Better to give than to receive: Predictive directional measurement of volatility spillovers

Diebold, Francis X.; Mody, Ashoka

doi:10.1016/j.ijforecast.2011.02.006

Cited by 3,887 publications

(3,565 citation statements)

References 16 publications

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“…We proceed with the FEVD based on the generalized VAR as proposed by Pesaran and Shin (1998) and further developed by Dees et al (2007) and Diebold and Yilmaz (2012), which does not require specific ordering and it is thus robust to errors due to incorrect ordering 5 .…”

Section: Replication Resultsmentioning

confidence: 99%

Food versus fuel: An updated and expanded evidence

et al. 2019

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. What do prices tell us?" Energy Policy 38, pp. 445-451. We confirm the findings of the original paper that there was only a weak relationship between ethanol and food commodities in the period between March 1989 and July 2008. In addition, we extend that study and examine the cointegration relationship between biofuels and related commodities for a considerably enlarged dataset (3 vs. 1 market, 26 vs. 8 commodities, analysis up till 2017 vs. 2008, weekly vs. monthly data frequency). Focusing on the biofuel markets of Brazil, the EU and the USA in the three separate periods before, during, and after the food crisis of 2007 and 2008, we show that studying the time variation of the relationships plays an essential role in their proper understanding. Our results help to clarify the wide extensive discussion about the role of biofuels prices in food shortages manifested particularly during the food crises. In agreement with the original study, we confirm that price series data do not support strong statements about biofuels uniformly serving as main leading source of high food prices and consequently the food shortages. Terms of use: Documents in

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Section: Replication Resultsmentioning

confidence: 99%

Food versus fuel: An updated and expanded evidence

et al. 2019

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“…Diebold and Yilmaz (2009) use Cholesky decomposition, which yields variance decompositions dependent on the ordering of the variables, whereas Diebold and Yilmaz (2012) extend the Diebold and Yilmaz (2009) model, using the generalized VAR framework of Koop et al (1996) and Pesaran and Shin (1998), in which variance decompositions are invariant to the order of the variables. Both models yield an N × N matrix φ(H) = [φ ij (H)] i,j=1,...N , where each entry gives the contribution of variable j to the forecast error variance of variable i.…”

Section: Spillover Methodologymentioning

confidence: 99%

“…In particular, the aim of this paper is to examine spillovers between Brent crude oil prices and the Baker et al (2013) economic policy uncertainty index (EPU). To achieve that, we extend the spillover index approach by Yilmaz (2009, 2012), using structural decomposition rather than Choleski decomposition (Diebold and Yilmaz, 2009) or generalized forecast error variance decomposition (Diebold and Yilmaz, 2012). Furthermore, in order to generate more informative results, we disentangle oil price shocks according to their origin (i.e.…”

Section: Introductionmentioning

confidence: 99%

Dynamic spillovers of oil price shocks and economic policy uncertainty

2014

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This study examines the dynamic relationship between changes in oil prices and the economic policy uncertainty index for a sample of both net oil-exporting and net oil-importing countries over the period 1997:01-2013:06. To achieve that, an extension of the Yilmaz (2009, 2012) dynamic spillover index based on structural decomposition is employed. The results reveal that economic policy uncertainty (oil price shocks) responds negatively to aggregate demand oil price shocks (economic policy uncertainty shocks). Furthermore, during the Great Recession of 2007-2009, total spillovers increase considerably, reaching unprecedented heights. Moreover, in net terms, economic policy uncertainty becomes the dominant transmitter of shocks between 1997 and 2009, while in the post-2009 period there is a significant role for supply-side and oil specific demand shocks, as net transmitters of spillover effects. These results are important for policy makers, as well as, investors interested in the oil market.

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“…As in Diebold and Yilmaz (2012), the econometric framework is based on the following covariance-stationary Vector AutoRegression (VAR) model…”

Section: The Empirical Frameworkmentioning

confidence: 99%

“…It also investigates the role of bilateral trade flows and financial linkages in business cycle co-movements between the LA region and its main economic partners. More specifically, the analysis is based on the framework introduced by Diebold and Yilmaz (2012) and uses a very flexible empirical model to examine the propagation of international business cycles without any restrictions on the directions of short-and long-run spillovers or the nature of the propagation mechanism itself.…”

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confidence: 99%