Short run and long run causality in time series: inference

Dufour, Jean Marie; Pelletier, Denis; Renault, Éric

doi:10.1016/j.jeconom.2005.02.003

Cited by 113 publications

(216 citation statements)

References 46 publications

(48 reference statements)

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“…We are not interested in causality in a longer horizon, because, as Dufour and Renault [1998] and Dufour, Pelletier, and Renault [2006] show, in the financial market, if there is no causality between } { t X and } { t Y , it will be difficult to explore Granger causality in a longer horizon. As a consequence of the development of information technology, the impact of information in one market has the most significant effects in a short run.…”

Section: Resultsmentioning

confidence: 99%

Causality in distribution between European stock markets and commodity prices: using independence test based on the empirical copula

Wanat¹,

Papież²,

Śmiech³

2015

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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Section: Resultsmentioning

confidence: 99%

Causality in distribution between European stock markets and commodity prices: using independence test based on the empirical copula

Wanat¹,

Papież²,

Śmiech³

2015

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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“…Standard errors (S.E.) in all equations are based on the Newey-West estimator of the variance-covariance matrix (see, Dufour, Pelletier and Renault [35]). …”

Section: Impact Of News Releasesmentioning

confidence: 99%

The Efficiency in Liquidity Measures during the US Monetary Announcements

Vortelinos¹,

Γκίλλας²,

Konstantatos³

et al. 2018

TEL

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We examine the impact of US economic news releases in the liquidity of eleven not so extensively researched emerging stock markets. We employ ten liquidity measures. The sample begins from June 2007 up to December 2016. Analysis is performed in a weekly frequency. China is the least liquid Asian market. Peru is the most liquid Latin American market. Most of the emerging markets are positively affected by the US news, offering diversification benefits to international investors. India and Argentina (China and Chile) are the Asian and Latin American countries with the highest (lowest) impacts, respectively. There is not a single best-in-class liquidity measure. The country with the lowest liquidity has the lowest impact from the US news releases. This result holds for both groups of countries in Asia and Latin America.

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“…Rejecting non-causality hypotheses in statistical tests implies that certain variables can help in forecasting others [Dufour et al (2006)]. Of course, statistical significance depends on the data sets and test power, and the outcomes of such tests do not represent the magnitude of causality.…”

Section: Measuring Causality Across Horizonsmentioning

confidence: 99%

“…We examine the causal relationship between commodity prices and nominal exchange rates for three commodity currencies (Canada, Australia, Chile) and three commodity spot prices (crude oil, copper and gold), using daily data (and 5-minute data, for Canada). In view of the incomplete nature of causality at only one horizon, we study and compare causality at different horizons as proposed in Dufour and Renault (1998) and Dufour, Pelletier and Renault (2006). Further, to avoid the overly simplifying features of pure significance tests for non-causality, we compute measures at many horizons because they allow one to assess in a much more precise way the underlying linkages when causality at different horizons in different directions is present.…”

Section: Introductionmentioning

confidence: 99%