• 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.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.401-412
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• 2011

This study uses a vector error correction model to analyze the daily time series data of the spot price of EUA (European Union Allowance). As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid Phase 1 period (2005-2007) where the EUA prices were distorted. Unit-root and cointegration test results reveal that all variables have a unit root and cointegration vectors exist, so a vector error correction model is adopted instead of a vector autoregressive model.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1449-1466
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• 2014

In this paper, we consider a hedge portfolio based on futures of underlying asset. A classical way to estimate a hedge ratio for a hedge portfolio of a spot and futures is a regression analysis. However, a regression analysis is not capable of reflecting long-run equilibrium between a spot and futures and volatility clustering in the conditional variance of financial time series. In order to overcome such defects, we analyzed KOSPI200 index and futures using VECM-CC-GARCH model and computed a hedge ratio from the estimated conditional covariance-variance matrix. In real data analysis, we compared a regression and VECM-CC-GARCH models in terms of hedge effectiveness based on variance, value at risk and expected shortfall of log-returns of hedge portfolio. The empirical results show that the multivariate GARCH models significantly outperform a regression analysis and improve hedging effectiveness in the period of high volatility.

• Proceedings of the Safety Management and Science Conference
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• 2002.11a
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• pp.341-364
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• 2002

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.61-73
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• 2016

We consider the wild bootstrap Ljung-Box (LB) test for autocorrelation in residuals of fitted multivariate time series models. The asymptotic chi-square distribution under the IID assumption is traditionally used for the LB test; however, size distortion tends to occur in the usage of the LB test, due to the conditional heteroskedasticity of financial time series. In order to overcome such defects, we propose the wild bootstrap LB test for autocorrelation in residuals of fitted vector autoregressive and error correction models. The simulation study and real data analysis are conducted for finite sample performance.

• International Area Studies Review
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• v.16 no.1
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• pp.3-27
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• 2012

This paper adopts recently developed panel unit root test that is cross-sectionally robust. Cointegration test is also used to find whether regional house prices are in line with gross regional domestic production (GRDP) in the long run in Korea during 1989-2009. Based on the panel VECM and the panel ARDL models, we examine causal relationships among the variables and estimate the long-run elasticity. We find evidence of cointegration and bidirectional causal relationships between regional house prices and GRDP. The results of long-run estimates, using both fixed effect and ARDL models, show that house prices positively and significantly influence on the GRDP and vice versa. Together with these results, the findings of ARDL-ECM imply that there exists a long-run equilibrium relationship between house prices and regional economic variables even if there is a possibility of short-run deviation from its long-run path.

• 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.

• Korean Journal of Labor Studies
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• v.14 no.2
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• pp.1-21
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• 2008

1989~91년과 2004~7년에 이루어진 법정근로시간 단축이 실근로시간과 고용, 실질임금에 미친 영향을 분석했다. 통상적인 회귀분석과 벡터오차수정 모형을 병행해서 추정한 결과 확인된 사실은 다음과 같다. 첫째, 법정근로시간 단축으로 실근로시간과 월근로일수가 감소했다. 법정근로시간을 10% 단축할 때 실근로시간은 8.0% 감소하고 월근로일수는 3.0% 감소했다. 둘째, 법정근로시간 단축에 따른 실근로시간 단축은 고용증가로 이어졌다. 근로시간을 10% 단축할 때 단기적으로는 고용증가 폭이 미미하지만, 장기적으로 취업자는 8.5%, 노동자는 13.1% 증가했다. 셋째, 실근로시간 단축으로 시간당임금은 증가했다. 즉 실근로시간이 10% 단축될 때 시간당임금은 장기적으로 13.3% 증가했다. 그러나 월임금총액은 유의미한 영향을 받지 않았다.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.799-826
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• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• 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.