# Numerical Example: Goldfeld-Quandt Test

Data is taken from the Economic Survey of Pakistan 1991-1992. The data file link is at the end of this numerical example of the Goldfeld-Quandt Test.

For an illustration of the Goldfeld-Quandt test, data given in the file should be divided into two sub-samples after dropping (removing/deleting) the middle five observations.

Sub-sample 1 consists of data from 1959-60 to 1970-71.

Sub-sample 2 consists of data from 1976-77 to 1987-1988.

The sub-sample 1 is highlighted in green colour, and sub-sample 2 is highlighted in blue color, while the middle observation that has to be deleted is highlighted in red.

The Step by Step procedure to conduct the Goldfeld-Quandt test is:

Step 1: Order or Rank the observations according to the value of $X_i$. (Note that observations are already ranked.)

Step 2: Omit $c$ central observations. We selected 1/6 observations to be removed from the middle of the observations.

Step 3: Fit OLS regression on both samples separately and obtain the Residual Sum of Squares (RSS) for each sub-sample.

The Estimated regression for the two sub-samples are:

Sub-sample 1: $\hat{C}_1 = 1010.096 + 0.849 \text{Income}$

Sub-sample 2: $\hat{C}_2 = -244.003 + 0.88067 \text{Income}$

Now compute the Residual Sum of Squares for both sub-samples.

Residual Sum of Squares for Sub-Sample 1 is $RSS_1=2532224$

Residual Sum of Squares for Sub-Sample 2 is $RSS_2=10339356$

The F-Statistic is $\lambda=\frac{RSS_2/n_2}{RSS_1/n_1}=\frac{10339356}{2532224}=4.083$

The critical value of $F(n_1=10, n_2=10$ at 5% level of significance is 2.98.

Since the computed F value is greater than the critical value, heteroscedasticity exists in this case, that is, the variance of the error term is not consistent, rather it depends on the independent variable, GNP.

Your assignment is to perform this Numerical Example of the Goldfeld-Quandt test using any statistical software and confirm the results. 