Relationship between p-values and effect size I did a Wilcoxon signed rank test to understand whether there is a difference in average sales in 9 different counties. There are multiple pairs of counties that are significantly different.
Would it be fair in this case to say that p-values are representative of the effect size? i.e.: the pair with the lowest p-value differs the most in average sales?

In general, p values and effect size statistics address entirely different concepts.  I recommend keeping them entirely distinct in your mind.  ... You could devise circumstances where you keep e.g. the sample size and the hypothesis test the same, and that would make the p value related an effect size statistic.  But there's no reason to do this. You can simply calculate whatever effect size statistic you find informative. ...  For the signed rank test, the matched-pairs rank biserial correlation coefficient is good effect size statistic.  But if you wanted to present some other measure you could do that as well.
The signed rank test doesn't (directly) assess whether there is a difference in average sales.  If you are interested in the difference in average sales, I would recommend calculating this and presenting the results.  Likewise, you might be able to find an appropriate hypothesis test for the difference in average sales.
