Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI re...

Granger (Granger, C.W.J., 1969. Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37, 424–438.) defined causality between two variables X and Y in terms of predictability. A difficulty with this definition is that it is restricted to one-step ahead prediction. In the presence of a third environment variable Z the non-causality properties depend on the...

The causal notions embodied in the concept of Granger causality have been argued to belong to a different category than those of Judea Pearl’s Causal Model, and so far their relation has remained obscure. Here, we demonstrate that these concepts are in fact closely linked by showing how each relates to straightforward notions of direct causality embodied in settable systems, an extension and re...

of the Paper: Using time-series and panel data from 1986 to 2004, this paper examines the Granger causality relations between GDP, exports, and FDI among China, Korea, Taiwan, Hong Kong, Singapore, Malaysia, Philippines, and Thailand, the eight rapidly developing East and Southeast Asian economies. After reviewing the current literature and testing the properties of individual time-series data,...

Brain effective connectivity aims to detect causal interactions between distinct brain units and it is typically studied through the analysis of direct measurements of the neural activity, e.g., magneto/electroencephalography (M/EEG) signals. The literature on methods for causal inference is vast. It includes model-based methods in which a generative model of the data is assumed and model-free ...

This study is to investigate the short- and long-run causal relationship between agglomeration (localization and urbanization) economies and labor productivity in the manufacturing sector of 28 Iranian provinces over an 11-year period, 2001–2011. Fully Modified Ordinary Least Squares (FMOLS) method was used to estimate our long-run panel data model. The empirical findings suggested that localiz...

Granger causality is becoming an important tool for determining causal relations between neurobiological time series. For multivariate data, there is often the need to examine causal relations between two blocks of time series, where each block could represent a brain region of interest. Two alternative methods are available. In the pairwise method, bivariate autoregressive models are fit to al...