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

(EViews10): Estimate and Interpret VECM (1) #var #vecm #causality #lags #Johansen #innovations

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

Why Aliens Would NEVER Invade Africa

Trump Gets Booed & Falls Asleep During NBA Finals, Claims War is Almost Over & Goodbye Spencer Pratt

Ex-Google Recruiter Explains Why "Lying" Gets You Hired

How to Answer ANY Question (Even If You Don't Know The Answer!)

13. Vector Error Correction Model (VECM) using EViews || Dr. Dhaval Maheta

Intro to Hypothesis Testing in Statistics - Hypothesis Testing Statistics Problems & Examples

Trump Sells UFC Coins as Iran Strikes & Melania Pushes AI in a Speech Worthy of AI | The Daily Show

X+Y (Clip) - Nathan solves math problem | Pinnacle Films

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

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

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

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

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

Estimating a VAR(p) in EVIEWS

Granger Causality : Time Series Talk

