• Title/Summary/Keyword: 인과관계도

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주가와 지가의 인과관계에 관한 연구

  • 최승은
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.10a
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    • pp.313-316
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    • 1996
  • 주식과 부동산은 각각 금융자산(financial asset)과 실물자산(real asset)의 대표 격으로 투자자들에게 매력적인 투자대상이다. 투자자들은 경제 여건의 변화에 따라 나타나는 두 자산의 수익률 차이를 최대한 이용하려고 노력해 왔다. 흔히들 주가와 지가는 서로 대칭적인 것으로 주가가 오르면 지가가 떨어지고, 지가가 오르면 부동산 시장으로 자금이 몰려서 주가가 떨어지는 것으로 얘기하는 경우가 많으나, 실제로는 동행관계로서 완급차이가 있을 뿐이다. 경기변동 곡선을 따라 경기변동에 민감한 주가가 우선적으로 반응하고 뒤이어 지가가 1년여의 시차를 두고 비슷한 패턴을 보이고 있다. 지금까지 대부분의 논문은 지가결정 모형을 세우기 위한 것으로 주가 이외에도 다른 여러 독립 변수들이 지가에 어떤 영향을 주는지를 연구하였다. 지가가 종속변수로서 여러 가지 실물 경기의 상황에 영향을 받는 것처럼 주가도 역시 다른 경기지표의 영향을 받는다. 그러므로 본 연구의 목적은 과거 30여년간의 우리나라 주가와 지가의 움직임을 통하여 주가와 지가 사이의 인과관계를 규명하는데 있다. 즉 주가와 지가 사이에 일방적인 인과관계가 있어서 주가가 지가에 선행하는지, 혹은 주가와 지가 사이에 상호적인 인과관계가 있는지 실증적인 연구를 통하여 알아보고자 한다.

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A Causality Analysis between R&D Investment and Technology Trade (R&D 투자와 기술무역 간의 인과관계 분석)

  • Pak, Cheolmin;Ku, Bonchul
    • 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.

한국의 전력소비와 경제성장의 인과관계 분석

  • Jo, Jeong-Hwan;Gang, Man-Ok
    • Environmental and Resource Economics Review
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    • v.21 no.3
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    • pp.573-593
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    • 2012
  • The paper examined the relationship between total and sector level electricity consumptions and economic growth in Korea for the period of 1980-2009. The results of unit-roots and cointegration tests show that all variables-real GDP, total, primary, manufacture, and service sector electricity consumptions-were not stationary and there were no linear combinations in the long run between electricity consumptions and economic growth. Thus, by using standard Granger-causality test we found that total, primary, and manufacture sector electricity consumptions were Granger-caused by economic growth, not vice versa. This means that causality runs from economic growth to each electricity consumption. However, there is no causal relationship between service sector electricity consumption and economic growth. These results imply that the government policies aimed at reducing electricity consumptions and increasing energy efficiency etc. can be feasible without deterring economic growth in Korea.

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금리선물(金利先物)의 가격발견기능(價格發見機能)에 대한 실증적(實證的) 검정(檢定)

  • Sin, Min-Sik;Lee, Jun-Sik
    • The Korean Journal of Financial Management
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    • v.14 no.2
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    • pp.205-228
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    • 1997
  • 본 연구는 1982년부터 1996년까지의 유로달러선물과 T-bill 선물의 일별 시계열 자료를 이용하여 단기금리선물의 가격발견기능을 실증적으로 검정하고 있다. 분석방법은 시계열의 불안정성 여부를 알아보는 단위근검정, 장기균형관계를 알아보는 Johansen 공적분검정, 공적분관계가 있는 시장에 대해 설정오류의 문제를 피하고 변수들간의 인과관계를 파악하기 위해 Granger 인과관계모형을 사용하였다. 주요한 결과로 각 금리시계열들은 일차누적 시계열 I(1)임이 확인되었고 공적분관계를 분석한 결과, 각 금리 시계열의 선형결합은 안정적인 장기균형관계가 있음을 나타내 주고 있다. 따라서 각 시장은 서로 밀접한 인과관계가 있음을 암시하고 있다. 또한 선물금리와 현물금리를 대상으로 인과관계검정 결과 유로달러시장의 경우 전기에서는 피드백효과가 있고 후기에는 선물금리의 가격발견기능이 나타났다. T-bill 시장의 경우는 전기에 현물금리가 선물금리에 대해 선행하였고 후기에는 피드백효과가 나타났다. 이렇게 유로달러선물이 후기에서 가격발견기능이 있는 것은 정보통신의 발달과 유로시장의 적은 규제 등으로 유로달러선물시장이 1980년대 후반부터 급성장한 것이 그 원인으로 분석된다.

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A Test for Nonlinear Causality and Its Application to Money, Production and Prices (통화(通貨)·생산(生産)·물가(物價)의 비선형인과관계(非線型因果關係) 검정(檢定))

  • Baek, Ehung-gi
    • KDI Journal of Economic Policy
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    • v.13 no.4
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    • pp.117-140
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    • 1991
  • The purpose of this paper is primarily to introduce a nonparametric statistical tool developed by Baek and Brock to detect a unidirectional causal ordering between two economic variables and apply it to interesting macroeconomic relationships among money, production and prices. It can be applied to any other causal structure, for instance, defense spending and economic performance, stock market index and market interest rates etc. A key building block of the test for nonlinear Granger causality used in this paper is the correlation. The main emphasis is put on nonlinear causal structure rather than a linear one because the conventional F-test provides high power against the linear causal relationship. Based on asymptotic normality of our test statistic, the nonlinear causality test is finally derived. Size of the test is reported for some parameters. When it is applied to a money, production and prices model, some evidences of nonlinear causality are found by the corrected size of the test. For instance, nonlinear causal relationships between production and prices are demonstrated in both directions, however, these results were ignored by the conventional F-test. A similar results between money and prices are obtained at high lag variables.

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Category-Based Feature Inference: Testing Causal Strength (범주기반 속성추론: 인과관계 강도의 검증)

  • JunHyoung Jo;Hyung-Chul O. Li;ShinWoo Kim
    • Science of Emotion and Sensibility
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    • v.26 no.1
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    • pp.55-64
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    • 2023
  • This research investigated category-based feature inference when category features were connected in common cause and common effect causal networks. Previous studies that tested feature inference in causal categories showed unique inference patterns depending on causal direction, number of related features, whether the to-be-inferred feature was cause or effect, etc. However, these prior studies primarily focused on inference pattens that arise from causal relations, and few studies directly explored how the effects of causal relations vary depending on causal strength. We tested feature inference in common cause (Expt. 1) and common effect (Expt. 2) causal categories when casual strengths were either strong or weak. To this end, we had participants learn causal categories where features were causally linked and then perform feature inference task. The results showed that causal strengths as well as causal relations had important impacts on feature inference. When causal strength was strong, inference for common cause feature became weaker but that for the common effect feature became stronger. Moreover, when causal strength was strong and common cause was present, inference for the effect features became stronger, whereas the results were reversed in common effect networks. In particular, in common effect networks, casual discounting was more evident with strong causal strength. These results consistently demonstrate that participants consider not only causal relations but also causal strength in feature inference of causal categories.

The Verification of Causality among Accident, Depression, and Cognitive Failure of the Train Drivers (철도기관사의 사고, 우울감, 인지실패 간의 인과관계 검증)

  • Ro, Choon-Ho;Shin, Tack-Hyun
    • 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.

A Study on Causal Relations among BSC Performance Measurement Indexes - Focused on the case of C University Hospital - (BSC 성과측정지표간의 인과관계에 관한 연구 - C대학병원 사례 중심으로 -)

  • Shin, Seung-Kwon
    • Korean Business Review
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    • v.20 no.2
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    • pp.119-133
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    • 2007
  • The present study purposed to examine whether BSC, a management renovation method, is as effective in university hospitals, which are non-profit institutions, as it is in profit-making corporations. In order to determine causal relations among the BSC performance measurement indexes, we analyzed a case of university hospital using a structural equation model. The results of analyzing the causal relations among the BSC performance measurement indexes were all statistically significant, and therefore the research hypotheses were all accepted. Future research needs to study causal relations among the BSC performance measurement indexes from the viewpoint of the learning of financial data, growth, internal processes, and customers.

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Developing an Entropic Drawdown-at-Risk (EDaR) Fluctuation Forecasting Model for Commodity Futures Market Using Entropy-Based Dependency and Causality Network Modularity (엔트로피 기반 인과관계 네트워크의 모듈성을 활용한 상품 선물 시장의 EDaR 변동 예측 모형 개발)

  • Choi, Insu;Kim, Woo Chang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.370-373
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    • 2022
  • 본 연구에서는 전이 엔트로피 개념을 활용하여 주요 상품 선물의 하방 리스크 지수의 정보 흐름을 바탕으로 한 인과관계 네트워크를 구성하였다. 그리고 구성된 네트워크를 활용하여 금융 시장을 분석하였으며, 또한 정보 흐름의 존재 여부를 바탕으로 상품 선물의 하방 리스크 지수의 예측력이 개선될 수 있는지 확인하고자 하였다. 이를 위하여 정보 불확실성의 감소량을 측정하는 전이 엔트로피를 인과관계의 측정 지표로 상정하였으며, 전이 엔트로피 측정 시 발생할 수 있는 유한크기효과(finite size effect)를 조정하는 데 있어서 효과적인 지표인 효율적 전이 엔트로피를 활용하여 정보 흐름 네트워크를 구성하였으며 이를 이용하여 금융 지수 간의 인과관계를 분석하고 EDaR 의 등락 예측에 활용하였다. 그 결과, 금융 시장 지수를 효율적 전이 엔트로피를 이용한 인과관계 네트워크를 활용하여 금융 시장의 복잡계 네트워크 분석이 가능함을 확인하였고, 구성된 네트워크를 활용하여 국내 금융 시장 등락 예측에 있어 더 적은 데이터 열을 활용하여 거의 유사한 예측 결과를 냄으로써 상품 선물 시장 관련 예측의 데이터 열 선택에 활용할 수 있음을 확인하였다.

Latest Supreme Court Decision on Proof of Causation in Medical Malpractice Cases - Focusing on Supreme Court decision 2022da219427 on August 31, 2023 and the Supreme Court decision 2021Do1833 on August 31, 2023 - (의료과오 사건에서 인과관계 증명에 관한 최신 대법원 판결 - 대법원 2023. 8. 31. 선고 2022다219427 판결 및 대법원 2023. 8. 31. 선고 2021도1833 판결을 중심으로 -)

  • HYEONHO MOON
    • The Korean Society of Law and Medicine
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    • v.24 no.4
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    • pp.3-36
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    • 2023
  • The main issue in medical malpractice civil litigation is medical negligence and the causal relationship between medical negligence and damages. Regarding the presumption of causality in cases where medical negligence is proven, there is a previous Supreme Court decision 93da52402 on February 10, 1995, but it is difficult to find a case that satisfies the textual requirements of the above decision, and yet, in practice, the above decision is cited. In many cases, causal relationships were assumed, and criticism was consistently raised that it was inconsistent with the text of the above judgment. In its ruling, the Supreme Court reorganized and presented a new legal principle regarding the presumption of causality when medical negligence is proven in a civil lawsuit. According to this, If the patient proves ① the existence of an act that is assessed as a medical negligence, that is, a violation of the duty of care required of an ordinary medical professional at the level of medical care practiced in the field of clinical medicine at the time of medical practice, and ② that the negligence is likely to cause damages to the patient, the burden of proving the causal relationship is alleviated by presuming a causal relationship between medical negligence and damage. Here, the probability of occurrence of damage does not need to be proven beyond doubt from a natural scientific or medical perspective, but if recognizing the causal relationship between the negligence and the damage does not comply with medical principles or if there is a vague possibility that the negligence will cause damage, causality cannot be considered proven. Meanwhile, even if a causal relationship between medical negligence and damage is presumed, the party that performed the medical treatment can overturn the presumption by proving that the patient's damage was not caused by medical negligence. Meanwhile, unlike civil cases, the standard is 'proof beyond reasonable doubt' in criminal cases, and the legal principle of presuming causality does not apply. Accordingly, in a criminal case of professional negligence manslaughter that was decided on the same day regarding the same medical accident, the case was overturned and remanded for not guilty due to lack of proof of a causal relationship between medical negligence and death. The above criminal ruling is a ruling that states that even if 'professional negligence' is recognized in a criminal case related to medical malpractice, the person should not be judged guilty if there is a lack of clear proof of 'causal relationship'.