The Granger Non-Causality Test in Cointegrated Vector Autoregressions

In general, Wald tests for the Granger non-causality in vector autoregressive (VAR) process are known to have non-standard asymptotic properties for cointegrated systems. However, that may have standard asymptotic properties depending on the rank of the submatrix of cointegration. In this paper, we propose a procedure for conducting Granger non-causality tests that are based on discrimination of these asymptotic properties. This paper also investigate the finite sample performance of our testing procedure, and compare the testing procedure with conventional causality tests in levels VARfs.Vector autoregression, Cointegration, Granger causality, Hypothesis testing

Simulation Evidence on Granger Causality in Presence of a Confounding Variable

This paper provides simulation evidence on Granger causality between two variables when they are jointly caused by a third variable. Four Data Generating Processes (DGPs) are considered for testing causality by Granger method and two DGPs for testing causality by Toda and Yamamoto (1995) procedure. Our simulation involve three variables but causality has been tested only between two variable and the third variable (the real cause) has been ignored to show that its association which matters in these causality tests. Nevertheless, if we know that there are only two variables in economic dynamics and the true model is known then these causality tests work fine and for this we have carried out bootstrap simulation.Granger Causality, Toda and Yamamoto Procedure, Monte Carlo Simulation, Causation and Association, Bootstrap Simulation

A Consistent Nonparametric Test for Causality in Quantile

This paper proposes a nonparametric test of causality in quantile. Zheng (1998) has proposed an idea to reduce the problem of testing a quantile restriction to a problem of testing a particular type of mean restriction in independent data. We extend Zheng’s approach to the case of dependent data, particularly to the test of Granger causality in quantile. The proposed test statistic is shown to have a second-order degenerate U-statistic as a leading term under the null hypothesis. Using the result on the asymptotic normal distribution for a general second order degenerate U-statistics with weakly dependent data of Fan and Li (1996), we establish the asymptotic distribution of the test statistic for causality in quantile under ß-mixing (absolutely regular) process.Granger Causality, Quantile, Nonparametric Test

Bootstrap Panel Granger-Causality Between Government Spending and Revenue

Using bootstrap panel analysis, allowing for cross-country correlation, without the need of pre-testing for unit roots, we study the causality between government revenue and spending for the EU in the period 1960-2006. Spend-and-tax causality is found for Italy, France, Spain, Greece, and Portugal, while tax-and-spend evidence is present for Germany, Belgium, Austria Finland and the UK, and for several EU New Member States.panel causality; fiscal policy; EU.

Temporal Aggregation, Causality Distortions, and a Sign Rule

Temporally aggregated data is a bane for Granger causality tests. The same set of variables may lead to contradictory causality inferences at different levels of temporal aggregation. Obtaining temporally disaggregated data series is impractical in many situations. Since cointegration is invariant to temporal aggregation and implies Granger causality this paper proposes a sign rule to establish the direction of causality. Temporal aggregation leads to a distortion of the sign of the adjustment coefficients of an error correction model. The sign rule works better with highly temporally aggregated data. The practitioners, therefore, may revert to using annual data for Granger causality testing instead of looking for quarterly, monthly or weekly data. The method is illustrated through three applications.Granger causality test, cointegration, error correction model, adjustment coefficient, sign rule

Immigration, Unemployment and Growth in the Host Country: Bootstrap Panel Granger Causality Analysis on OECD Countries

This paper examines the causality relationship between immigration, unemployment and economic growth of the host country. We employ the bootstrap panel Granger causality testing approach of Kónya (2006) that allows to test for causality on each individual country separably by accounting for dependence across countries. Using annual data over the period 1980-2005 for 22 OECD countries, we find that, only in Portugal, unemployment negatively causes immigration, while in any country, immigration does not cause unemployment. We also find that, in France, Iceland, Norway and United Kingdom, growth positively causes immigration, while in any country, immigration does not cause growth.immigration, growth, unemployment, Granger causality

Electricity consumption and GDP in an electricity community: Evidence from bound testing cointegration and Granger-causality tests

This study probes nexus between electricity consumption and GDP for the electricity community of Togo and Benin using ARDL bounds testing approach of cointegration. Long-run equilibrium has been established among these variables for Benin. The study further establishes long- and short-run Granger causality running from GDP to electricity consumption for Benin and short-run Granger causality running from GDP to electricity consumption for Togo. The results of the cointegration test and the causality reflect better the Benin and Togo economies that are less dependent on electricity. The absence of causality running from electricity consumption to GDP implies that electricity demand side management measures can be adopted to reduce the wastage of electricity, which would not affect future economic growth in the community.ARDL, cointegration, causality, growth, electricity

Bootstrap panel Granger-causality between government spending and revenue in the EU

Using bootstrap panel analysis, allowing for cross-country correlation, without the need of pre-testing for unit roots, we study the causality between government revenue and spending for the EU in the period 1960-2006. Spend-and-tax causality is found for Italy, France, Spain, Greece, and Portugal, while tax-and-spend evidence is present for Germany, Belgium, Austria, Finland and the UK, and for several EU New Member States.panel causality, fiscal policy, EU.