• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.275-279
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• 2003

We obtain the asymptotic distributions of tests statistics for various types of seasonal cointegration based on GRR estimators of Ahn and Cho (2003). These tests are useful in testing for restrictions about cointegrating vectors after Chi-square tests for CCI and common PCIV in Ahn and Cho (2003) or tests for the known CCI and the known PCIVs have been performed.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.13-15
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• 2005

In this paper, we propose an extension of the maximum likelihood seasonal cointegration procedure developed by Johansen and Schaumburg (1999) for daily time series. We presented the finite sample distribution of the associated rank test statistics for daily data.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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• pp.587-592
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• 2016

It is a long-standing issue to correctly determine the number of long-run relationships among time series processes. We revisit nonparametric test for cointegration rank and propose bootstrap refinements. Consistent with model-free nature of the tests, we make use of Cholesky factor bootstrap methods, which require weak conditions for data generating processes. Simulation studies show that the original Breitung's test have difficulty in obtaining the correct size due to dependence in cointegrated errors. Our proposed bootstrapped tests considerably mitigate size distortions and represent a complementary approach to other bootstrap refinements, including sieve methods.

• The Journal of Fisheries Business Administration
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• v.29 no.2
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• pp.97-110
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• 1998

This paper tries to estimate Korea's import demand function for fisheries using cointegration analysis. The estimation function consists of one dependent variable-import quantity of fisheries(FTIW) and two independent variables-relative price(RP) between importable and domestic products and real income(GDP). As it has been empirically found out that almost all of time series of macro-variables such as GDP, price index are nonstationary, existing studies which ignore this fact need to be reexamined. Conventional econometric method can not analyze nonstationary time series in level. To perform the analysis, time series should be differenciated until stationarity is guaranteed. Unfortunately, the difference method removes the long run element of data, and so leads to difficulties of interpretation. But according to new developed econometric theory, cointegration approach could solve these problems. Therefore this paper proceeds the estimation on the basis of cointegration analysis, because the quartly variables from 1988 to 1997 used in the model is found out to be nonstationary. The estimation results show that all of the variables are statistically significant. Therefore Korea's import demand for fisheries has been strongly affected by the variation of real income and the relative price.

• Ocean and Polar Research
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• v.36 no.1
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• pp.71-76
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• 2014

This study aims to analyze the market interactions among the main farmed fish species in Korea, using both multivariate and bivariate cointegration analysis. For the analysis of market interactions among farmed fish species, major four farmed fish species, olive flounder (Paralichthys olivaceus), black rockfish (Sebastes schlegeli), red seabream (Pagrus major), and grey mullet (Mugil cephalus) were selected as the analytical target species. And their real price data by month from January 2000 to December 2011 were used in the analysis. The results of the multivariate cointegration test for four farmed fish showed that there would be no long-term equilibrium relationships among farmed fish species, and consequently they do not share the same market. The results of bivariate cointegration test indicated that there was little evidence to suggest that all farmed fish species were cointegrated each other. However, it was only analyzed that olive flounder and grey mullet might have a long run equilibrium relationship.

• 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.

• 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.

• East Asian Economic Review
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• v.16 no.1
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• pp.97-115
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• 2012

This paper investigates the relationship between financial markets and output growth for a panel of 27 Asian countries over 1960-2009. It utilizes the recently-developed panel cointegration techniques to test and estimate the long-run equilibrium relationship between real GDP and financial development proxies. Real GDP and financial development variables are found to have unit roots and to be cointegrated, based on various panel unit root tests and panel cointegration tests. We find that there is a statistically significant positive bi-directional cointegrating relationship between financial development and output growth by three distinct methods of panel cointegration estimation. Empirical findings suggest that financial market development promotes output growth and in turn output growth stimulates further financial development.

• The Journal of Asian Finance, Economics and Business
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• v.1 no.1
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• pp.15-21
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• 2014

This study investigates extensively the integration of various segments of financial markets (i.e. money market, lending and deposit market, exchange rate market, and capital market) both domestically and internationally. Cointegration approach is employed in the study to find out long term relationship among the variables. Data are on a monthly interval for the period spreads over 2001 to 2010. The results show no evidence of cointegration between money market and exchange rate market and between capital market and exchange rate market of Pakistan. On the other hand, international financial markets integration is also investigated and the findings revealed that domestic money market rates of Pakistan and USA are not cointegrated. Whereas, an evidence of cointegration between capital markets of Pakistan and USA is found in this study.

• The Journal of Fisheries Business Administration
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• v.44 no.1
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• pp.71-79
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• 2013

This study is aimed to estimate market integration of wild caught fish species on the Korean market, using both multivariate and bivariate cointegration analysis. For the analysis of market integration between wild caught fish species, major four fish species those are most popular fish in the market and caught by the large purse seine fishery-chub mackerel, jack mackerel, hairtail and spanish mackerel-were selected as analytical target fish species. And their real monthly price data from January 2000 to December 2011 were used in the analysis. The results of the multivariate cointegration test for four wild caught fish species showed that there would be long-term equilibrium relationships among prices of four wild caught fish species, and consequently, the markets for wild caught fish species were estimated to be integrated. The results of exclusion test and bivariate cointegration test also supported that there would be a clear evidence to suggest that all target wild caught fish species were cointegrated each other.