• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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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.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.73-80
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• 2007

Cointegration(together with VARMA(vector ARMA)) has been proven to be useful for analyzing multivariate non-stationary data in the field of financial time series. It provides a linear combination (which turns out to be stationary series) of non-stationary component series. This linear combination equation is referred to as long term equilibrium between the component series. We consider two sets of Korean bivariate financial time series and then illustrate cointegration analysis. Specifically estimated VAR(vector AR) and VECM(vector error correction model) are obtained and CV(cointegrating vector) is found for each data sets.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.416-427
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• 2018

As the loan size of real estate PF is huge, its market ripple effect gets bigger when overdue occurs. Accordingly, the management of the delinquency rate and macroeconomic analysis are required. As the preceding research mainly proceeded with microeconomic analysis through the real estate PF data of individual banks to evaluate importance of list or analyzed core factors for delinquency, it lacked research on comprehensive real estate PF size. In order to overcome the limitations of such data, this research studied real estate PF delinquency rate of the entire market and effect relationship by the size. The research utilized the size of real estate PF loans, money supply, interest rate, consumer price index(CPI), and GDP data. Also, it applied the first model of VECM as linear relationship between at least two or more variables, following the result of co-integration test. As a result of Granger-causality test, the real estate PF loans delinquency rate is influenced by their loan size, and as a result of impulse response analysis, the interest rate is shown to be affecting delinquency rate the most. Interest rate could risesomeday and aggravate the delinquency rate of real estate PF. Also, risk exposure could be serious as the loan size increases.Therefore, the management of real estate PF delinquency rate requires continuous monitoring, tracking and observing issued loans from a macro point of view. The plans to prevent delinquency will be necessary.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.1
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• pp.65-72
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• 2017

This study analyzed causal relationship between electricity consumption and economic output (GDP) for Korea from 2001 to 2014 employing the vector error-correction model estimation by manufacturing sector. The results of unit-roots tests show that all sectoral GDP and electricity consumptions were not stationary. And cointegration tests show that processed foods, Wood Pulp Paper, electricity apparatus, Precision Medical sectors had a linear combinations in the long run between electricity consumptions and economic growth. With respect to the direction of causality, manufacturing sector has a uni-directional running from economic output (GDP) to electricity consumption in short term. The results of study show that sectoral causal relation were different each other in short term and long term. These findings imply that electricity demand management policy focusing on efficiency improvement is necessary to minimize negative impacts on economic growth and to adopt suitable structural policies can induce energy conservation.