A new statistic and practical guidelines for nonparametric Granger causality testing

By Cees G. H. Diks, Valentyn Panchenko. 2006

959 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/94d66d1e1597e19e78d666c312c50bfa9481327a

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Citations in the corpus

The electricity consumption versus economic growth of the Polish economy (2012, methodology): “We decided to use some typical values of the technical parameters of this method, which have been commonly used in previous papers (e.g. Diks and Panchenko, 2005, 2006; 5 The technical details of resampling procedure applied in our bootstrap research may be found in Hacker and Hatemi (2006).”
Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach (2017, background): “Note that, while other nonparametric tests of causality are available in the literature (for example, Hiemstra and Jones (1994), and Diks and Panchenko (2005, 2006)), our decision to use the Nishiyama et al. (2011) test emanates from the fact that, unlike the other tests which can only detect…”
The relationship between crude oil spot and futures prices: cointegration, linear and nonlinear causality (2008, methodology): “lX=lY=1, if en 1⁄4 Cn b CN0; 1 bbb 1 then Diks and Panchenko (2006) prove under strong mixing For 4 3 that the test statistic in Eq.”
Examining the dynamic relationship between spot and future prices of agricultural commodities (2010, methodology): “12 Considering that the null hypothesis of Granger non-causality can be rephrased in terms of conditional independence of two vectors X and Z given a third vector Y, Diks and Panchenko (2006) show that the Hiemstra and Jones test is sensitive to variations in the conditional distributions of X and Z”
Causal independence between energy consumption and economic growth in Liberia: Evidence from a non-parametric bootstrapped causality test (2012, methodology): “Third, parametric tests based on prediction errors will be sensitive only to causality in the mean, while higher order structure such as heteroskedasticity, will be ignored (see Diks and DeGoede, 2001; Diks and Panchenko, 2006).”
Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility (2018, methodology): “However, Diks and Panchenko (2006) illustrated that under certain variance conditions, the HJ test could cause over-rejection in nonparametric tests for nonlinear Granger causality, and they proposed the DP test.”
Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests (2015, methodology): “8 We also apply the Diks and Panchenko (2005) nonlinear bivariate method but do not provide the results as they are very similar to those of Hiemstra and Jones (1994). They are available from the authors on request.”
Does twitter predict Bitcoin? (2019, methodology): “From these VAR models, we employ the linear Granger causality test (Granger 1969) as well as the nonlinear causality test of Diks and Panchenko (2006).”
The CO2-Growth nexus revisited: A nonparametric analysis for G7 economies over nearly two centuries (2017, positive): “In order to test the robustness of the causality analysis, we have applied the Diks and Panchenko (2006) causality test and the results are provided in Table 7.”