• The Journal of Industrial Distribution & Business
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• v.9 no.7
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• pp.33-42
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• 2018

Purpose - This paper aims to verify whether the Fisher effect and the international Fisher effect are significant between China and South Korea in the long and short run, respectively. Research design, data, and methodology - The annual and monthly data, respectively, are employed to conduct an empirical estimation under the fully modified ordinary least squares(FMOLS). The nominal interest rate is treated as an independent variable. The inflation rate is treated as a dependent variable. Results - The results exhibit whenever in the long or short run, the Fisher effect exists in China and South Korea. However, the Fisher effect in South Korea is more significant than that of in China. Meanwhile, an empirical analysis is also preformed to investigate the long-run and the short-run international Fisher effect between China and South Korea. The deviation from the equilibrium relationship is that the commodity market and the Financial market have started to integrate in China. But China's integrated level proved to be relatively lower. Conclusions - To exploit that the Fisher effect and the international Fisher effect hold between China and South Korea can help both countries deal with the sufferings from integration of the commodity market and the financial market.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.95-104
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• 2019

Along with the economic globalization and network generalization, this provides a good opportunity to the development of cross-border e-commerce trade. Based on this background, this paper sets ASEAN countries as an example to exploit the determinants of cross-border e-commerce trade including the export and the import, respectively. The panel data from the year of 1998 to 2016 will be employed to estimate the relationship between cross-border e-commerce trade and relevant variables under the dynamic ordinary least squares and the error correction model. The findings of this paper show that there is a long-run relationship between cross-border e-commerce trade and relevant variables. Generally speaking, the GDP(+) and real exchange rate(-export & +import) have an effect on cross-border e-commerce trade. However, the population (+) and the terms of trade (-) only have an effect on cross-border e-commerce import. The empirical evidences show that the GDP and the real exchange rate always affect the development of cross-border e-commerce trade. Therefore, all ASEAN countries should try their best to develop the economic growth and focus on the exchange rate regime so as to meet the need of cross-border e-commerce trade development.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.41-46
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• 2021

The purpose of this study is to investigate the relationship between unemployment and shadow economy for 7 selected ASEAN countries using panel data from 2000-2017. This study uses a sample of 7 ASEAN countries including Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam covering the 2000-2017 period. The stationarity of the variables is determined by Pesaran panel unit-root tests. The Westerlund panel co-integration technique is used to examine the long-run relationship among the variables. In addition, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) methods are also employed. The DOLS and FMOLS results indicate that unemployment acts as an important driver for the increase in the shadow economy. In addition, the study results also reveal that GDP per capita has a negative impact on the shadow economy. Moreover, government expenditure, bank credit, and inflation are positively related to the shadow economy. The empirical results indicate that the size of the shadow economy is boosted by unemployment in the selected ASEAN economies. In addition, it is also evident that an increase of GDP per capita in the sample countries results in a lower shadow economy. Besides, government expenditure, bank credit, and inflation play a crucial role in the shadow economy.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1664-1673
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• 2022

Achieving sustainable development requires an increasing share of green technologies. World energy demand is expected to rise significantly especially in developing economies. The increasing energy demands will be entertained with conventional energy sources at the cost of higher emissions unless eco-friendly technologies are used. This study examines the asymmetric effects of nuclear energy on carbon emissions for Pakistan from 1974 to 2019. Augmented Dickey-Fuller (ADF) and Phillips Perron (PP) unit root tests suggest that variables are integrated of order one and bound test of Autoregressive Distributed Lag (ARDL) and nonlinear ARDL confirm a long-run relationship among selected variables. The ARDL, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS) results show that the coefficient of nuclear energy has a negative and significant impact on emissions in both short and long run. Further, the NARDL finding shows that there exists an asymmetric long-run association between nuclear energy and CO₂ emissions. The vector error correction method (VECM) results indicate that there exists a bidirectional causal relationship between nuclear energy and carbon emissions in both the short and long run. Additionally, the impact of nuclear energy on ecological footprint has been examined and our findings remain robust.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.393-393
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• 2021

도시화는 도시 호우 유출 발생으로 인한 수질 악화를 초래했고 문제를 해결하기 위해 본 연구에서는 보다 정확한 설계를 위해 그린인프라(Green Infrastructure, GI)의 구조적 특성과 수문학적인 특성을 이용해 어떤 인자들이 설계에 필요한지 상관관계를 통해 분석하였다. GI의 종류 중 저류지와 저류연못의 총부유사량(Total Suspended Solids, TSS)와 총인 (Total Phosphorous, TP)의 유입수, 유출수, 비점오염원 농도, 수문학적인 특성 그리고 GI의 구조적 특성을 Ordinary Least Squares regression(OLS)과 Multi Linear Regression(MLR) 방법을 적용하였다. GI의 구조적인 특성은 한 BMP마다 달라지지 않으나 호우사상의 데이터 개수에 의한 편향이 있을 수 있다. 이런 문제를 해결하기 위해 일정한 범위를 가지고 무작위로 데이터를 추출하는 방법과 이상치를 제외하는 방법을 사용하여 모델에 적용하였다. 이러한 OLS와 MLR 모델들의 정확도를 PBIAS(Percent Bias), NSE(Nash-Sutcliffe efficiency), RSR(RMSE-observations standard deviation ratio)을 통해 분석할 수 있다. 연구 결과 유입수의 비점오염원의 농도뿐만 아니라 수문학적 특성과 GI의 구조적 특성이 함께 들어갈 시 더 좋은 상관관계를 가지고 있음을 알 수 있다. 저류지가 저류연못보다 모델의 성능평가 면에서 좋은 값을 가지고 있지만 특성별 상관관계는 저류연못이 더 뚜렷한 결과를 보여준다.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.111-117
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• 1997

The ordinary least squares estimator $S^2$ for the variance of the disturbances is considered in the linear regression model with sutocorrelated disturbances. It is proved that the OLS-estimator of disturbance variance is asymptotically unbiased and weakly consistent, when the distrubances are generated by an MA(q) process. In particular, the asymptotic unbiasedness and consistency of $S^2$ is satisfied without any restriction on the regressor matrix.

• Journal of the Korean Statistical Society
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• v.17 no.1
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• pp.9-23
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• 1988

The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.1-17
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• 2008

The ordinary least squares regression method of Haseman and Elston(1972) is most widely used in genetic linkage studies for continuous traits of sib pairs. Kruglyak and Lander(1995) suggested a statistic which appears to be a nonparametric counterpart to the Haseman and Elston(1972)'s regression method, but in fact these two methods are quite different. In this paper the relationships between these two methods are described and will be compared by simulation studies. One of the characteristics of the sib-pair linkage study is that the explanatory variable has only three different values and thus dependent variable is heavily replicated in each value of the explanatory variable. We propose a weighted least squares regression method which is more appropriate to this situation and the efficiency of the weighted regression in genetic linkage study was explored with normal and non-normal simulated continuous traits data. Simulation studies demonstrated that the weighted regression is more powerful than other tests.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.31-39
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• 2001

For estimating parameters of possibly nonlinear and/or non-stationary seasonal autoregressive(AR) processes, we introduce a new instrumental variable method which use the direction vector of the regressors in the same period as an instrument. On the basis of the new estimator, we propose new seasonal random walk tests whose limiting null distributions are standard normal regardless of the period of seasonality and types of mean adjustments. Monte-Carlo simulation shows that he powers of he proposed tests are better than those of the tests based on ordinary least squares estimator(OLSE).

• Journal of the Korean Statistical Society
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• v.33 no.2
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• pp.149-157
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• 2004

The stationarity is one of the most important properties of a time series. We propose robust sign tests for seasonal autoregressive processes to determine whether or not a time series is stationary. The proposed tests are robust to the outliers and the heteroscedastic errors, and they have an exact binomial null distribution regardless of the period of seasonality and types of median adjustments. A Monte-Carlo simulation shows that the sign test is locally more powerful than the tests based on ordinary least squares estimator (OLSE) for heavy-tailed and/or heteroscedastic error distributions.