Predictive validity of selection tools: The critical role of applicant-pool composition

Worldwide, trends of globalization, demographic changes, and rising social mobility are modifying the composition of the pools of applicants competing for jobs, educational places, and other opportunities for which selection tools are used. This study investigates the impact of changes in applicant-pool composition (operationalized as the proportion of a focal group within the applicant pool, p) on the predictive validity of a selection tool (r). We demonstrate that there is a direct relationship between p and r that is shaped by several parameters identified by a proposed equation. To investigate this relationship in the field, we conducted an empirical study based on more than 130,000 observations gathered from a real-life, high-stakes selection context. The results indicate that, under certain conditions, a given change in p can have a beneficial effect on r, whereas, under different conditions, it has a detrimental effect. Furthermore, the results suggest that the proposed equation can be used to explain the performance of a selection tool, under real conditions in the field, where the simplifying assumption underlying the proposed equation does not always hold. The present findings will enable decision-makers to explore the possible impact of anticipated changes in applicant-pool composition on the predictive validity of their selection tools, helping them make better informed decisions regarding the best one to use. Additional practical implications involve explaining differences between the predictive validity of different selection tools, or variations in the predictive validity of one particular tool depending on country, year, academic discipline, or occupation, for instance. (PsycInfo Database Record (c) 2026 APA, all rights reserved).