• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.153-161
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• 1993

시간변동모수 공적분(Time-Varying Parameter Cointegration) 모형에서 시간변동모수가 안정적인 확률과정을 따르는 경우 BI(bi-integrated) 과정을 오차항으로 갖는 고정모수 공적분 모형과 동일하다. 이 때 BI과정은 ARCH 과정과 조건부분산이 동치관계에 있음을 이용하여 소득과 비내구재(서비스) 소비의 시간변동모수 공적분 관계를 추정하였다. 이로부터 합리적기대 항상소득가설을 검증한 결과 고정모수 공적분 모형과 달리 가설을 기각할 수 없는 것으로 나타났다.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.13-21
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• 2011

This paper studies the analysis of multivariate nonstationary time series with seasonality. Three types of multivariate time series models are considered: seasonal cointegration model, nonseasonal cointegration model with seasonal dummies, and vector autoregressive model in seasonal differences that are compared for forecasting performances using Korean macro-economic time series data. The cointegration models produce smaller forecast errors in short horizons; however, when longer forecasting periods are considered the vector autoregressive model appears preferable.

• KDI Journal of Economic Policy
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• v.31 no.2
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• pp.1-13
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• 2009

The monetary model suggests that nominal exchange rates between two countries will be determined by important macroeconomic variables. The existence of a cointegrating relationship among these fundamental variables is the backbone of the monetary model. In a recent paper, Rapach and Wohar (2002, Journal of International Economics) advance the literature by testing for linear cointegration in the monetary model using a century of data to increase power. They find evidence of cointegration in five or six of ten countries. We extend their work to the nonlinear framework by performing threshold cointegration tests that allow for asymmetric adjustments in two regimes. Asymmetric adjustments in exchange rates can occur, for example, if transactions costs are present or if policy makers react asymmetrically to changing fundamentals. Moreover, whereas Rapach and Wohar (2002) found it necessary to exclude the relative output variable in some cases to maintain the validity of their cointegration tests, we can include this variable as a stationary covariate to increase power. Overall, using their same long-span data, we find more support for cointegration in a nonlinear framework.

• The Korean Journal of Financial Management
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• v.18 no.1
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• pp.23-41
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• 2001

본 연구에서는 여러 계량 모형을 이용하여 계산한 헤지 비율의 성과를 비교하였다. 특히 헤지 비율을 추정하기 위하여 분수 공적분 오차 수정 모형을 이용하였다. KOSPI200 현물과 선물 지수를 이용하여 검증한 결과 현물, 선물 지수는 1차 적분된 시계열이며 베이시스는 분수 적분된 시계열이었다. 따라서 현물과 선물 지수는 분수 공적분된 시계열이었다. 최소 분산 헤지 비율을 최적 헤지 비율로 하여 성과를 측정한 결과 다음과 같은 결과를 얻었다. 헤지 성과는 GARCH 항이 있는 모형이 없는 모형에 비해 크게 나타나며 각 모형에서 고려하고 있는 정보 집합의 크기가 큰 순서인 FIEC, EC, VAR, OLS 순으로 헤지 성과는 크게 나타나고 있다. 그러나 OLS 방법에 의한 헤지에 의해서도 수익률 변동의 많은 부분이 사라져, 다른 모형들은 OLS 모형과 비교하여 추가적인 분산 감소 효과는 크지 않았다.

• International Commerce and Information Review
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• v.3 no.1
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• pp.277-294
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• 2001

본 연구는 환율과 금리 및 주가간의 균형관계를 나타내는 분석모형(分析模型)을 구축 제시하고, 그 분석모형을 구성하고 있는 일별(日別) 국내 외 금융지표의 변동간에 장기관계(長期關係)가 성립하는지 즉, 공적분(共積分) 관계(關係)의 성립여부를 분석하며, 이들 금융지표간 균형관계에 대한 안정성(安定性)(stationary) 여부를 검증함으로써 제시한 분석모형의 유효성(有效性) 즉, 장기모형관계(長斯模型關係)에 대한 성립여부를 분석하는 데 중점을 두고 있다. 분석결과는 분석모형의 변수간 장기관계 즉, 공적분 관계가 존재한다 할지라도 다변량 가설검증에 의하여 분석모형이 장기모형관계(長斯模型關係)로부터 유의적(有意的)으로 이탈할 수도 있다는 사실을 확충하고 있다.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.63-79
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• 2013

The fundamental endeavor of this study is to investigate the asymmetric relationship between bunker price and Baltic Dry-bulk Index (hereafter BDI). Previous investigations employ linear form based analysis between oil price and BDI but we develop nonlinear and asymmetric cointegration method, which is properly able to capture the decreasing and increasing periods differently. The empirical results show there is no relationships in linear model (e.g. Engle and Granger's methods). On the contrary, our estimate reveals there is significant long-run relationship with asymmetric framework, which implies the necessity of nonlinear and asymmetric consideration to the bunker price analysis.

• Environmental and Resource Economics Review
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• v.19 no.3
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• pp.485-508
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• 2010

This paper examines the long memory property and investigates cointegration in the dynamics of crude oil markets. For these purposes, we apply the joint ARMA-FIAPARCH model with structural break and the vector error correction model (VECM) to three daily crude oil prices: Brent, Dubai and West Texas Intermediate (WTI). In all crude oil markets, the property of long memory exists in their volatility, and the ARMA-FIAPARCH model adequately captures this long memory property. In addition, the results of the cointegration test and VECM estimation indicate a bi-directional relationship between returns and the conditional variance of crude oil prices. This finding implies that the dynamics of returns affect volatility, and vice versa. These findings can be utilized for improving the understanding of the dynamics of crude oil prices and forecasting market risk for buyers and sellers in crude oil markets.

• KDI Journal of Economic Policy
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• v.35 no.2
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• pp.107-131
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• 2013

In this paper, we test and estimate the stochastic non-fundamental trend in Korean stock market. For this, following Kim (2011), we exploit that the long-run equilibrium stock price may be decomposed into fundamental and stochastic non-fundamental trends (i.e., the sum of dividend innovations and a part that are orthogonal with the dividend innovations) by using the Beveridge-Nelson decomposition and projections. In this VAR construction, there is an error correction mechanism through which stock prices converge to their long-run equilibrium, which also contain the stated stochastic non-fundamental trend as well as fundamental trend. The estimation and test results using yearly data from the Korea (1976-2012) indicated that fluctuations in stock prices during that period can be explained mainly not by the stochastic non-fundamental trend but by the dividend trend. However, during some periods like after Seoul Olympic Games, we may observe the non-fundamental trend affected to the stock price variation.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.75-98
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• 2021

This paper compares three statistical models that examine the relationship between national and provincespecific fertility rates. The three models are two of the regression models and a cointegration model. The regression model is by substituting Gompit transformation for the cumulative fertility rate by the average for ten years, and this model applies the raw data without transformation of the fertility data. A cointegration model can be considered when fitting the unstable time series of fertility rate in probability process. This paper proposes the following when it is intended to derive the relation of non-stationary fertility rate between the national and provinces. The cointegrated relationship between national and regional fertility rates is first derived. Furthermore, if this relationship is not significant, it is proposed to look at the national and regional fertility rate relationships with a regression model approach using raw data without transformation. Also, the regression model method of substituting Gompit transformation data resulted in an overestimation of fertility rates compared to other methods. Finally, Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon and Gyeonggi province are expected to show a total fertility rate of 1.0 or less from 2025 to 2030, so an urgent and efficient policy to raise this level is needed.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.405-421
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• 2019

Predicting how much energy to use is an important issue in society. However, it is more difficult to capture the usage characteristics of residential buildings than other buildings. This paper provides time series analysis methods for electricity consumption in a residential building. Temperature is closely related to electricity demand. An error correction model, which is a method of adjusting the error with time, is applied when a cointegration relation is established between variables. Therefore, we analyze data via ECMs with consideration of the temperature effect.