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How to determine the optimal lag length from a Var?
In the paper, the author estimated a VAR to determine the optimal lag length based on the Schwartz Criterion. Then later in the paper the author estimated a Vector Error Correction Model for men and women. For men, the error correction terms had two lags while for women it is three lags for the error correction terms.
Which is better a VaR or a VECM model?
The advantage of VECM over VAR is that the resulting VAR from VECM representation has more efficient coefficient estimates. In order to fit a VECM model, we need to determine the number of co-integrating relationships using a VEC rank test.
Why does VECM impose additional restriction on data?
VECM imposes additional restriction due to the existence of non-stationary but co-integrated data forms. It utilizes the co-integration restriction information into its specifications. After the cointegration is known then the next test process is done by using error correction method.
Is the critical value of λmax higher than VECM?
The test output reports the results for the λmax statistics which does not differ much from trace statistic; the critical value (29.28) is still higher than test statistic. We will still go ahead and estimate VECM, since it can still valuable for short-run dynamics in absence of co-integration.
How to control the number of lags in VECM?
For that you can use function VARselect from the same package vars. Function cajorls does not have the argument K. However it has the argument r, which denotes cointegration rank. Argument K in function ca.jo controls the number of lags of VEC model.
How to calculate the cointegration rank in VEC?
Determine the cointegration rank using the function ca.jo. Pass the number of lags found in the first step as argument K. Fit VEC model using the cointegration vectors determined from the second step. This is performed by function cajorls, where you should pass the result of ca.jo and the number of cointegration vectors.
How is the error correction term included in the equation?
Finally, the error correction term is included in each equation of the VECM only once. It is either lagged by one or by p where p is the lag order of the VECM; the corresponding representations of the VECM are known as long-run and transitory; it is still the same model, just different representations — pick the one you like.