Essays in Econometrics
DOI: 10.1017/cbo9780511753978.002
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Investigating Causal Relations by Econometric Models and Cross-Spectral Methods

Abstract: INVESTIGATING CAUSAL RELATIONS BY ECONOMETRIC MODELS AND CROSS-SPECTRAL METHODS There occurs on some occasions a difficulty in deciding the direction of causality between two related variables and also whether or not feedback is occurring. Testable definitions of causality and feedback are proposed and illustrated by use of simple two-variable models. The important problem of apparent instantaneous causality is discussed and it is suggested that the problem often arises due to slowness in recording information… Show more

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Cited by 3,390 publications
(3,793 citation statements)
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“…Ordinarily, if X and Y are two economic time series, X is said to Granger-cause Y if it can be shown, usually through a series of t-tests and F-tests on lagged values of X (and with lagged values of Y also included), that those X values provide statistically significant information about future values of Y. The Granger (1969) model, based on the following bivariate VAR models, is used in this paper to estimate the casual relationship between time series (Feng et al, 2009):…”
Section: Granger Causality Testsmentioning
confidence: 99%
“…Ordinarily, if X and Y are two economic time series, X is said to Granger-cause Y if it can be shown, usually through a series of t-tests and F-tests on lagged values of X (and with lagged values of Y also included), that those X values provide statistically significant information about future values of Y. The Granger (1969) model, based on the following bivariate VAR models, is used in this paper to estimate the casual relationship between time series (Feng et al, 2009):…”
Section: Granger Causality Testsmentioning
confidence: 99%
“…Wiener-Granger causality (G-causality) (Granger, 1969;Geweke, 1982Geweke, , 1984 is an increasingly popular method for identifying "causal" connectivity in neural time series data (Bressler and Seth, 2011). It can be traced conceptually to Wiener (Wiener, 1956) and was operationalised by Granger in terms of linear autoregressive modelling of stochastic processes (Granger, 1969).…”
Section: Introductionmentioning
confidence: 99%
“…It can be traced conceptually to Wiener (Wiener, 1956) and was operationalised by Granger in terms of linear autoregressive modelling of stochastic processes (Granger, 1969). G-causality is based on predictability and precedence.…”
Section: Introductionmentioning
confidence: 99%
“…These not only take into account the correlation structure within and between the observed time series, but they also allow use of the 'arrow of time' to devise influence measures to statistically assess causality as introduced by Granger and co-workers (Granger, 1963(Granger, , 1969(Granger, , 1980Granger and Lin, 1995). Granger reasoned thus: if time series x t is influencing y t then adding past values of x t to the regression of y t will improve its prediction.…”
Section: Second Generation Influence Measures: Granger Causalitymentioning
confidence: 99%
“…Based on these definitions, Granger introduced the following (linear) influence measure (Granger, 1969):…”
Section: Second Generation Influence Measures: Granger Causalitymentioning
confidence: 99%