2. QUANTITATIVE ANALYSISTHE RESIDUALS ARE CALLED HETEROSCEDASTIC IF...

3. - ECONOMETRICS FINAL EXAM FACTORS AFFECTING QUANTITY OF NEW CARS SOLD FOREIGN TRADE UNIVERSITY STUDENTS 3. - ECONOMETRICS FINAL EXAM FACTORS AFFECTING QUANTITY OF NEW CARS SOLD FOREIGN TRADE UNIVERSITY STUDENTS
ECONOMETRICS FINAL EXAM FACTORS AFFECTING QUANTITY OF NEW CARS SOLD FOREIGN TRADE UNIVERSITY STUDENTS

3.2. Quantitative analysis

The residuals are called heteroscedastic if the residual variables have

different variances and homoscedastic if constant. White test is a statistical test that

establishes whether the residual variance of a variable in a regression model is

constant. The null hypothesis in White test is that the residuals are homoscedastic.

Figure 7.4: White test (squares only)(Source: Gretl)

Null Hypothesis: Ho : var ( ui) = σ

2

for all i

Alternative Hypothesis: H1: var (ui)# σ

2

for all i

The data table above shows that p-value = 0.635525 > = 0.05

For the common = 5% for the 2-tail test, we are able to give the conclusion

not to reject hypothesis Ho : var (ui ) = σ

2

for all i.

Conclusion: No heteroscedasticity is found.

Analysis:

While heteroscedasticity does not cause bias in the coefficient estimates, it

does make them less precise. Lower precision increases the likelihood that the

coefficient estimates are further from the correct population value. Our model is not

heteroscedastic, which means the preciseness of the coefficient is high.