**4.4 VAR residual serial correlation LM tests**


Before the estimation of the Causality Test, Forecast Error Variance Decomposition (FEVD) and Impulse Response Functions (IRFs). The VAR residual serial correlation test is needed to verify the adequacy of the lag selection criterion used in

*\*indicates lag order selected by the criterion. LR: sequential modified LR test statistic (each test at 5% level), FPE: Final prediction error, AIC: Akaike information criterion, SC: Schwarz information criterion and HQ: Hannan-Quinn information criterion. Source: E-views Version 9 software was used in the estimation.*

#### **Table 4.** *VAR lag order selection criteria.*

*Impact of Oil Price Fluctuation on the Economy of Nigeria, the Core Analysis for Energy… DOI: http://dx.doi.org/10.5772/intechopen.94055*


## **Table 5.**

*Correlation matrix for TY-VAR.*


*Probs from chi-square with 16 df.*

*Source: Estimation was compiled using E-views Version 9 software.*

#### **Table 6.**

*TY-VAR residual serial correlation LM tests.*

the estimation of a chosen multivariate model, it is applied to test a set of restrictions on a model that is unrestricted, and it is based on the restricted maximum likelihood test (ML) [42, 60, 61]. From the TY-VAR estimated output for the residual serial correlation test in **Table 6**, the null hypothesis for the test is that there is no serial correlation. The result submits that there is no evidence of serial correlation. Which indicate the acceptance of the null hypothesis that the restriction (lags) place on the model is adequate.
