign ownership is cointegrated with capital market conditions in Korea using Vector Error Correction Model (VECM) and how the mechanism of innovations and dynamics among the foreign ownership and capital market proxies in the VECM was described. Specifically, we find that the foreign ownership and capital market proxies follow I (1) process and there are cointegrated relations between the foreign ownership and capital market proxies. Adopting the impulse response function and variance decomposition in the VECM, we suggest, in turn, the default risk premia, liquidity of market and the rate of interest in long term business cycle take on a special function on the KSE and KOSDAQ. Finally, we also offer evidences of which there are differences of the mechanism of dynamics and innovations between on the KSE and on the KOSDAQ.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.411-420
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• 2008

This paper considers a feasible two-step estimator for seasonal cointegration as the extension of $Br{\ddot{u}}ggeman$ and $L{\ddot{u}}tkepohl$ (2005). It is shown that the reducedrank maximum likelihood(ML) estimator for seasonal cointegration can still produce occasional outliers as that for non-seasonal cointegration even though the sizes of them are not extreme as those in non-seasonal cointegration. The ML estimator(MLE) is compared with the two-step estimator in a small Monte Carlo simulation study and we find that the two-step estimator can be an attractive alternative to the MLE, especially, in a small sample.

• Journal of Korea Trade
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• v.23 no.2
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• pp.34-45
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• 2019

Purpose - This study investigates the lead-lag relations between the prices of major commodities imported into Korea and corresponding shipping freight rates. This paper aims to provide implications for cross-market causal relations between related economic segments. Design/Methodology - For economic long-run equilibrium between commodity prices and freights, a Johansen (1988) cointegration test is employed first. Then, Granger (1987) causality tests are performed under the vector error correction model (VECM) framework. Findings - The results indicate that the direction of causality varies by raw materials, which is attributable to different economic mechanisms in the corresponding shipping transportation sectors. In addition, the significance of causality becomes blurred during the post-2008 period. Practical Implication - Corporate managers in commodity trading, steelmaking, power generation, and oil refinery sectors can take advantage of the findings in this study as identifying leading economic indicators can be helpful for decision making in both short- and long-term strategies. Originality/value - This study is the first attempt to analyze the inter-relations between commodity prices and corresponding freight rates focusing on raw material imports of Korea.

• International Area Studies Review
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• v.20 no.1
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• pp.127-146
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• 2016

This paper investigates that the Granger-causality between ODA FDI Trade, and economic growth in Senegal over the last 50 years and ODA, FDI, Trade have a impact on the Senegal's economic growth using the Vector Error Correction Model. The empirical results do confirm a directional causality between the variables considered. It also showed that an increase of ODA in the Senegal has positive effect on GDP growth and FDI, which are important factors of economic growth for poor country like Senegal. Underdeveloped nation has been suffered from insufficient savings or capital for economic growth; therefore, developed nations have to provide enough ODA to supply initial capital formation for growth, so-called, seed money. In a nutshell, ODA as a priming the pump is required and expanded continuously for Africa country's economic growth.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.50-55
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• 2021

This study aims to analyze an influence of industrial accident on industrial productivity. We analyzed relationship among industrial accident, labor force, and industrial productivity using vector error correction model (VECM). The data used in the analysis were the number of industrial accidents, the number of workers, and index of all industry production from January 2008 to June 2017 in Korea. Finally, the industrial accidents have played a role in reducing labor force and industrial productivity.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.89-99
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• 2012

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.3260-3269
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• 2014

The construction industry has strong ties with other industries, and so construction company insolvency also has a strong influence on other industries. Prediction models addressing the insolvency of construction company have been well studied. Although factors contributing to insolvency must precede those of predictions of insolvency, studies on these contributing factors are limited. The purpose of this study is to analyze the influence of changes in the housing market on construction company insolvency by using the Vector Error Correction Model. Construction companies were divided into two groups, and the expected default frequency(EDF), which indicates insolvency of each company was measured through the KMV model. The results verified that 10 largest construction companies were in a better financial condition compared to relatively smaller construction companies. As a result of conducting impulse response analysis, the EDF of large companies was found to be more sensitive to housing market change than that of small- and medium-sized construction companies.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.15-24
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• 2018

Purpose - The adjustment of one country's monetary policy can cause the macroeconomic change of other countries. Due to this, this paper attempts to analyze the impact of China's monetary policy on South Korea's exchange rate. Research design, data, and methodology - Based on the flexible-price monetary model, sets of annual time series from 1980 to 2017 are employed to perform an empirical estimation. The vector error correction model is also used to exploit the short-run relationship between both of them. Of course, the South Korea's real GDP, the China's real GDP, South Korea's interest rate, the South Korea's interest rate and the South Korea's monetary supply are treated as independent variables in this paper. Result - The long-run findings reveal that the China's money supply has a negative effect on South Korea's exchange rate. Respectively, the short-run findings depicts that the China's money supply has negative a effect on South Korea's exchange rate. Of course, other variables selected in this paper also have an effect on South Korea's exchange rate whatever positive or negative. Conclusions - As the empirical evidence shows, the China's monetary policy has a negative effect on South Korea's exchange rate whenever in the long run or in the short run.

• International Journal of Contents
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• v.15 no.4
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• pp.113-119
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• 2019

It has been reported that large amounts of information on agri-foods were delivered to consumers through television and social networks, and the information may influence consumers' behavior. The purpose of this paper was first to analyze relations of social network service and broadcasting program on paprika consumption in the aspect of amounts to purchase and identify potential factors that can promote paprika consumption; second, to develop prediction models of paprika consumption by using structured and unstructured big data. By using data 2010-2017, cross-correlation and time-series prediction algorithms (autoregressive exogenous model and vector error correction model), statistically significant correlations between paprika consumption and television programs/shows and blogs mentioning paprika and diet were identified with lagged times. When paprika and diet related data were added for prediction, these data improved the model predictability. This is the first report to predict paprika consumption by using structured and unstructured data.