## Example 112

RELATIONSHIP BETWEEN COMPENSATION AND PRODUCTIVITY: THE GLEJSER TEST

Continuing with Example 11.1, the absolute value of the residuals obtained from regression (11.5.3) were regressed on average productivity (X), giving the following results:

|&H = 407.2783 - 0.0203X, se = (633.1621) (0.0675) r2 = 0.0127 (11.5.5)

As you can see from this regression, there is no relationship between the absolute value of the residuals and the regressor, average productivity. This reinforces the conclusion based on the Park test.

Spearman's Rank Correlation Test. In exercise 3.8 we defined the Spearman's rank correlation coefficient as rs = 1-6

where di = difference in the ranks assigned to two different characteristics of the ith individual or phenomenon and n = number of individuals or phenomena ranked. The preceding rank correlation coefficient can be used to detect heteroscedasticity as follows: Assume Yi = ¡¡0 + ¡1 Xi + ui.

Step 1. Fit the regression to the data on Y and X and obtain the residuals 