• Korean Journal of Clinical Pharmacy
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• v.28 no.2
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• pp.154-157
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• 2018

Levosulpiride is one of the most frequently prescribed medicines in Korea. An adverse drug reaction (ADR) after taking levosulpiride was reported at a community pharmacy in Korea. A 31-year-old woman reported the symptoms of lactation and amenorrhea after taking levosulpiride; an evaluation of whether these symptoms were caused by the medication was therefore necessary. Several tools can be used to determine if the ADR resulted from the administered drug or other factors, including the World Health Organization-Uppsala Monitoring Centre (WHO-UMC) criteria, the Naranjo scale, and the Korean causality assessment algorithm (Ver. 2). The causality was evaluated as "possible" by the WHO-UMC and Naranjo scales, but as "probable" by the Korean causality assessment algorithm (Ver. 2). In conclusion, the information provided did not indicate definite causality and there were slight differences in the results obtained from each assessment method.

• 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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.845-852
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• 2018

Mayer-Schönberger and Cukier(2013) explain why big data is important for our life, while showing many cases in which analysis of big data has great significance for our life and raising intriguing issues on the analysis of big data. The two authors claim that correlation is in many ways practically far more efficient and versatile in the analysis of big data than causality. Moreover, they claim that causality could be abandoned since analysis and prediction founded on correlation must prevail. I critically examine the two authors' accounts of causality and correlation. First, I criticize that corelation is sufficient for our analysis of data and our prediction founded on the analysis. I point out their misunderstanding of the distinction between correlation and causality. I show that spurious correlation misleads our decision while analyzing Simpson paradox. Second, I criticize not only that causality is more inefficient in the analysis of big data than correlation, but also that there is no mathematical theory for causality. I introduce the mathematical theories of causality founded on structural equation theory, and show that causality has great significance for the analysis of big data.

• 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 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.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.677-682
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• 2020

To investigate the nexus between urban population, gross capital formation, and economic growth in the Kingdom of Saudi Arabia, yearly data was collected from the World Bank for the period 1974- 2018. Basic statistics test and correlation matrix was used to investigate the causal effect among the tested parameters, followed by Augmented Dickey-Fuller (ADF) stationary test, co-integration analysis by Johansen test after that Vector Auto-Correction Model for both short-run and long-run and finally the Granger-Causality tests. Result of unit root test analysis shows that the urban population became stationary at I (0) level while economic growth and gross capital formation became stationary at I (1). Johansen co-integration analysis indicates that there is presence of both long-run and short-run relationship between the three variables in the Kingdom of Saudi Arabia. The result of the VECM Model reflects that both economic growth and gross capital formation have a negative impact on urban population in the short run. According to the Granger-Causality tests, there is unidirectional causality with the urban population by both gross capital formation and economic growth. Also, the result of the Granger Causality tests show that there is unidirectional causality between economic growth and gross capital formations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1207-1217
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• 2013

This study utilizes raw data from "Research on the actual condition of firms' information security" of KISA (2010) and constructs panel dataset to analyze a causal relationship between information security investment and security breach. Using Difference in Difference estimation method we find the following results. First, while the usual causality that information security investment reduces security breach is not supported, the reverse causality that security breach increases information security investment is well explained. Second, contrary to the conventional wisdom, firms in the finance/insurance business sector show the most significant reverse causality pattern.

• 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.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.357-364
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• 2018

Colombo noticeably became the most economical gateway to the Indian subcontinent, in terms of cost as well as time. The Colombo Port Expansion Project (CPEP) started commencement with the purpose of accommodating mega ships, under the long-term strategies of making Colombo the hub of South Asia. In this context, the purpose of this study is to investigate the causal relationship between Indian ports' originated container traffic, and total transshipments of the port of Colombo, and also to identify the nature of the causality between the two variables, evaluating Granger causality test results. It finds unidirectional causality from total transshipments of Colombo to Indian ports' originated transshipments in the port of Colombo. It suggested that ongoing port expansion projects, opening up for new markets and attracting new shipping lines in the port of Colombo, have generated significant impact on Indian ports' container traffic, via the port of Colombo. Findings would be valuable for future forecasting of container traffic in Colombo port and the policy-making process in the port as well.