It is therefore probable that the results of our experiments underestimate the extent of discrimination against women. In fact, there is another flaw: our panels are mostly made up of university students-who are statistically better educated than the average, and less inclined to discriminate. But they are the best way today to get people to reveal their preferences. This is, of course, assuming that the individuals are trying to maximize their gain, which seems reasonable in an experiment that takes place in the context of work, business and professional achievement.īut given the small sums at stake (the participants earned an average of about €20), one could doubt the reliability of the process for ensuring that they are being honest…ĭ.M.: You are right in the sense that these laboratory studies have their limits and are, after all, simulations. It prompts the employers to reveal their true choices, instead of trying to appear as ethical as possible. Once “hired,” they are asked to solve logic problems, play code breaking games, etc., for their “employer.” At the end of the trial, employers and employees are paid based on their performance. Since they are making choices that have no actual consequences for them, how can this be considered a “real” situation?ĭ.M.: But their choices do have consequences! The participants actually “work” during the experiment. I’m not sure I understand why the participants in your experiments would be more honest and forthcoming than those in a survey. This shows that it is not a case of intra-group preference, and that women are also influenced by negative stereotypes about their own professional skills. In addition, we noted that women (43 of the 72 on the panel) discriminate against women as much as men do (40 out of 72). ![]() Of course, the educational levels and disciplines were homogenous among the 72 women and 72 men of our 144-strong experimental panel. Discrimination is shown when the educational level and all other variables being equal, a participant ranks a woman lower than a man. Our experiments, on the other hand, allow us to observe the participants’ decision-making process in the laboratory: they are asked to rank, from most to least favorite, various job candidates based on files that include their educational level and areas of study, and an avatar that makes it possible to determine the gender of each applicant. And if recruiters are asked about it in a survey, they are not likely to tell the truth if they indeed practice any kind of discrimination. Why can’t conventional survey results be used to identify the origin of the discrimination?ĭ.M.: The hiring process is a real “black box.” Statistics can tell which candidates were recruited, but not what was going on in the employer’s mind during the decision process. Conventional data derived from employment statistics or surveys is insufficient to determine which theory, whether intra-group or statistical discrimination, is actually at play. And these interpretations are influenced by stereotypes-women supposedly performing less well than men in the same job, for example. The problem is that recruiters often try to draw conclusions from other parameters for which individuals cannot be held accountable, such as age, gender, skin color, etc. The second postulates that, having no reliable information on a candidate’s skills, employers are reduced to interpreting signals, the main one being educational level. This type of discrimination is already present in early childhood, according to tests on children who were split in two groups (red and blue, for example)., which influences employers to hire someone who “resembles” them. ![]() For example, it prompts a man to prefer recruiting another man. ![]() One suggests that it is the result of “intra-group” favoritism FermerA behavior that favors members of one’s own group against others who do not belong to it. 2 Secondly, it makes it possible to study the root cause of this discrimination, which is usually explained by two opposing theories. What does this new aspect of economics reveal about discrimination against women in the job market?ĭavid Masclet: 1 First of all, it has enabled us to observe that discriminatory behavior towards women does indeed exist during the recruitment process. The idea is to compare theoretical economic models with data observed in “real” situations. The objective is to be able to observe whether or not a model prediction is true, if such prediction cannot be validated using conventional methods-such as surveys., a relatively recent discipline that involves testing the reactions of participants in simulation games. Your research concerns experimental economics FermerResearch method used for testing conventional economic models with participants, in the laboratory.
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