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Abstract This experiment aims to identify the impact of increased competition in the hiring market on the employer ethnic discrimination during the hiring. For each session, there are also 4 participants, to play the role of employer and finish a hiring game. We will provide profiles of employees candidates collected in the preliminary phase. Each session has profiles of 6 majorities and 6 minorities. All employers will firstly finish a practice task to understand the difficulty of the task to measure the ability of all employee candidates. We will have 3 treatments of this experiment: no hiring and wage competition, hiring competition with fixed wage, hiring and wage competition. In this experiment, we will experimentally examine the impact of increased competition in the recruitment market on employers' hiring and wage decisions. We design a laboratory experiment where we will use reserve wage to stimulate the hoteling model (Hotelling, 1929) to introduce competition in the hiring market. We will compare 2X2 treatments to identify whether increased competition in hiring market can effectively undermine the ethnic discrimination in both hiring and wage decisions: Hiring competition X flexible wage scheme. In the treatments with hiring competition settings, employers will face hiring competition in the labour market while in the treatments with a flexible wage scheme, employers can choose different wages to increase the likelihood of hiring their preferred candidates. The experiment is designed to test two theories: (1) whether discrimination can help employers to segment the market and escape away from competition; (2) whether ban of wage discrimination will lead to greater hiring discrimination.
Trial Start Date December 01, 2021 March 01, 2022
Last Published October 29, 2021 01:41 PM February 21, 2022 11:48 PM
Intervention (Public) 1)Baseline (Treatment A): No hiring and wage competition 2)Treatment B: Hiring competition with a fixed wage regime 3)Treatment C: Hiring competition and wage competition (flexible wage regime)
Intervention Start Date December 01, 2021 March 01, 2022
Primary Outcomes (End Points) The probability of a minority candidate being hired by at least one participant, controlled by given scores (rank), age, treatments and before or after updating process. The main variable of interest is the probability of an individual being hired in different treatments, controlled by ethnicity, scores and age. Another main variable is the wage that an individual being offered in different treatments, controlled by ethnicity, scores and age
Primary Outcomes (Explanation) 1) Hypothesis 1: The probability of minority employees being hired are lower in A than in B-1 and B-2 2) Hypothesis 2: The probability of minority employees being hired are lower in A than in C-1 and C-2 3) Hypothesis 3: The probability of minority employees being hired are lower in C-2 than in B-2
Experimental Design (Public) The experiment includes 2 parts:1) a preliminary phase. We will ask the participants to finish a series of tasks and an exit survey to capture their productivity and demographic information. This information will be used in the second part; 2) a hiring game. In the hiring game, we have three treatments: baseline -treatment A (without hiring and wage competition), fixed-wage -treatment B (with hiring competition only), flexible wage -treatment C (with both hiring and wage competition). We design a two-stage hiring game where the two participants (i.e. employers) will see four candidates, and they must decide whether to hire them or not in the first stage. If they decide to hire the candidate, they then need to choose a wage for their hired candidate in stage 2. We will introduce an intermediate hiring competition or a flexible wage scheme in the different treatments. To allow for learning effects, the participants will play this two-stage game in 5 independent rounds. The experiment is based on a between-subject design. In the baseline treatment (Treatment A0), 2 employers will have a hiring competition if both employers decide to hire the same candidate, and they are free to choose different wage offer to different candidates. As the main experimental variation (Treatment B0), we consider a non-competitive treatment where employers are free to choose different wage offers and always hire the preferred candidate without competition. In the main treatments, 2 employers are unable to practice wage discrimination, and they can only choose identical wages for all the preferred candidates under competitive (Treatment A1) and non-competitive scenarios (Treatment B1). The experiment is designed to examine the economic theory which predicts that discrimination can be profitable for employers to segment market and reduce wage payments in the presence of hiring competition (as in Treatment A0), and it is not profitable in the absence of hiring competition (as in Treatment B0). Moreover, the hiring discrimination against minority workers should be greater if wage discrimination is feasible (as in Treatment A0) than if wage discrimination is banned (as in Treatment A1). And such differences should only exist in the competitive environment (A0-A1) and do not exist in the non-competitive environment (B0-B1).
Planned Number of Clusters Each treatment has 100 sessions. So there will be 300 sessions Each treatment has 100 sessions. So there will be 400 sessions
Planned Number of Observations Each session has 12 employee candidates and 4 participants. The total observations are 48*300 =14400 observations Each session has 4 employee candidates and 2 participants. The total observations are 4x2x4x100 = 3200 observations
Sample size (or number of clusters) by treatment arms 300 sessions 400 sessions
Intervention (Hidden) In Treatment B and Treatment C, we will also introduce an update process to capture the interaction effects after the initial hiring decision. The update process occurs when all participants submit their initial hiring decisions. We will provide additional information, including how many participants have selected each candidate (occur both in Treatment B and Treatment C) and the highest wage offer each candidate has received so far (occur only in Treatment C). All participants will be given the opportunity to update their hiring decision within one minute after receiving this additional information. The updated hiring decision will result in two sub-treatments named B-2 Treatment and C-2 Treatment (prior to the updating is B-1 Treatment and C-1 Treatment, respectively).
Public analysis plan No Yes
Secondary Outcomes (End Points) Secondary outcome variables are the percentage (%) of minority candidates being hired in different treatments and the differences in mean wage between majority candidates and minority candidates in different treatments.
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MD5: 0486c7179d93ab6cb7d2411dc1d98161
SHA1: 86da1ed8e3035b551e0acaea4006f38d6ee561cd
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