Try different lag lengths.

@Shimelis Kebede is there any criteria to choose the lag length?

Dear Abhishek

I suggest to review the explanatory variables. There may be some collinearity but near-perfect collinearity is usually the signal of an error in that matrix (being yourself the culprit)

Use Schwarz' Bayesian Information Criterion(SBIC) to determine the statistically significant number of lags, when using VAR modelling.  

I agree with Carlos R. Barrera-Chaupis, you should check explanatory variable whether there are any multicollinearity. In addtition, you should also cautious at dummy variables that may cause "dummy traps"

you can run this with rats software. in the rats, you can choice the various method of lag such as AIC, BIC

also You can change the lag at the start of the estimate in eviews .

I also concur with the submission of Carlos. There might be element of multicolleaniarity within the explanatory variables.