Summary We propose an extension of the bivariate nonparametric Diks–Panchenko Granger non‐causality test to multivariate settings. We first show that the asymptotic theory for the bivariate test fails to apply to the multivariate case, because the kernel density estimator bias and variance cannot both tend to zero at a sufficiently fast rate. To overcome this difficulty we propose to reduce the order of the bias by applying data sharpening prior to calculating the test statistic. We derive the asymptotic properties of the ‘sharpened’ test statistic and investigate its performance numerically. We conclude with an empirical application to the US grain market, using the price of futures on heating degree days as an additional conditioning variable. Copyright © 2015 John Wiley & Sons, Ltd.

In this paper we propose an extension of the nonparametric Granger causality test, originally introduced by Diks and Panchenko [2006. A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics & Control 30, 1647-1669]. We show that the basic test statistics lacks consistency in the multivariate setting. The problem is the result of the kernel density estimator bias, which does not converge to zero at a sufficiently fast rate when the number of conditioning variables is larger than one. In order to overcome this difficulty we apply the data-sharpening method for bias reduction. We then derive the asymptotic properties of the 'sharpened' test statistics and we investigate its performance numerically. We conclude with an empirical application to the US grain market.

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There is no clear-cut evidence on how the adoption of the European fiscal standards influences discretionary fiscal policies within the Member States. This study investigates that phenomenon on the example of the 2004 enlargement. The results show that the effects of the adoption of EU fiscal rules bring a statistically significant change towards more countercyclical behavior. The results are robust for different model specifications, including alternative time spans and correcting for the possible influence of the financial crises and political forces. Interestingly, the year 2004 did not have any significant impact on the change in fiscal policies in the Old Member States, suggesting that the EU entry might motivate new members to run more prudent budgetary policies.

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We create a network of bilateral correlations of changes in sovereign bond yields and individual bank equity price changes since 2000. We extract some stylized facts from this network of asset price correlations and document the clear differences in asset price correlations between safe havens and non-safe havens: safe havens, as commonly defined, have higher sovereign-sovereign, bank-bank, and bank-sovereign correlations than nonsafe havens. In a simple shock propagation model, we illustrate how these higher correlations may turn safe havens into shock propagators. While we discuss safe havens as a group, we document how the US is in a category of its own, differing significantly from the other countries including Switzerland or Japan. Separately, we find that feedback loops amplify shocks, and those emanating from bank stress more than those emanating from sovereign stress. JEL Classification Numbers: F3, F650, G1

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