If you think your boss is in her position only because of a gender quota and not because of merit, it could affect the work you do for her.
Gender quotas may be effective in fixing an imbalance of men and women in the workplace but whether they are good or bad for organisations depends on how people feel about them, our study shows.
Gender quotas are controversial. Opponents of gender quotas have long argued that they are unfair because it often means the best candidates do not get the positions they deserve.
Proponents of gender quotas often argue that, among other reasons, women have to go the extra mile in order to get the same recognition because of various disadvantages such as discrimination and societal pressure. As a result, gender quotas are required to correct for such unfair disadvantages.
Both of these arguments revolve around the idea of whether the best person gets the job. However, whether gender quotas reward those who are talented actually depends on the perception of the labour market environment, which depends on the profession.
We surveyed 1,011 respondents in the US and asked them whether they agreed with the use of gender quotas to reserve leadership positions for women. Without providing any context, opinions were divided - roughly the same number of people agreed and disagreed with the use of quotas.
However, when we provided some context about the labour market environments, there was a lot more consensus. When told that there was a gender skill gap (where women are on average worse than men at a certain job), only around 20% of the respondents agreed with the use of quotas.
When told that there was no skill gap, close to 30% of the respondents agreed with the use of quotas. However, when told that there was a bias against women in the selection process, more than 70% of the respondents agreed with the use of quotas.
We found that whether gender quotas are good or bad for an organisation’s performance is reflected in these attitudes towards gender quotas. If gender quotas are applied in industries where women are thought to be discriminated against, they can enhance the productivity of managers and workers. However, if they are applied in industries where discrimination against women is thought not to be a problem, then the organisation’s performance can deteriorate significantly.
Our experiments on gender quotas
To test how implementing gender quotas affects an organisation’s performance, we conducted an experiment with 516 students.
In the experiment, managers were chosen based on their score in a five-minute arithmetic task that they performed prior to the experiment. If a quota was not implemented, then the students with the highest observed scores were chosen as managers. If a quota was implemented, then a proportion of the manager positions were reserved for the highest scoring female students, and the best of the rest filled up the remaining manager positions. All other students were assigned the role of worker.
Each manager was then paired with a worker. Each manager started with an endowment and decided how much wage they would offer the paired worker. The worker, after receiving the wage, decided how much effort they put in for the manager. Participants were paid for taking part in the experiment. The manager’s pay depended on the worker’s effort and the wage offered to the worker. The worker’s pay depended on the wage received and the cost of effort.
This experiment was designed so that the more effort the workers put in, the better the organisational performance. We tested whether or not managers offered different wages and the workers put in different effort level, when a gender quota was implemented under the three different environments.
In the first environment, we generated a perceived gender skill gap by telling participants that women solved 20% fewer sums in the arithmetic task. In the second environment, we told participants that there was no gender difference in the arithmetic task. In the third environment, students were told that there was no gender difference. However, in that environment we only counted the the score from the first four minutes of the five-minute task for female participants, creating a bias against women in the selection procedure.
We found that when there was no skill gap or bias against women, implementing gender quotas substantially reduced the wages that the managers offered and the effort that the workers provide. The result was even worse when there was a skill gap. However, when there was a bias against women in the selection procedure, we observed the opposite: managers offered higher wages and the workers put in more effort.
What these results mean for quotas
Our results show that gender quotas should not be blindly implemented. When there is a perceived bias against women in an industry, implementing gender quotas can enhance an organisation’s performance. However, when there is no perceived bias against women in an industry, implementing gender quotas can damage an organisation’s performance and harm the people who are meant to benefit from the quotas.
It is therefore important to know how people perceive the labour market environment in each industry. In our survey, we asked respondents about their perception of skill gap and bias against women in their profession.
White collar workers tended to think that there was no skill gap or bias against women and blue collar workers tended to think there was a bias against women. On the other hand, architecture, healthcare and “pink collar” workers tended to think that women were better than men at the job and that there may be a bias in favour of women.
While how people perceive gender skill gap and discrimination may not be accurate, it is what matters. So if your organisation wants to impose gender quotas then they should first educate their employees about whether any gender skill gap in the field is actually justified in the first place, and whether there is gender discrimination in the sector. Otherwise, without this understanding, implementing gender quotas could backfire.
Authors: Edwin Ip, Researcher, University of Melbourne