What's My Employee Worth? Information Frictions, Pay, and Pay Equity
Determining the right salaries is of utmost importance for companies, as salaries often represent the largest expenditure. On the one hand, paying salaries that are too high can be wasteful. On the other hand, paying salaries that are too low can make it difficult to attract, motivate and retain employees. How do employers find the sweet spot? This project seeks to enhance our understanding of how companies determine their employees' compensation. The project has two parts. The first part studies the use of aggregated market data to set salaries, a practice that is known as salary benchmarking. Despite their pervasiveness, salary benchmarking tools rarely make their way into public view and have not been studied by economists. The researchers provide theoretical and empirical evidence on the effects of salary benchmarking on compensation. The second part of the project studies the gender pay gap. Companies are showing growing interest in narrowing the gender pay gaps within their workforce. This interest has created a whole industry around pay-equity consulting. The researchers study pay equity tools. These are data analytics tools that use an employer's payroll data to identify gender pay disparities in the workforce. For instance, an employer might discover that among its bank tellers, female tellers on average earn 90% of what their male counterparts make. The researchers explore whether the use of these pay equity tools indeed helps in reducing the gender pay gap. The project seeks to make significant contributions to the field of labor economics. Moreover, the findings can have far-reaching consequences for policies related to salary benchmarking, pay transparency and fair pay.
The researchers employ theoretical models to understand how firms use salary benchmarking and pay equity tools. These models make predictions about the impact of these tools on outcomes such as employee pay and turnover. The researchers then test those hypotheses with multiple sources of data and identification strategies. To document pay practices and policies, the investigators design and conduct tailored surveys with Human Resources executives. Most importantly, the researchers capitalize on a partnership with the largest payroll processing company in the United States. This company offers state-of-the-art salary benchmarking and pay equity tools. The researchers leverage rich sources of administrative data. For instance, they use payroll records spanning millions of employees and thousands of firms. Additionally, they leverage data on how employers utilize benchmarking and pay equity tools in their daily operations. To identify the causal effects of these tools, the researchers exploit multiple identification strategies. The investigators leverage quasi-experimental sources of variation. For instance, they use a differences-in-differences design that leverages the staggered adoption of the tools across different companies. In a nutshell, this strategy compares the evolution of the outcomes right before and right after the company adopts the tool. In addition to the non-experimental data, the investigators design and conduct field experiments to create exogenous variation in the usage of the tools.
Supported by the National Science Foundation grant #2242542
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