The Preventive Pay Equity Audit: Guidance for Modeling the Regression Analysis
Sarkar, D., Haverstick, A.D.
D Sarkar, AD Haverstick - ABAJ Lab. & Emp. L., 2010 - HeinOnline
Summary
"The Preventive Pay Equity Audit: Guidance for Modeling the Regression Analysis" by Sarkar and Haverstick, published in 2010, serves as a practical guide for employers undertaking pay equity audits with a focus on prevention. The paper centers on the methodology of using regression analysis as a statistical tool to identify and address potential pay disparities. It delves into the essential statistical concepts relevant to such an audit, aiming to equip practitioners with the knowledge required for accurate analysis. The authors advocate for a careful and nuanced approach to modeling regression analyses, highlighting the importance of considering various details specific to each case when interpreting results. The implication of this guidance is to provide employers with a robust framework for proactively assessing their compensation structures to prevent discrimination, rather than merely reacting to it. The paper suggests that while complex statistical models may offer deeper insights, there might be strategic reasons for organizations, particularly for compliance purposes, to opt for more straightforward modeling approaches. This pragmatic advice underscores the challenges of balancing statistical rigor with practical applicability and regulatory expectations in the field of pay equity. The emphasis on prevention indicates the paper's value in fostering fair compensation practices and mitigating legal risks associated with pay discrimination.
Key Findings
- - The paper provides guidance for employers on conducting preventive pay equity audits using statistical methods, particularly regression analysis.
- It highlights key statistical concepts necessary for understanding and performing an effective pay equity audit.
- Authors recommend a cautious approach to interpreting regression analysis results, stressing the need to consider specific case details.
- For compliance purposes, organizations may have reasons to opt for more simplistic regression models.