Dear Stata users,
I would appreciate it if someone could help me with a VECM interpretation and some suggestions to eliminate serial correlation. I have attached some results. The model has 4 variables: reer, pricecop, reserve and tb. The first three are non-stationary, but tb is stationary. I am not entirely sure if I can use a VECM in this case, but I did anyway. If I interpreted the results correctly, then the short-run adjustment parameters are significant for every variable except for pricecop. I am not sure what the ‘omitted’ in the last table means. Does it mean that there is a long-run relationship between reer and reserve and pricecop and reserve? The postestimation tests show that there is serial correlation in the residuals. I increased the number of lags, but nothing changed. Could it be because the sample size is too small? The model doesn’t seem misspecified.
Thank you.
I would appreciate it if someone could help me with a VECM interpretation and some suggestions to eliminate serial correlation. I have attached some results. The model has 4 variables: reer, pricecop, reserve and tb. The first three are non-stationary, but tb is stationary. I am not entirely sure if I can use a VECM in this case, but I did anyway. If I interpreted the results correctly, then the short-run adjustment parameters are significant for every variable except for pricecop. I am not sure what the ‘omitted’ in the last table means. Does it mean that there is a long-run relationship between reer and reserve and pricecop and reserve? The postestimation tests show that there is serial correlation in the residuals. I increased the number of lags, but nothing changed. Could it be because the sample size is too small? The model doesn’t seem misspecified.
Thank you.