Estimation of a VEC model in R (standard errors) Estimating a Vector Error Correction Model (VECM) in R can be done by using the command cajorls. The R output consists of the coefficients of the Error Correction Terms and the values of the coefficients on the lagged variables used in the VECM, together with the "Betas". When using two variables, we are getting a bivariate model.
My questions:


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*Although all the coefficients necessary to build the VECM are getting calculated by R, there are no standard errors or respective p-values reported in the R output. In R, is there a command that lets you compute the standard errors of the coefficients on the error correction terms (ECT)?

*Is it correct that the coefficients on the ECT describe the long-run relationship between the two variables in a mathematical way (the sign tells you what variables is "dominant")?
 A: 
Although all the coefficients necessary to build the VECM are getting calculated by R, there are no standard errors or respective p-values reported in the R output. In R, is there a command that lets you compute the standard errors of the coefficients on the error correction terms (ECT)?

An indirect way would be to manually specify the particular equation (having defined the appropriate lags of variables and the error correction term first) and estimate it with the lm function.

Is it correct that the coefficients on the ECT describe the long-run relationship between the two variables in a mathematical way (the sign tells you what variables is "dominant")?

The coefficient on the ECT in an equation of the VECM quantifies the impact of the error correction term on the particular dependent variable (just as any regression coefficient in a linear model). The sign shows whether there is "error correction" (so that the variable corrects towards eqquilibrium) or "error inflation" (just made this term up; so that the variable deviates further from the equilibrium). I am not sure if the latter makes sense, but empirically the coefficients might occasionally have funny signs like that. 
If some of the variables have coefficients that are indistinguishable from zero, then those are "dominant" in the sense that they do not adjust towards the equilibrium; rather, they "drive" the system of variables. But there must be some other variables in the system that do adjust, and these ones are "dominated". (If none of the variables adjusted towards the equilibrium, there would be no cointegration.)
On the other hand, the coefficients on the variables inside the error correction term describe the long-run equilibrium relationship.
