(EViews10): VECM and 3-Ways Causality Checks (1)

Описание: A statement such as “X causes Y” will have the following meaning in different scenarios and disciplines such as X leads Y, X is the only cause of Y, X is only one of the possible causes of Y, X must always lead to Y (that is X determines Y), the occurrence of X makes the occurrence of Y more probable, X is a probabilistic cause of Y, X must occur either before or simultaneously with Y, but not afterwards, past values of X forecasts future values of Y. But Regression analysis deals with the dependence of one variable on other variables, it does not necessarily imply causation. In other words, the existence of a relationship between variables does not prove causality or the direction of influence. But in regressions involving time series data, the situation may be somewhat different. Short-run causal effects: through the F-statistics and the statistical significance of the regressors. Long-run causal effects: through the statistical significance error-correction term (applicable to VECM only). Joint causal effects: through the F-statistics and the significance of the independent variables and the statistical significance error-correction term (applicable to VECM only). Unidirectional causality: occurs from X to Y if the set of estimated coefficients of the lagged X are significantly different from zero and the set of estimated coefficients of lagged Y are not significantly different from zero. Bi-directional causality: occurs from X to Y if the set of estimated coefficients of the lagged X are significantly different from zero and vice-versa. Independence: occurs from Y (X) to X (Y) if the set of estimated coefficients of the lagged Y (X) are not significantly different from zero. Using EViews10, this video shows you how to perform causality tests in four different ways within a VECM framework and interpret the results.

Here is the link to the ex21-1.wf1 dataset (EViews file) used for this tutorial (endeavour to have a Google account for easy accessibility): https://drive.google.com/drive/u/1/fo...

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