I'm interested in inequality and, in particular, I'm interested in gender inequality.
So, over the last decade, we have seen that women are doing much better in terms of education, in terms of health.
We see that access to schooling is equal among boys and girls as well as access to health services
but there are still some disparities and the largest disparity that we see is in terms of labor market.
We see that when women go to the labor market, they have worse conditions than men.
They are, first, less likely to enter, and, they are more likely to be unemployed, they have lower wages,
they have less employment in formal jobs. So, what can we do from a policy perspective to decrease this inequality?
So, one of the main policies that has been used, or, one of the many policies that have been used,
is affirmative action
and affirmative action tries to decrease these disparities by either giving preferential access to women for employment
possibilities or by directly setting some quotas for women to enter into certain positions,
like the quota that sees them on company boards that we see in Germany.
There is not a strong debate: is this good to use affirmative action policies, do they help, or,
do they actually discriminate against women and devalue their achievements?
We'll go to a different question and we'll go to the more basic question here is
but what happened with affirmative action policies?
Do they actually help to promote women into the labor market, to incentivize women to apply to positions?
And, if that is the case, what happens with males? Do they get less encouraged to participate?
And, lastly, is there an efficiency cost? Do we get more applicants but relatively worse qualified ones?
Do they get rid of the good men and attract many bad women?
So, in order to address this question, what we need to know is to have the application rate, that is,
out of the total number of job seekers, how many sent up the application or complete the application process?
So what we do is that we do an experiment.
In the experiment, first, we built up the, the pool of job seekers,
we sent an announcement asking for people who might be interested in working for us and, then,
once we knew who would be looking for a job,
(we knew also quite some detailed characteristics of who was looking for a job)
we assigned them to different information conditions.
So, we told them, “now, you can apply for the position and fill a very demanding form”
but the choice here is that half of them were told that affirmative action would be used in the selection process.
And the other half was not told about that when they were completing the application form
but they were only informed after they finished the application form, so exposed all received the same information.
What we do is that we now compare the rate of applications to the number of applicants that were invited to apply under
both conditions and, out of these applicants, how many ends up submitting the application process.
And we can break this down by gender, how many males, how many females end up completing the whole application?
So, this allows us to understand how affirmative action affects application rates.
One of the beautiful things of our experiment is that we use it in a natural experimental set up so participants never
know that they are in an experiment so they cannot affect their behavior by being in an experimental condition.
And this also allows us to understand the drivers of participation in the labor market
or the obstacles that some groups might confront in participating in the labor market, like, for instance, children.
Are applicants with children different in their likelihood to submit or to complete the application process or not?
So what do we find? We find that, out of the total job seekers, about 50% end up submitting an application form.
But, more interestingly, how does it change for males and women?
We find that in the control condition, without affirmative action, there is a huge gap in application rate.
Women are 20% less likely to complete an application than males.
And once we use the affirmative action policy, this gap completely disappears. But how does it disappear?
Does it disappear because now there are less males applying or is it just because there are more women applying?
What we find is that the application rate by males is rather constant.
With the three experiments, only in one of the experiments is there a decrease, so it is not a significant,
there are not systematic differences in application patterns.
And what we do find is that, over all three experiments, the application rate by females is significantly higher.
So what we find is that, indeed, affirmative action works and it works by bringing the women that would have,
otherwise, sorted out from the labor market.
So, affirmative action seemed to be working but does it come with an efficiency cost?
Is it that we are attracting relatively worse candidates?
Are we actually losing all these very good male candidates that now don't want to apply for the position?
So to address this question, what we need to do is to build up a measure of qualification.
And, the measure of qualification that we build is based on the predicted wage.
So, according to individual characteristics of the job seekers, we can predict their expected wage
and use this as an indicator of qualification.
So, best qualified candidates would have an expected, higher expected wage than less qualified candidates.
And what do we find?
So, when we compared the affirmative action treatment with the control,
we find that there are no significant differences in the qualifications, and neither for male applicants
nor for female applicants.
So, all together, it seems that, in terms of qualifications, the pool of applicants is rather comparable.
So, if that is the case, what we are actually finding,
is that affirmative action is beneficial in attracting more women to the job market and it does not come at a cost.
It’s not decreasing efficiency, it’s not decreasing the quality of the application.
So the policy recommendation of this research is clear.
Affirmative action is a good policy and affirmative action can help to leverage the playing field.
And these results are talking to a large audience
and to a large number of developing countries that have very similar conditions to the set up that we use in the
experiment.
But we also want to be realistic and call for the attention on how particular contextual factors matter and,
in particular, we warn against replications without evaluation because contextual factors like female empowerment,
support at home, perceived responsibilities of women at the household level,
can have very different implications on how effective affirmative action policies are.
And also, if you compare it with policies that are compulsory versus policies that are voluntary,
the effects might be very different.
So what we are just “calling out” is, like, look,
there is this great research agenda out there that needs more work, that needs to be tested in different contexts
and we provide some instruments on how this can be done and some expertise on our research.
So,
our contribution to the scientific community is that we developed some methods that can be used to understand affirmative
action policies or many other policies in the labor market and that we open a field of research that needs more work
and that there are many more questions that can be addressed: how contextual factors matter
and how can we actually decrease discrimination or gender gaps in the labor market.
What are the open questions?
So, what we saw is that inequality is an important issue
and one dimension in which gender inequality is even more important is in terms of managerial positions.
In terms of decision making power within organizations, women are completely under represented
and this is almost a phenomenon that occurs everywhere. So why are these differences emerging?
Why is it that women don't want to do it? Is it that it’s something innate?
Is it like some suggest that women are less competitive, that women don’t like to take a status,
that women dislike taking responsibility for others? Or, is it actually something that is socially learned?
Is it that the society is shaping these norms and, therefore,
is there room to change these behaviors by social learning?
So what we do is that we try to understand this question looking at the context of India,
a country that has both matrilineal and patrilineal societies and we compare decision making of men and women.
And we investigate whether women would be more willing to implement social sanctions, so,
whether they would be willing to take boys, to go against social-antisocial behavior,
and if there would be differences between men and women. We don't find anything like that.
We find that, in matrilineal societies, women are much more willing to go for positions of boys than males
and this is just telling us that all the differences that we observe are driven by socialization are not by innate
differences.
So, there is also a lot of research that is needed to understand how these differences emerge already at early age
and whether there are differences in the school age children.
So we are studying in a new project the decision making within households, within schools,
and democratic participations and comparing whether and how these differences emerge in early age.
And, finally, I think that another dimension where inequality is still important
and where we need to do much more research is in terms of inequality within the household.
So, what we are studying in another project is the decision making within the household.
Do men and women, or are women equally likely, like men, than men, to be willing to decide?
Who wants to decide at home?
