• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1573-1583
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• 2016

It is necessary to check mutual correlations between related variables because housing prices are influenced by a lot of variables of the economy both internally and externally. In this paper, employing the Granger causality test, we have validated interrelated relationship between the variables. In addition, there is cointegration associations in the results of the cointegration test between the variables. Therefore, an analysis using a vector error correction model including an error correction term has been attempted. As a result of the empirical comparative analysis of the forecasting performance with ARIMA and VAR models, it is confirmed that the forecasting performance by vector error correction model is superior to those of the former two models.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.531-540
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• 2007

In this research, we proposed a two-phase hybrid stock price forecasting model with cointegration tests and artificial neural networks. Using not only the related stocks to the target stock but also the past information as input features in neural networks, the new model showed an improved performance in forecasting than that of the usual neural networks. Firstly in order to extract stocks which have long run relationships with the target stock, we made use of Johansen's cointegration test. In stock market, some stocks are apt to vary similarly and these phenomenon can be very informative to forecast the target stock. Johansen's cointegration test provides whether variables are related and whether the relationship is statistically significant. Secondly, we learned the model which includes lagged variables of the target and related stocks in addition to other characteristics of them. Although former research usually did not incorporate those variables, it is well known that most economic time series data are depend on its past value. Also, it is common in econometric literatures to consider lagged values as dependent variables. We implemented a price direction forecasting system for KOSPI index to examine the performance of the proposed model. As the result, our model had 11.29% higher forecasting accuracy on average than the model learned without cointegration test and also showed 10.59% higher on average than the model which randomly selected stocks to make the size of the feature set same as that of the proposed model.

• International Area Studies Review
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• v.14 no.3
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• pp.363-387
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• 2010

This papers studies the causalities and effects on the relationship between inbound tourism(TOU) and the production amount of service industry in China, using the unit root test, the Granger causality test, the cointegration test, and VECM. we take their natural logarithm and define them as TOU and SGDP: these represent the distributed variable based the lagged values of the number of international tourists by continent and real production amount in service industry of China, respectively. The results of empirical study of this papers are as follows: Firstly, in the unit root test, we found that each time series was unstable one that has unit root. This result made me use 1st differenced data for this empirical study. Secondly, in the Granger casuality test, the study results show that there is unilateral casuality relation between DLSGDP-$DLTOU_i$ except DLSGDP-DLTOUL model for the same time, while no casuality relation between DLTOU-DLSGDP for all models of China. Thirdly, there is cointegration relation between all models for the period of 1980-2008.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.207-218
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• 2011

This paper investigates the determinants of trade on Southeast Asia via Korean ports using monthly data. I employ Johansen cointegration methodology since the model must be stationary to avoid the spurious results. Johansen(1988) and Johansen and Juselius(1990) propose two statistics for testing the number of cointegrating vectors: the trace and maximum eigenvalue statistics. The null hypothesis that there is no cointegrating vector should be rejected at the 5% level. The results indicate that there is a long-run relationship between trade and variables. This also suggests that these variables have a meaningful equilibrium relationship between trade and variables would not move too far away from each other, displaying a comovement phenomenon for the export and import. Apparently, the error correction term reflects market information in a state of disequilibrium that is bound to be corrected when moving toward the long-run level.

• The Korean Journal of Financial Management
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• v.10 no.2
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• pp.137-159
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• 1993

본 연구에서는 우리나라의 금융자산, 특히 회사채와 주식이 인플레이션과 관련하여 어떠한 행태를 보이는가를 실증적으로 살펴본다. 1976년부터 1992년까지의 기간중 채권 및 주식수익률에 피서가설이 성립하는가의 여부, 주식수익률과 기대인플레이션과 관련된 Fama의 허구성가설 및 Geske & Roll의 역인과성가설 등을 공적분관계검정 및 VAR모형의 예측오차 분산분해등을 통하여 포괄적으로 결정한다. 이를 위하여 본 연구는 다음과 같은 순서로 진행하였다. 첫째, 단순정태회귀분석을 통하여 우리나라 금융시장에서 주식이나 채권이 기대된 인플레이션이나 예상치 못했던 인플레이션에 대해 얼마나 인플레이션방어수단으로 유효한지를 살펴보았다. 우선, 회사채수익률의 경우 피서가설의 성립을 기각하기 어려웠다. 반면, 주식의 경우에는 피서가설이 성립될 수 없음은 물론이고, 대부분의 선진국가들처럼 기대인플레이션에 주식수익률이 만대방향으로 반응하는 것으로 나타났다. 주식수익률을 설명하는 변수에 예상되는 산업생산증가나 통화량증가를 나타내는 변수들을 추가하여도 주식수익률과 기대인플레이션간의 부의 관계는 여전히 유의적인 것으로 남아있었다. 따라서 파마의 주식수익률과 기대인플레이션간의 허위관계가설은 우리나라 주식시장에서는 적용되지 않는 것으로 나타났다. 둘째, 단순정태분석에서 활용된 여러 회귀식들이 가성적회귀관계(假性的回歸關係)를 나타내는 경우를 확인하기 위하여 공적분관계가 형성되는지를 검정하였다. 그 결과, 회사채수익률과 인플레이션은 공적분관계가설이 기각되지 않았으나, 주식수익률과 기대인플레이션간에는 공적분관계가 나타나지 않았다. 공적분관계에 입각하여 오차수정모형을 추정한 결과, 회사채수익률의 변화는 단기적인 인플레이션의 동태를 예측하는데 있어서 도움을 주지만, 기대인플레이션 및 예상산업생산증가률의 변화는 주식실질수익률의 단기적 동해예측에 개별적으로는 도움이 되지 못하였다. 마지막으로 여러 변수들의 관계를 사전적으로 설정하지 않고 VAR 모형의 오차분해를 통하여 인과관제를 분석한 결과, 주식수익률과 기대인플레이션이 허구적(虛構的)인 관계가 아님을 시사하고 있다. 그러나, 주식수익률변동은 예상산업생산증가에 의하여 어느정도 설명이 가능하고 대부분의 경제변수에 대하여는 외생적인 성격을 강하게 보여주고 있어서, 기대인플레이션과의 인과관계에 있어서도 선행적인 위치를 지지하고 있다.

• International Area Studies Review
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• v.20 no.3
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• pp.3-22
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• 2016

This paper uses Dynamic OLS(DOLS) approach to estimate the long-run energy demand functions. The results are compared with those of standard cointegration approach. Cointegration tests verify that there is a cointegration among energy consumption, real GDP, and energy price in China. Johansen approach and DOLS approach are more appropriate to estimate for the long-run energy demand function than Engle-Granger Cointegration approach. DOLS provided significant negative sign of price while Engle-Granger did not. Based on the DOLS results, the elasticities of real GDP and energy price on energy consumption are 0.83 and -0.45 respectively, and their statistical significances are high.

• International Commerce and Information Review
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• v.14 no.3
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• pp.307-322
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• 2012

The purpose of this paper is to examine determinants of export to the East Asia region, using panel unit root, panel cointegration framework, panel VECM (vector error correction model), panel FMOLS (fully modified OLS). Different panel unit root tests confirm that the data series are integrated processes with unit roots. When applying cointegration tests to long-run effect for aggregate panel data, a primary concern is to construct the estimators in a way that does not constrain the transitional dynamics to be similar among different countries of the panel. The regression equations are estimated by various panel cointegration estimators. The panel data causality results reveal that exchange rates has unidirectional effects on export and GDP, and there exists bidirectional causality between export and GDP. Also, the results from the panel FMOLS tests overwhelmingly reject the null hypothesis of zero coefficient. The panel cointegrating vectors show that the export has positive relationship with the GDP and ODI (overseas direct investment).

• International Commerce and Information Review
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• v.13 no.3
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• pp.77-95
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• 2011

This paper investigates the relationship between export and economic variables such as trade insurance, world economy activity, relative price, unemployment rate, exchange rate volatility, using monthly data. I employ Johansen cointegration methodology since the model must be stationary to avoid the spurious results. The results indicate that there is a long-run relationship between export and variables. Also, the empirical analysis of cointegrating vector using the CCR, DOLS, FMOLS reveals that the increases of trade insurance has positive relations and the increases of exchange rate volatility have negative relations with export. Especially, DOLS based on Monte Carlo simulations, of this estimator being superior in small samples compared to a number of alternative estimators, as well as being able not only to accommodate higher orders of integration but also to account for possible simultaneity within regressors of a potential system. This paper also applies impulse-response functions to get the additional information regarding the responses of the export to the shocks of the variables. The result indicates that export positively to trade insurance and then decay fast compare with exchange rate volatility. Consequently, trade insurance plays the role of trade policy for export promotion in Korea. Whereas, increase of exchange risk result in reduction of export. Therefore, the support of trade insurance should be expanded and the stabilization of the foreign exchange market must be done for the export promotion.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.7-15
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• 2005

The objective of this study is to estimate highway trip demand functions in Korea. In order to estimate them, I propose various socio-economic variables that affect the highway trip demand functions. I use the unit root test for each variable and the cointegration test to and the relationships among variables. Finally, I use the vector error correction model, to get the highway trip demand functions. The implication which I derive from the estimation is that real GDP and highway tolls have positive and negative effects, respectively. on the highway trip demand.

• Environmental and Resource Economics Review
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• v.24 no.4
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• pp.709-725
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• 2015

This study is to analyse the relationship between the price and the supply in the farming Olive Flounder's production area market. The data used in this study correspond to daily price and supply quantity covering time period from January 1, 2007 to June 30. 2013. The analysis methods of cointegration and vector error correction model are employed. The empirical results of this study are summarized as follows: First, the price and the supply follow random walks and they are integrated of order 1. Second, the price and the supply are cointegrated. Third, vector error correction model suggests that the relationship between the price change ration and the supply quantity change ratio has negative and feedback effect exists in the long-run, but the disequilibrium between the price and the supply is corrected by the supply quantity. Finally, vector error correction model suggests that the supply quantity leads the price in the short-run. This indicates that the decrease(increase) of the supply quantity results in the increase(decrease) of the price.