Competition and Equal Pay Policy: Experimental Evidence

2023-09-21

2023-10-05

The main outcome of interest is how an equal pay policy impacts the percentage of minority workers being hired and the wage dispersion between the minority and majority workers.

We will compare the percentage of hired minority candidates and the average wage gap between minority and majority candidates in both Treatment 1 (Ind_Flex) and Treatment 2 (Ind_Fixed) to understand the overall effects of an Equal Pay Policy in a non-competitive market. Similarly, we will compare the percentage of hired minority candidates and the wage gap between minority and majority candidates in both Treatment 3 (Comp_Flex) and Treatment 4 (Comp_Fixed) to understand the overall effects of an Equal Pay Policy in a competitive market. The difference in treatment effects will identify the role of competition plays in the impact of an Equal Pay Policy.

The primary outcome can be broken down into three parts: 1) Impact on Hiring and Selection, 2) Impact on Wage Offers and Payments, and 3) Impact on the overall employment rate and wage payments in different competitive markets. For the first and second parts, we're interested in how the equal pay policy affects differences across ethnic and ability groups. We're operating under the assumption that managers believe the average ability of minority workers is lower than that of majority workers. For the third part, we are interested in to see how the equal pay policy impacts the overall employment rate and wage payments in different competitive markets.

(1) Hiring and Selecting Effect: Whether and how much the managers hire and select less minority and low-ability workers with the Equal Pay Policy
(2) Wage offering and paying effect: Whether and how much the managers pay less wage for the minority and low ability workers with the Equal Pay Policy
(3) Overall effect: Whether an increase in competition will not affect the overall employment rate but reduce the average wage for all hired workers with the Equal Pay Policy.
(4) Competition Effect: In a laissez-faire market, whether the increase in competition will increase the impact of an ability signal on wage, reduce the wage dispersion between majority and minority (Hirata & Soares, 2020), but reduce the hiring rate of minority workers (Lagerlöf, 2020).
(5) Sorting Effect: The sorting Effect measures the competition effect on the Equal Pay Policy. We are interested in with equal pay policy, whether an increase in competition will lead to a sorting effect that managers will hire only one ethnic type of workers in order to lower the wage cost (Lagerlöf, 2020).

This experiment consists of two phases: 1) the preliminary phase, in which we aim to recruit 150 participants to complete a series of anagram tasks; and 2) the main phase, in which we aim to recruit 44 participants for each of the four treatments to complete a hiring task (i.e., 176 participants in total).

In the preliminary phase, participants will be asked to complete five 2-minute anagram tasks individually and paid by piece-rate performance. This phase is designed to generate actual profiles of candidates to be used in the main phase of the experiment. The benefit of using actual profiles is to introduce real consequences for discriminatory behaviour and therefore capture the actual level of employer discrimination (Hedegaard & Tyran, 2018). To construct a balanced candidates pool for the second phase, 75 participants will be recruited from an ethnic minority group (i.e., East Asians) and the remaining 75 will be recruited from the ethnic majority group (i.e., Whites). Out of the five performances, we drop the lowest and the highest scores to form the final candidate profiles. And we randomly choose 2 scores from the rest of 3 scores remaining as the pre-performance score and interview performance score

In the main phase of the experiment, participants will undertake a manager's role to make hiring decisions, using a set of four pre-screened candidate profiles based on data from the preliminary phase. Each participant will be assigned to one of the following four experimental treatments: Individual-Flexible treatment - without the equal pay policy or hiring competition (Treatment 1), Individual-Fixed treatment - with an equal pay policy (requiring employers to offer the same wage to all chosen candidates) but without hiring competition (Treatment 2), Competition-Flexible treatment - with hiring competition (employers compete with each other over wages for each candidate) but without the equal pay policy (Treatment 3), and Competition-Fixed treatment - with both the equal pay policy and hiring competition (Treatment 4). We will recruit only participants from the ethnic majority group to act as employers/managers. Each set of four candidate profiles includes two minority and two majority candidates, randomly selected from the pool collected in the preliminary phase.

The employer/manager will be provided with the interview performances of all four candidates. They will then decide whether or not to hire each candidate and, if they opt to hire, what wage they are willing to offer. Each candidate will have an undisclosed reservation wage. The employer/manager can successfully hire a candidate if their wage offer is higher than the candidate's reservation wage (Treatments 1 and 2), or if their wage offer is higher than both the candidate's reservation wage and the competing manager's wage offer for the same candidate (Treatments 3 and 4). Depending on the treatment, the potential employer/manager can choose to offer an identical wage (Treatments 2 and 4) or different wages to different candidates. Along with interview performances, the potential employer/manager will also be given information about the candidates’ ages, prolific IDs (not their actual IDs), and ethnicity (reflected through their surnames).

Not available

A computer

individual candidate

Yes

Each treatment has 44 sessions. So there will be 176 sessions.

Each session has 16 candidates and 1 participant (manager). The total observations are 4x44x1= 176 participants, and 4x44x16 = 2816 candidates. Each participant finish 4 tasks (named as candidate pool), so total will be 704 pools.

176 sessions