Causality in temporal systems

Pierce, David A.; Haugh, Larry D.

doi:10.1016/0304-4076(77)90039-2

Cited by 521 publications

(63 citation statements)

References 17 publications

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“…For our purposes, it is more convenient to rewrite the above bivariate process as two univariate processes (this can always be done according to [17]):…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…In Section 2, we start by introducing an alternative formulation of Granger causality [17] and proceed to outline a framework within which the effects of added (measurement) noise on the estimation of directional influences in bivariate autoregressive processes can be addressed. To simplify matters, we then consider a bivariate first order autoregressive (AR(1)) process in Section 3.…”

Section: Introductionmentioning

confidence: 99%

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Mitigating the effects of measurement noise on Granger causality

2007

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Computing Granger causal relations among bivariate experimentally observed time series has received increasing attention over the past few years. Such causal relations, if correctly estimated, can yield significant insights into the dynamical organization of the system being investigated. Since experimental measurements are inevitably contaminated by noise, it is thus important to understand the effects of such noise on Granger causality estimation. The first goal of this paper is to provide an analytical and numerical analysis of this problem. Specifically, we show that, due to noise contamination, (1) spurious causality between two measured variables can arise and (2) true causality can be suppressed. The second goal of the paper is to provide a denoising strategy to mitigate this problem. Specifically, we propose a denoising algorithm based on the combined use of the Kalman filter theory and the Expectation-Maximization (EM) algorithm. Numerical examples are used to demonstrate the effectiveness of the denoising approach.

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“…For our purposes, it is more convenient to rewrite the above bivariate process as two univariate processes (this can always be done according to [17]):…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mitigating the effects of measurement noise on Granger causality

2007

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“…The appearance of both events is followed by concluding the presence of a feedback loop (Schmidt 1976;Pierce and Haugh 1977;Geweke et al 1983;Guilkey and Salemi 1982;Gao and Tian 2009). The F-statistics value computed for the purpose of the causality test assesses the equation presented above (2):…”

Section: Methodsmentioning

confidence: 99%

Alterations in the Financial Markets of the Baltic Countries and Russia in the Period of Economic Downturn / Finansų Rinkų Pokyčiai Baltijos Šalyse Ir Rusijoje Ekonominio Nuosmukio Laikotarpiu

Dubinskas

Stungurienė

2010

Technological and Economic Development of Economy

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The present article analyses the alternations in the causality in the financial markets during the 2008–2009 financial crisis with a clear focus on the changes and developments in the financial markets of the Baltic States and Russia in the period starting from 2008. The authors have advanced a hypothesis that the research methods of trends of an abrupt plunge and subsequent stabilistation of equity prices that were clearly discernable during the 1987 crisis are also pointfull for the current financial crisis. The present research was conducted on the basis of the following assumptions: both crises affected financial markets of several nations; a characteristic feature for the inception of the crises is an abrupt fall in equity prices; indications of stabilisation in financial markets become observable before financial experts conclude the end of the financial crisis. To confirm the hypothesis on the similarities of the general trends during the two major international financial crisis, the authors employed empiric tests developed on the basis of Granger causality tests. Based on the precedent survey of the financial crisis of 1987 (Malliaris and Urrutia 1992), the authors of the present article chose to use the Granger causality testing methodology. To be able to apply the Granger causality test first it was necessary to verify the degree of cointegration of the indices of the main equity markets in each of the country (OMX Vilnius, OMX Riga, OMX Tallinn, RTS). For that purpose the authors used the Dickey‐Fuller and Johansen testing methodology. Both methodologies demonstrated a strong cointegration between the changes in the indices of all equity markets irrespective of the period analysed (i.e., pre‐crisis, during the crisis, post‐crisis). In all cases the T‐statistics exceeded the critical value. The strongest cointegration was observable in the crisis period, and the weakest – after the crisis. The results showed that in view of the financial crisis the Latvian market showed the greatest degree of slow‐down despite it being most active in the pre‐crisis times, likewise, Estonian market also showed a somewhat higher degree of passiveness. Thus, it was the Latvian and Estonian markets that the financial downturn had the most painful impacts upon. While the Lithuanian and the Russian markets were, on the contrary, much more active and therefore outlived the equity crash period with least painful after‐effects, thus producing confirmation that in the face of a crisis the interests and expectations of most investors are largely related to major markets normally viewed as more reliable and showing a higher degree of resilience. Santrauka Straipsnyje analizuojami finansų rinkų priežastingumo pokyčiai 2008–2009 m. finansinės krizės laikotarpiu. Pagrindinis dėmesys sutelkiamas į Baltijos šalių– Lietuvos, Latvijos ir Estijos – bei Rusijos akcijų rinkų pokyčius nuo 2008 m. Autoriai iškelia hipotezę, kad finansų rinkose staigaus akcijų kainų kritimo ir jų stabilizavimosi tendencijos, kurios išryškejo nuo 1987 m. prasidėjusios krizės, būdingos dabartinei finansinei krizei. Tyrimo metu daromos prielaidos: abi krizės apima daugelio valstybių finansų rinkas; krizių pradžiai būdingas staigus akcijų kainų kritimas; finansų rinkų stabilizavimosi požymiai pastebimi anksčiau, nei ekspertai konstatuoja krizės pabaigą. Dviejų tarptautinių finansų rinkų krizių bendrųjų tendencijų panašumo hipotezei patvirtinti naudoti empiriniai testai, parengti remiantis Granger priežastiniais testais: Granger priežastiniai testai ir kointegracijos testai. Nustatyta, kad finansinės krizės metu Latvijos rinka tapo pasyviausia, nors iki prasidedant krizei buvo pati aktyviausia, pasyvesne tapo ir Estijos rinka. Taigi finansinis nuosmukis skaudžiausiai paveikė Latvijos ir Estijos finansų rinkas. Lietuvos ir Rusijos rinkos krizės metu tapo pačios aktyviausios ir lengviausiai išgyveno akcijų kainų kritimo perioda, tuo patvirtindamos, kad krizės metu daugelio investuotojų interesai ir lūkesčiai paprastai siejami su didesnemis rinkomis, kurios laikomos patikimesnėmis ir turinčiomis galimybę greičiau atsigauti.

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“…Thus, causality runs from X to Y if knowledge of X results in a smaller error variance in predicting Y than would result from a prediction based solely on past observations of Y.? One might be hesitant to use the word 'causality' to describe the nature of the association that would then exist but it appears difficult to present an alternative definition for causality which can be empirically tested (Pierce and Haugh, 1977).…”

Section: Methodsmentioning

confidence: 99%

The impact of crude oil price fluctuations on unemployment in the United States

Uri

Boyd

1996

Int. J. Energy Res.

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SUMMARYThis study begins by asking whether fluctuations in the price of crude oil have affected employment in the United States. After reviewing previous assessments of the issue, the existence of an empirical relationship between unemployment and crude oil price volatility is established using Granger causality. Subsequently, the nature of the relationship is estimated with the results suggesting that at least three full years are required before measurable impacts of a percentage change in the real price of crude oil on the change in unemployment are exhausted. Finally, the structural stability of the functional relationship between the change in unemployment, the volatility of the price of crude oil and the percentage change in gross national product is examined.

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Causality in temporal systems

Cited by 521 publications

References 17 publications

Mitigating the effects of measurement noise on Granger causality

Mitigating the effects of measurement noise on Granger causality

Alterations in the Financial Markets of the Baltic Countries and Russia in the Period of Economic Downturn / Finansų Rinkų Pokyčiai Baltijos Šalyse Ir Rusijoje Ekonominio Nuosmukio Laikotarpiu

The impact of crude oil price fluctuations on unemployment in the United States

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