• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.136-151
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• 2016

Flexible large-scale WLANs are now widely deployed in crowded and highly mobile places such as campus, airport, shopping mall and company etc. But network management is hard for large-scale WLANs due to highly uneven interference and throughput among links. So the traffic is difficult to predict accurately. In the paper, through analysis of traffic in two real large-scale WLANs, Granger Causality is found in both scenarios. In combination with information entropy, it shows that the traffic prediction of target AP considering Granger Causality can be more predictable than that utilizing target AP alone, or that of considering irrelevant APs. So We develops new method -Granger Causality and Vector Auto-Regression (GCVAR), which takes APs series sharing Granger Causality based on Vector Auto-regression (VAR) into account, to predict the traffic flow in two real scenarios, thus redundant and noise introduced by multivariate time series could be removed. Experiments show that GCVAR is much more effective compared to that of traditional univariate time series (e.g. ARIMA, WARIMA). In particular, GCVAR consumes two orders of magnitude less than that caused by ARIMA/WARIMA.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.1
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• pp.51-54
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• 2003

The z-transform method is a basic mathematical tool in analyzing and designing digital signal processing systems for discrete input and output signals. There are may cases where the output signal is in the form of a discrete convolution sum of an input function and a designed digital processing algorithm function. It is well known that the z-transform of the convolution sum becomes the product of the two z-transforms of the input function and the digital processing function, whose proofs require the causality of the digital signal processing function in the almost all the available references. However, not all of the convolution sum functions are based on the causality. Many digital signal processing systems such as image processing system may depend not on the time information but on the spatial information, which has nothing to do with causality requirement. Thus, the application of the causality-based z-transform theorem on the convolution sum cannot be used without difficulty in this case. This paper proves the z-transform theorem on the discrete convolution sum without causality requirement, and make it possible for the theorem to be used in analysis and desing for any cases.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.109-114
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• 2019

The purpose of the study to evaluate the contribution of foreign direct investment (FDI) and tourism receipts (TR) to Sri Lanka's gross domestic product (GDP). This study employs time series annual data for the period from 1978 to 2016 and EViews 10 econometrics software was used for the time series data analysis. Unit root test was done on the variables and the method chosen was the Augmented Dicky - Fuller test. Co-integration analysis was used for the long run relationship and the Granger causality test was performed to investigate the causal relationship. Recently a more conducive environment has been established after the three decade long ethnic war came to an end. In this context, the Sri Lankan government has taken positive measures to attract foreign direct investment and boost tourism in the country. This study intends to evaluate the contribution of Sri Lanka, as these two factors are considered to be very effective at increasing the GDP of a country. The empirical study shows that there is a positive and statistically significant relationship between the variable's TR and FDI to the GDP in the long run. Results of Granger causality test implied that the two-way causality promoted the economic growth of Sri Lanka.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.192-200
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• 2019

This paper is analyzed causality using cointegration test and impact response after deriving a causality between direct overseas purchasing and sale and macroeconomic variables. The model used for the empirical analysis is the vector error correlation model. The model is used the macroeconomic variables such as the consumer price index and the GDP, and e-commerce variables such as direct overseas purchasing, direct overseas sales and online shopping amount. According to empirical analysis, the direct overseas purchasing has the causality with the consumer price index, and GDP has the causality with direct overseas purchasing and online. According to the impact response analysis of the VECM, the direct overseas purchasing has a positive effect on the CPI and GDP, but the direct overseas sales has a negative effect on the CPI and GDP. In addition, both direct overseas purchasing and sales have a negative effect on online shopping, but it has been shown that the direct overseas purchasing has a bigger negative effect on online shopping.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.3
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• pp.297-311
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• 2010

The purpose of this study is to analyze the causality among GRDP, patent, investment of R &D, and researcher among 16 Metropolitan cities and provinces in Korea. Using the annual data ranged from 1998 to 2008, the causality test for time-series data such as unit roots test and Granger causality test were performed. We estimate the Panel-Var of the four variables to find out the various Granger causal relations for two groups which are classified by the patent productivity. The panel data causality results reveal that there are bidirectional causality relations among four variables for the more patent-productivity group. The patent has bi-directional effects on GRDP and R&D. The patent cause GRDP and vice versa, patent cause R&D and vice versa. Patent not only has strong direct impact on GRDP and R&D but also has affected by the increase of GRDP and R&D through the interactive feedback mechanism. However, the causality patterns are somewhat different between the more patent-productive region and the less patent-productive region. There exists one directional causality between the R&D and GRDP for the less patent-productivity group. Such result may imply that the type of regional innovation policy should be differentiated between two groups. Regional economic policy efforts should be placed on increasing the knowledge productivity and on strengthening the regional competitiveness through the regional innovative infrastructure.

• East Asian Economic Review
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• v.19 no.1
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• pp.39-70
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• 2015

This paper examines the effects of foreign direct investment (FDI) on South Asian economies' output growth, utilizing recent panel cointegration testing and estimation techniques. Annual panel data on eight SAARC (South Asian Association for Regional Cooperation) member countries' macroeconomic variables over the period 1960- 2013 are employed in empirical analysis. Using various heterogeneous panel cointegration and panel causality tests, a bi-directional relationship between FDI and growth is found. We find evidence for both FDI-led growth and growth-induced FDI hypotheses for the South Asian economies over the sample period. Individual member countries exhibit heterogeneity in terms of the direction or existence of causality subject to their idiosyncratic economic conditions. Among various regressors, FDI, financial development, human capital, and government consumption show the most significant positive effects on output growth. As determinants of FDI, GDP, financial development, human capital, and government consumption are found significant in the region. The bi-directional causality between FDI and growth is found robust to the inclusion of other control variables and using different estimation techniques.

• 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.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.837-848
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• 2021

Evaluating or predicting the effectiveness of economic policies is an important issue, but it is difficult to find an economic variable which causes a significant result because there are numerous variables that cannot be taken into account. A randomized controlled experiment is the best way to investigate causality, but it is not realistically possible to control through randomization and intervention in time series data such as macroeconomic data. Although some analysis methods have been proposed to find causality, the methods such as Granger causality method and Chow test are insufficient to explain causality. Recently, Pfister et al. (2019) proposed invariant causal prediction methods which can be applicable in time series data. In this paper, we introduce the method of Pfister et al. (2019) and use the method to find macroeconomic variables invariantly affecting the won-dollar exchange rate.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.5
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• pp.652-662
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• 2000

Most of established study about consumer behavior was directly connected abstract value with concrete purchase behavior, nevertheless several recognizable process is intervened between abstract concept and concept behavior. Of course researchers suggest hierarchical causality through means-end chain model. However empirical study is insufficient. And it's not certain whether the consumer's personal value affects actual evaluation about product attributes. Thus the purpose of this paper was to explore hierarchical causality of personal value, benefits sought and clothing product attributes and to suggest an alternative approach method. For the empircial study the data sets were collected through 150 female consumers living in Pusan and SAS and LISREL VIII were used for statistical analysis. As the result, hierarchical causality suggested by means-end chain model was positively substantiated. That is, benefits sought is differentiated according to personal value, and actual product attributes are indirectly influenced by personal value through benefits sought. Benefits sought are found to be key mediating variables.

• Journal of Korea Port Economic Association
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• v.23 no.4
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• pp.216-227
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• 2007

The aim of this paper is to find out the nature of causality between the two ocean freights employing the Granger method. That is because the Baltic freights tend to move very closely and seem to be behave like one time series. The Granger causality test, however, is very sensitive to the number of lags used in the analysis. This means that one has to be very careful in implementing the Granger causality test. This paper, hence, uses more rather than the lags which the Akaike Information Criterion and the Schwarz Information Criterion suggest. This study shows that BPI does not "Granger-cause" BCI and BSI, but BCI and BSI Granger-cause BPI. I also discover that BHSI does not "Granger-cause" BPI and BSI, but BPI and BSI Granger-cause BHSI. I, hence, model and estimate the ocean freight function and show that the Baltic ocean freight market is inefficient and the biased estimator of the other freight.