Granger causality revisited

This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality - providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes - as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling

Money-output Granger causality revisited: An empirical analysis of EU countries

In this paper, the evidence collected in the large literature on testing for Granger-causality from money to output is revisited. Using a broad data base of 14 EU-countries plus Canada, the US and Japan, and quarterly data from the mid 60s to the mid 90s, a number of hypotheses from this literature is evaluated. It is found that very few general conclusions can be sustained. For instance, in most countries it is not the case that the use of data in levels creates a bias in favour of finding Granger-causality effects of money on output compared to using differences. Neither does the significance of money lags decline when increasing the number of variables included in the model. What appears to be robust, though, is that allowing for asymmetries clearly increases the likelihood of finding significant causality effects. Based on the Grangercausality test results, a number of country groups are obtained using cluster analysis, which are characterised by a similar behaviour with respect to the money-output relation. --Money-Output Causality,Granger Causality,EU countries

The economic impact of electricity conservation policies: A case study of Ireland

As electricity is an essential input in almost every production process, it is essential to quantify the impact of economic policies aimed at electricity conservation on the output. This research investigates the e®ect of unanticipated shocks in electricity consumption, technical e±ciency, and electricity price on the value added in the heterogenous service and industrial sectors, under a demand side model. Ireland is utilized as a case study as it is pursuing ambitious electricity conservation targets while in the midst of a severe economic recession. Given the important role of electricity as an input in both the services and industrial sectors, it was feared that these energy conservation targets may adversely impact on these sectors and as a result worsen the national economic situation. Findings show that value added, electricity consumption, electricity price and technical e±ciency are co-integrated for both the service and industrial sectors. However, impulse response functions show that positive technical e±ciency and consumption shocks have persistent negative e®ects on the value added of both sectors. Therefore, a direct electricity conservation policy, that puts a constraint on electricity consumption, should not have an adverse e®ect on sector speci¯c value added.Electricity consumption, Value added, Granger Causality, Impulse response

Gelişmekte olan piyasalarda enerji tüketimi ve büyüme ilişkisinin panel kantil regresyon ile incelenmesi: VISTA ülkeleri örneği

Energy consumption and economic growth relationship is an important topic for global economy. Most of researchers investigated this relationship with different methods on different macro-economic data. These methods are including not only time-series econometrics but also panel data analysis. Moreover, they analyzed different countries or country groups classified by OECD, World Bank or any other economic organizations. The aim of study is the relationship between energy consumption and economic growth with panel quantile regression method on VISTA countries (Vietnam, Indonesia, South Africa, Turkey and Argentina). Estimations are made annually for 1985 – 2013 period. Dependent variable is GDP per capita growth and independent variables are logarithmic energy consumption indicators which are Oil Consumption, Coal Consumption, Hydroelectricity Consumption and Primary Energy Consumption. Results show that the effects of logarithmic energy consumption variables are changing on economic growth for different quantiles (τ = 0.25; 0.50; 0.75; 0.90). In conclusion, effect of oil consumption on economic growth is falling at high quantiles of GDP growth. In contrast, effect of hydroelectricity consumption and primary energy consumption on economic growth is rising at high quantiles. But, there is not a statistical significant effect of coal consumption on economic growth at any quantile

Macroeconomic Convergence in the East African Community: A Multivariate Cointegration Analysis of the Exchange Rates

The EAC member countries have to-date implemented various reforms with the aim of achieving macroeconomic convergence before the on-coming EAST African Monetary Union, however, the extent of convergence to-date is an empirical question that is yet to be answered.  Various researchers have used the Johansen approach to investigate cointegration but have not catered for the gradual changes that occur during the adjustment period.  This study revisited the definition of convergence based on Johansen cointegration approaches to include zero mean, conditional deterministic, stochastic, conditional and unconditional stochastic convergence; and unlike other studies, applied a rolling multivariate cointegration/convergence approach to investigate the extent to which exchange rates in the East African Community (EAC) have converged following macroeconomic reforms.   Rolling Johansen, rolling multivariate Engle and Granger, impulse response and Granger-causality approaches were applied.  The results revealed that existence of cointegration does not necessarily mean complete convergence. Although the exchange rates in the EAC were cointegrated, there was limited convergence and uni-directional causality in most cases.  The shocks arising from Kenya had major effects on the exchange rates for other countries in the region; those from Rwanda affected that for Burundi while shocks arising elsewhere had minimal effects.  To ensure smooth transitions in the monetary union, reforms that can ensure convergence thus stable exchange rates are required. Keywords: Macro-economic convergence, Multivariate rolling cointegration tests, Exchange rates, Granger-causality,   East African Community integration JEL Nos. C32, E52, E61, E63, F1

Energy consumption and aggregate income in Italy: cointegration and causality analysis

The aim of this article is to assess the empirical evidence of the nexus between aggregate income and energy consumption for Italy during the period 1970-2009, using a time-series approach. After a brief introduction, a survey of the economic literature on this issue is shown, before discussing the data and intro-ducing some econometric techniques. Stationarity tests reveal that both series are non-stationary, or I(1). Moreover, we found a cointegration relationship between the two variables. The short-run dynamics of the variables show that the flow of causality runs from energy use to GDP, and there is a long-run bi-directional causal relationship (or feedback effect) between the two series. Consequently, we conclude that energy is a limiting factor to GDP growth in Italy.Energy policies; energy consumption; GDP; stationarity; cointegration; causality; Italy

Military spending and economic growth in China: a regime-switching analysis

This article has been made available through the Brunel Open Access Publishing Fund.This article investigates the impact of military spending changes on economic growth in China over the period 1953 to 2010. Using two-state Markov-switching specifications, the results suggest that the relationship between military spending changes and economic growth is state dependent. Specifically, the results show that military spending changes affect the economic growth negatively during a slower growth-higher variance state, while positively within a faster growth-lower variance one. It is also demonstrated that military spending changes contain information about the growth transition probabilities. As a policy tool, the results indicate that increases in military spending can be detrimental to growth during slower growth-higher growth volatility periods. © 2014 © 2014 The Author(s). Published by Taylor & Francis