• Journal of Technology Innovation
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• v.24 no.2
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• pp.91-113
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• 2016

The purpose of this study is to examine the causal relationship among R&D spending and variables of technology trade, and to explore promoting R&D activities and revitalizing technology trade. To analyze the causal relationship, we built a multivariate model that consists of government R&D spending, private R&D spending, technical importation and export of techniques, and employed the Granger-causality test based on an error correction model. The results show that there are five Granger-causality relationship among them in the short run, as well as there are eleven Granger-causality relationship among a total of twelve causal relationship, excluding only a unidirectional causality relationship from the government R&D spending to the export of techniques, in the long run. Besides, we attempted the impulse-response analysis on them to observe the reaction of any dynamic system in response to some external change. The significance of this paper is to make sure the causal relationship between R&D investments and the technology trade by analyzing empirically, and to suggest several implications for promoting the R&D activities and revitalizing the technology trade.

• Journal of Science Education
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• v.38 no.2
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• pp.454-469
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• 2014

Teachers' presuppositions of nature of science, scientific causality, and nature are unconsciously constructed through interactions with his or her physical and social environment everyday and it began even before they were in any formal education. It directly influences their teaching later. Thus, this study examined what comprehensive presuppositions in nature of science, scientific causality, and nature are held by in-service secondary science teachers. For the study, Q-methodology was used. Q-sorting was done on 81 statements from three instruments: Nature statements, the Test of Preferred Explanations, and the Nature of Science Scale with twelve in-service science teachers. Teachers sorted the statements along a presented agreement scale of their viewpoint and the collected data was analyzed using recommended procedures for Q-sorts in order to group teachers with similar views. As a result, ten participants were placed in five factors based on their presuppositions of science, scientific causality, and nature and distinctive features of each factor were discovered. In addition, the study confirmed that presuppositions of science, scientific causality, and nature are interrelated. This study method will be helpful to discover more relationships regarding teachers' various viewpoints further.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.109-115
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• 2016

This study intended to testify the causality among three variables such as accident, depression and cognitive failure of the train drivers. For this purpose, two research models were suggested. Model 1 hypothesized the causality among three variables as 'depression ${\rightarrow}$ cognitive failure ${\rightarrow}$ accident'. On the other hand, model 2 hypothesized the causality among three variables as 'accident ${\rightarrow}$ depression ${\rightarrow}$ cognitive failure'. Results based on AMOS using 416 train drivers' questionnaire showed that model 2 is more valid than model 1. The statistical result of model 1 showed that depression has a positive effect on cognitive failure, however no significant relationship between depression and accident as well as between cognitive failure and accident. In model 2, the result showed that the accident has a positive effect on cognitive failure mediated by depression. This result suggests the necessity for establishment of countermeasures to mitigate mistake and cognitive failure caused by train drivers in a wider context, considering the causality between accident and depression.

• Information Systems Review
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• v.19 no.1
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• pp.185-202
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• 2017

Most studies based on production function theory have concluded that economic growth is a result of information technology (IT) capital use. However, some studies have indicated that economic growth is a determinant of IT investment. To determine if these results also hold at the industry level, we use the Granger causality test to analyze bidirectional causality with industry-level data for 1977~2007 from the United States. The results generally reveal that IT investment causes economic growth in many industries under the concept of Granger causality, that economic growth causes IT investment in some industries, and that IT investment is not associated with economic growth in some industries. In the country-level time-series data made by summing up the IT capital and gross output for each industry, the results do not show any causality between IT investment and economic growth. However, they show bi-directional causality between IT investment and economic growth in the panel data. These results may be a source of IT productivity paradox.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.89-99
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• 2012

This study investigates the Granger-causality between economic growth and demand for electricity in Korea, using two quarterly time-series data (real GDP and electricity consumption) for 1970:Q1 through 2009:Q4. We apply Hsiao's sequential procedure to identify a vector autoregressive model to a decision of the optimal lags in the vector error-correction model because the two time-series data contain unit roots respectively and they are cointegrated. According to the empirical results in this study, we find that Hsiao's approach to the Granger-causality indicates a bidirectional causal relation between economic growth and demand for electricity in Korea. Following the Granger and Engle's approach, we also find the statistical evidence on (1) short-run bidirectional causality between real GDP and electricity consumption, (2) bidirectional strong causality between them, and (3) long-run unidirectional causality running from demand for electricity to economic growth. Our results show an inconsistency with the existing studies on Korea's case; however, the results appear to provide more meaningful policy implications for the Korean economy and its strategy of sustainable growth.

• Communications of the Korean Mathematical Society
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• v.11 no.3
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• pp.783-788
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• 1996

We study some causality characterizations in a space-time by considering chronological common future (or past) sets and indecomposable sets that are important roles in studying causal boundary structure of the space-time.

• Communications of the Korean Mathematical Society
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• v.10 no.2
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• pp.385-392
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• 1995

Along with certain properties of a chronal or a causal isomorphism, we discuss the invariant nature of a causality conditions of a given space-time.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.655-660
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• 2009

As the global economic crisis, the Korean foreign exchange market appears unstable with large fluctuations in exchange rate. Inevitably, there is growing attention on price variables such as exchange rate and interest rates and also on corelation between the factors. This is an empirical study on the causality of fluctuation between exchange rate and interest rate in the Korean market under global economic crisis. The fluctuations in won/dollar exchange rate and call rate are described and followed by analysis of lead-lag relationship between the two variables using Cross-correlation function and Granger causality test.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.329-336
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• 2008

Recently, causality analysis of source time series extracted from EEG or MEG signals is becoming of great importance in human brain mapping studies and noninvasive diagnosis of various brain diseases. Two approaches have been widely used for the analyses: one is independent component analysis (ICA), and the other is multiple signal classification (MUSIC). To the best of our knowledge, however, any comparison studies to reveal the difference of the two approaches have not been reported. In the present study, we compared the performance of the two different techniques, ICA and MUSIC, especially focusing on how accurately they can estimate and separate various brain electrical signals such as linear, nonlinear, and chaotic signals without a priori knowledge. Results of the realistic simulation studies, adopting directed transfer function (DTF) and Granger causality (GC) as measures of the accurate extraction of source time series, demonstrated that the MUSIC-based approach is more reliable than the ICA-based approach.