(Stata13): VECM Estimation, Discussion and Diagnostics
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 Published On May 30, 2018

So, what do you understand by vector error correction model (VECM)? You may say any of the following: that it is a system having a vector of two or more variables that all the variables in a VECM are endogenous there are no exogenous variables VECM is constructed only if the variables are cointegrated cointegration implies evidence of a long-run relationship among the variables it is a restricted VAR model with cointegrating restrictions built into the specification constructed to examine long- and short-run dynamics of the cointegrated series restricts the long-run behaviour of endogenous variables to converge to their cointegrating relationships that the cointegrating term is known as the error correction term it is a representation of cointegrated VAR (courtesy of granger’s representation theorem) and that the resulting VAR from VECM representation has more efficient coefficient estimates. Also, note that VAR specified in differences is a mis-specification while VECM is obtained by differencing a VAR, hence losing a lag. So, you construct a VECM with a (p-1) lag lengths for all the variables in the system. These are the basic steps required to estimating a VECM. (1) series must be stationary (integrated of same order) (2) determine optimal lag length for the model (3) perform Johansen cointegration test (4) if there is no cointegration, estimate the unrestricted VAR model (5) but if there is cointegration, then specify the restricted VAR model (i.e. VECM). In this video using Stata13, I show you the rudiments of the VECM specification. Kindly check my channel and playlist for all simple and exciting hands-on tutorials using EViews, Stata and Excel applications.

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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