(EViews10): ARDL and 3-Ways Causality Checks (2) #ardl #causality #granger #wald #boundstest
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 the ARDL framework and interpret the results. Here is the link to the cam.xlsx dataset used for this tutorial (endeavour to have a Google account for easy accessibility): https://drive.google.com/drive/u/1/fo... Follow up with soft-notes and updates from CrunchEconometrix: Website: http://cruncheconometrix.com.ng Blog: https://cruncheconometrix.blogspot.co... Forum: http://cruncheconometrix.com.ng/blog/... Facebook: / cruncheconometrix YouTube Custom URL: / cruncheconometrix Stata Videos Playlist: • (Stata13):Estimate and Interpret Two-way A... EViews Videos Playlist: • (EViews10):Interpret VECM, Forecast Error ...

(EViews10): ARDL and 3-Ways Causality Checks (1) #ardl #causality #granger #wald #boundstest

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(EViews10):VAR and 4-Ways Causality Checks(2) #var #vecm #causality #granger #wald #Johansen

(EViews10):VAR and 4-Ways Causality Checks(1) #var #vecm #causality #granger #wald #Johansen

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(EViews10): VECM and 3-Ways Causality Checks (2) #var #vecm #causality #granger #wald #Johansen

(EViews10): VECM and 3-Ways Causality Checks (1)#var #vecm #causality #granger #wald #Johansen

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(Stata13): VAR and 3-Ways Causality Checks (2) #var #vecm #causality #granger #wald #Johansen

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(EViews10): ARDL-VECM and Causal Inference #ardl #ecm #causality #granger #wald #boundstest

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(EViews10):Discussing Results, VAR Models(2) #var #vecm #Johansen #normality #serialcorrelation

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