• 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.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.615-624
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• 2015

We consider the estimation of seasonal cointegration in the presence of conditional heteroskedasticity (CH) using a feasible generalized least squares method. We capture cointegrating relationships and time-varying volatility for long-run and short-run dynamics in the same model. This procedure can be easily implemented using common methods such as ordinary least squares and generalized least squares. The maximum likelihood (ML) estimation method is computationally difficult and may not be feasible for larger models. The simulation results indicate that the proposed method is superior to the ML method when CH exists. In order to illustrate the proposed method, an empirical example is presented to model a seasonally cointegrated times series under CH.

• New & Renewable Energy
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• v.16 no.4
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• pp.9-22
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• 2020

This study analyzed the short- and long-term effects of nuclear and renewable energy generation on CO2 emissions in Korea, Japan, and Germany from 1987 to 2016 by using the unit root test, Johansen cointegration test, and ARDL model. The unit root test was performed, and the Johansen cointegration test showed cointegration relationships among variables. In the long run, in Germany, the generation of both nuclear and renewable energy was found to affect CO2 emission reduction, while South Korea's renewable energy generation, including hydropower, increased the emissions. Japan only showed significance in fossil fuels. In the short run, in the three countries, the generation of nuclear and renewable energy, excluding hydropower, affected CO2 emission. However, in Korea and Germany, nuclear and renewable energy generation, respectively, affected CO2 emission reduction. Although the rest are significant, the results showed that they increased CO2 emissions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.23-36
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• 2021

The study explores the nexus between foreign direct investment (FDI), financial innovation, and exchange rate volatility in selected South Asian countries for 1980 to 2017. The study applies the unit root test, Autoregressive Distributed Lagged, nonlinear ARDL, and causality test following Toda-Yamamoto. Unit root tests ascertain that variables are integrated in a mixed order; few variables are stationary at a level and few after the first difference. Empirical model estimation with ARDL, Long-run cointegration revealed with the tests of FPSS, WPSS, and tBDM by rejecting the null hypothesis of "no cointegration." This finding suggests that, in the long-run financial innovation, FDI inflows, and exchange rate volatility move together. Moreover, study findings established adverse effects running from FDI inflows and financial innovation to exchange rate volatility in the long run. These findings suggest that continual FDI inflows and innovativeness in the financial system assist in lessening the volatility in the foreign exchange market. Furthermore, nonlinear ARDL confirms the presence of asymmetric cointegration in the model. The standard Wald test established asymmetric effects running from FDI inflows and financial innovation to exchange rate volatility, both in the long and short run. Directional causality unveils feedback hypothesis holds for explaining causality between FDI, financial innovation, and exchange rate volatility.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.227-237
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• 2011

This paper considers a generalized method of moments(GMM) estimation for seasonal cointegration as the extension of Kleibergen (1999). We propose two iterative methods for the estimation according to whether parameters in the model are simultaneously estimated or not. It is shown that the GMM estimator coincides in form to a maximum likelihood estimator or a feasible two-step estimator. In addition, we derive its asymptotic distribution that takes the same form as that in Ahn and Reinsel (1994).

• 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.

• The Journal of Fisheries Business Administration
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• v.40 no.2
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• pp.105-126
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• 2009

This study applies the cointegration theory to analyse the causality of the prices between imported fisheries and domestic fisheries in distribution channel. We've focused on the prices of import, wholesale and retail about the frozen Alaska pollack, hairtail and croaker which take up high portion and are popular among most of the consumers. In process of analysis, the unit root test was adopted to find the stability of time series data prior to the cointegration test. If the time series data was found as stable one in unit root test, we should analyse the VAR model. If unstable, the cointegratioin test was adopeted to find the long-run equilibrium relationship between the data. When the long-run equilibrium relationship was found among the price of the import, wholesale and retail price, the VECM model was adoped. If not, the differenced VAR model was adopted. The main findings of this study could be summarized as follows ; First, according to the result of the analysis on VAR model, time series data of frozen Alaska pollack was found as stable and has causality relationship and close effect was existing among the import, wholesale and retail price. Second, the data of frozen hairtail was found as an unstable one in unit root test and the result of cointegration test showed the long-run equilibrium relationship at lag 1. From the results of VECM model, we could find that the coefficient of error correction is effective, and the sign is negative(-). It means that the existence of adjustment tendency to long-run equilibrium after a short-run deviation. But the short-run causality of the prices were not found except the price of wholesale. Third, according to the results of differenced VAR model, data from frozen croaker did not have the stability and long-run equilibrium. Moreover, it was found that the import price has a weak causality on the retail price. Because of having difficulties in collecting data, the result of this paper could not explain the relationship among the prices of import, wholesale and retail perfectly. However, it more or less contributed to a long-lasted debate on the direction of causality of price-setting in academic research and provided a useful guide for the policy makers in charge of the price-setting of fisheries products as well.

• Ocean and Polar Research
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• v.32 no.1
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• pp.23-40
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• 2010

This study investigated the effects of imported fisheries products on WTO/DDA tariff negotiations. To calculate the results, the study estimated the demand functions of imported fisheries products by using unit root and cointegration approaches. These approaches allowed us to solve spurious regression problems with macro-economic variables. In addition, this study surmised the effects of change by individually imported fish products from a tariff negotiation model using price elasticities of estimated import demand function. In a process of the analysis for estimating import effects, this study found out that 39 out of 128 imported fish products had positive (+) price elasticities or did not exhibit cointegrations. To cure this problem, this study suggested that the effects of these 39 imported products be estimated with the average variation rate of import volume, rather than by the Ordinary Least Squares approach. In this study, a case-study of tariff formula with coefficient 8 based on a 'Swiss formula' for priority duty rate of 2001 and 2008 was used by to analyze the effect of change in the 128 imported fish products of both years, respectively.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.163-171
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• 2020

The study aims to examine the effects of inward every presence of foreign investment, import, and real exchange rate shocks on export performance in Vietnam. This study employs a time-series sample dataset in the period of 2009 - 2018. All data are collected from the General Statistics Office of Ministry of Planning and Investment in Vietnam, World Development Indicator and Ministry of Finance, State Bank of Vietnam. This study employs the Augmented Dickey-Fuller test and the vector error correction model with the analysis of cointegration. The results demonstrate that a higher value of import significantly accelerates export performance in the short run, but insignificantly generates in the long run. When the volume of registered foreign investment goes up, the export performance will predominantly decrease in the both short run and long run. Historically, countries worldwide are more likely to devaluate their currencies in order to support export performance. According to the study, the exchange rate volatility has an effect on the external trade in the long run but no effect in the short run. Finally, Vietnam's export performance converges on its long-run equilibrium by roughly 6.3% with the speed adjustment via a combination of import, every presence of foreign investment, and real exchange rate fluctuations.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.309-325
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• 2013

Environmental and operational variables are inevitable concerns by researchers and engineers when implementing the damage detection algorithm in practical projects, because the change of structural behavior could be masked by the conditions in a large extent. Thus, reliable damage detection methods should have a virtue of immunity from environmental and operational variables. In this paper, the pair cointegration method was presented as a novel way to remove the effect of environmental variables. At the beginning, the concept and procedure of this approach were introduced, and then the theoretical formulation and numerical simulations were put forward to illustrate the feasibility. The jump exceeding the control limit in the residual indicates the occurrence of damage, while the direction and magnitude imply the most potential damage location. In addition, the simulation results show that the proposed method has strong ability to resist the noise.