• Title, Summary, Keyword: causality

Search Result 661, Processing Time 0.064 seconds

ALMOST CAUSAL STRUCTURE IN SPACE-TIMES

  • Park, Jong-Chul
    • Journal of the Korean Mathematical Society
    • /
    • v.34 no.2
    • /
    • pp.257-264
    • /
    • 1997
  • We shall introduce the concept of almost causality condition. By defining the almost causality condition we would like to examine the relationship between Woodhouse's causality principle and other known causality conditions. We show that a series of causality conditions can be characterized by using the almost causality condition.

  • PDF

The Analysis of Granger Causality between GDP and R&D Investments in Government, Private, Defense Sectors (국방 R&D 투자 및 정부, 민간 R&D 투자와 국민소득간의 상호 인과관계 분석)

  • Lee, Jin-Woo;Kwon, O-Sung
    • Journal of the military operations research society of Korea
    • /
    • v.34 no.1
    • /
    • pp.79-98
    • /
    • 2008
  • The purpose of this paper is to find the desirable R&D policies in defense area by analyzing causality between GDP and R&D investments in government, private, defense sectors. We have five variables which are composed of GDP, total R&D investment, R&D investments in government, private and defense sectors to figure out the causality between R&D investment in defense sector and other components. In the course of analysis on causality, we took the unit root test of variables to prevent spurious regression. Also we need to take cointegration test about non-stationary variables before the causality test. According to these test results, we took the causality test using ECM(Error Correction Model) for the models which have cointegrating relations. And we took ordinary Granger causality test for model which doesn't have a long-run stationary relationship. As a result of the causality test, it was shown that there exists the long-nu causality to GDP and R&D investments in government and private sectors from other variables. However, there doesn't exist the causality to defense R&D investment from other variables. We found that there doesn't exist the causality between R&D investments in defense and private sectors, and that they are independent.

Causality change between Korea and other major equity markets

  • Kwon, Tae Yeon
    • Communications for Statistical Applications and Methods
    • /
    • v.25 no.4
    • /
    • pp.397-409
    • /
    • 2018
  • The world financial markets are inter-linked in ways that varies according to market and time. We examine the causality of change focusing on the Korean market as related to the U.S. (S&P 500), Japan (Nikkei 225), Hong-Kong (HSI), and European (DAX) markets. In order to capture time-varying causality running from and to the Korea stock market, we apply the Granger causality test under a VAR model with a wild bootstrap rolling-window approach. We also propose a new concept of a significant causality ratio to measure the intensity of the Granger causality in each time unit. There are many asymmetric strengths in mutual Granger causal relationships. Moreover, there are cases with significant Granger causal relations only in one direction. The period with the most severe Granger causality both running from and to the KOSPI market is the GFC. The market that formed the two-way Granger causal relationship with the KOSPI market for the longest period is the S&P 500. The HSI and DAX markets have the strongest two-way Granger causal relationship with the KOSPI shortly after 2000, and the Nikkei market had the strongest two-way Granger causal relationship with the KOSPI market before the Asian financial crisis.

Nonparametric Test for Money and Income Causality

  • Jeong, Ki-Ho
    • Journal of the Korean Data and Information Science Society
    • /
    • v.15 no.2
    • /
    • pp.485-493
    • /
    • 2004
  • This paper considers the test of money and income causality. Jeong (1991, 2003) developed a nonparametric causality test based on the kernel estimation method. We apply the nonparametric test to USA data of money and income. We also compare the test results with ones of the conventional parametric test.

  • PDF

Long-run and Short-run Causality from Exchange Rates to the Korea Composite Stock Price Index

  • LEE, Jung Wan;BRAHMASRENE, Tantatape
    • The Journal of Asian Finance, Economics, and Business
    • /
    • v.6 no.2
    • /
    • pp.257-267
    • /
    • 2019
  • The paper aims to test long-term and short-term causality from four exchange rates, the Korean won/$US, the Korean won/Euro, the Korean won/Japanese yen, and the Korean won/Chinese yuan, to the Korea Composite Stock Price Index in the presence of several macroeconomic variables using monthly data from January 1986 to June 2018. The results of Johansen cointegration tests show that there exists at least one cointegrating equation, which indicates that long-run causality from an exchange rate to the Korean stock market will exist. The results of vector error correction estimates show that: for long-term causality, the coefficient of the error correction term is significant with a negative sign, that is, long-term causality from exchange rates to the Korean stock market is observed. For short-term causality, the coefficient of the Japanese yen exchange rate is significant with a positive sign, that is, short-term causality from the Japanese yen exchange rate to the Korean stock market is observed. The coefficient of the financial crises i.e. 1997-1999 Asian financial crisis and 2007-2008 global financial crisis on the endogenous variables in the model and the Korean economy is significant. The result indicates that the financial crises have considerably affected the Korean economy, especially a negative effect on money supply.

STATISTICAL CAUSALITY AND EXTREMAL MEASURES

  • Petrovic, Ljiljana;Valjarevic, Dragana
    • Bulletin of the Korean Mathematical Society
    • /
    • v.55 no.2
    • /
    • pp.561-572
    • /
    • 2018
  • In this paper we consider the concept of statistical causality in continuous time between flows of information, represented by filtrations. Then we relate the given concept of causality to the equivalent change of measure that plays an important role in mathematical finance. We give necessary and sufficient conditions, in terms of statistical causality, for extremality of measure in the set of martingale measures. Also, we have considered the extremality of measure which involves the stopping time and the stopped processes, and obtained similar results. Finally, we show that the concept of unique equivalent martingale measure is strongly connected to the given concept of causality and apply this result to the continuous market model.

Evolutionary Perspective on Autism (자폐증에 대한 진화적 관점)

  • Jeong, Yunjin;Son, Jung-Woo;Kim, Bung-Nyun;Yoo, Hee Jeong
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
    • /
    • v.26 no.2
    • /
    • pp.67-74
    • /
    • 2015
  • So far, most research studying the causality of autism has focused on neurobiological or psychological aspects. However, most studies have dealt with only proximal causality of autism, and there is little research on its ultimate causality. 'Evolutionary perspective', which has received attention recently in various academic fields, suggests several theories regarding the ultimate causality of autism. We reviewed different theories on the evolution of autism, and discussed both the merits and the limitations of the theories.

Impact of Debts on Economic Growth of Bangladesh: An Application of ARDL Model

  • Hossain, Muhammad Amir;Shirin, Shabnam
    • Asia-Pacific Journal of Business
    • /
    • v.7 no.1
    • /
    • pp.1-10
    • /
    • 2016
  • This study attempts to investigate the effects of different types of debts on economic growth in Bangladesh using time series data spanning from 2000 to 2015. In this study, the RDL model has been applied to determine the long run relationship among the selected variables. The result of the ARDL model shows that there exists a long term relationship between economic growth and the debt variables. It was evident from the findings that there exists bidirectional causality between public sector external debt and economic growth. Causality between private external debt and economic growth has been found to be insignificant. However, causality between domestic debt and economic growth showed a unidirectional causality from domestic debt to economic growth and not vice versa. Causality tests suggest that impact of domestic debt on economic growth is more effective compared to external debts.

  • PDF

Tests for Causality from Internet Search to Return and Volatility of Cryptocurrency: Evidence from Causality in Moments (인터넷 검색을 통한 암호화폐 수익률 및 변동성에 대한 인과검정: 적률인과 접근)

  • Jeong, Ki-Ho;Ha, Sung Ho
    • The Journal of Information Systems
    • /
    • v.29 no.1
    • /
    • pp.289-301
    • /
    • 2020
  • Purpose This study analyzes whether Internet search of cryptocurrency has a causal relationship to return and volatility of cryptocurrency. Design/methodology/approach Google Trend was used as a measure of the level of Internet search, and the parametric tests of Granger causality in the 1st moment and the 2nd moment were adopted as the analysis method. We used Bitcoin's dollar-based price, which is the No. 1 market value among cryptocurrency. Findings The results showed that the Internet search measured by Google Trends has a causal relationship to cryptocurrency in both average and volatility, while there is a difference in causality and its degree according to the search area and category that Google Trend user should set. Because the Granger causality is based on the improvement of prediction, the analysis results of this study indicate that Internet search can be used as a leading indicator in predicting return and volatility of cryptocurrency.

Causality join query processing for data stream by spatio-temporal sliding window (시공간 슬라이딩윈도우기법을 이용한 데이터스트림의 인과관계 결합질의처리방법)

  • Kwon, O-Je;Li, Ki-Joune
    • Spatial Information Research
    • /
    • v.16 no.2
    • /
    • pp.219-236
    • /
    • 2008
  • Data stream collected from sensors contain a large amount of useful information including causality relationships. The causality join query for data stream is to retrieve a set of pairs (cause, effect) from streams of data. A part of causality pairs may however be lost from the query result, due to the delay from sensors to a data stream management system, and the limited size of sliding windows. In this paper, we first investigate spatial, temporal, and spatio-temporal aspects of the causality join query for data stream. Second, we propose several strategies for sliding window management based on these observations. The accuracy of the proposed strategies is studied by intensive experiments, and the result shows that we improve the accuracy of causality join query in data stream from simple FIFO strategy.

  • PDF