Discussion
Suppose \(Y_{i} = \alpha + \beta X_{i} + e_{i}\) is a linear regression model. Goldfeld-Quandt test is a test of :
Answer: C
The Goldfeld-Quandt test is a test of heteroscedasticity.
The observations are ordered by the variable thought to drive the error variance, a block of central observations is dropped, and separate regressions are fitted to the two ends. The ratio of their residual sums of squares, each divided by its degrees of freedom, follows an F distribution if the error variance is constant. A large ratio indicates heteroscedasticity.
Autocorrelation is tested with the Durbin-Watson or Breusch-Godfrey tests, and the correlation between X and Y is measured by the correlation coefficient, not by this test.
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