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The economics of gender has been left behind, and still employs a reductive framing in which gender gaps in economic outcomes are either due to discrimination or to “choice.” Shelly Lundberg suggests this is because of strong priors driven by market bias and gender essentialism, a perspective that views the default economic agent as male, and an oft-noted tendency to avoid complex problems in favor of those that can be modelled simply. Shelly discusses more and paths forward here.

Image courtesy of interviewee. July 30, 2024

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This video is a transcript discussing gender economics and its shortcomings in recognizing and addressing issues related to labor market discrimination and gender differences. The speaker highlights that traditional economic frameworks often default to male perspectives, leading to a narrow understanding of economic behavior and choices. Key points include:

1. **Gender Economics Gap**: The field has lagged in integrating psychological and social factors that affect gender differences in behavior and outcomes.
2. **Gender Essentialism**: The assumption of inherent differences between men and women hinders a comprehensive understanding of discrimination and economic participation.
3. **Labor Market Discrimination**: Discrimination is often framed in terms of market outcomes while neglecting influential pre-market factors like socialization and upbringing, which shape preferences and opportunities.
4. **Cultural Influences on Choices**: Gender stereotypes significantly influence decisions about education and career paths, affecting women’s participation in fields like STEM.
5. **Need for Broader Perspectives**: Economic research must consider the male gender also as a variable influencing behavior and choices, rather than viewing it as the default.
6. **Future Research Directions**: There are opportunities for in-depth analysis of gender norms across cultures and their role in shaping economic behavior, requiring a nuanced approach to understanding and addressing gender disparities.

Overall, the conversation emphasizes the need for a shift in how economists approach gender-related issues by acknowledging the complexities of gender norms and their socio-economic implications.

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Here are some key quotes extracted from the video discussing the intersection of gender, economics, and discrimination:

1. **Broadening Economic Framework**:
- "As economics has drastically broadened its conceptual framework to include more realistic psychological and social influences on people's behavior, gender economics really has fallen behind somewhat."

2. **Gender Essentialism and Bias**:
- "I think that what's going on is the phenomenon that psychologists call gender essentialism, which I think is really biased."

3. **Understanding Labor Market Discrimination**:
- "Labor market discrimination is usually defined as systematic differences between groups in labor market outcomes, employment wages, and so on."

4. **Focus on Preferences**:
- "This intense focus on what happens only in the market... usually get attributed to differences in preferences."

5. **Pre-market Factors and Socialization**:
- "We should be concerned about the totality of factors that drive gender differences in earnings."

6. **Role of Social Norms**:
- "We need to get rid of this sharp dichotomy between differences in economic outcomes between men and women that are due to preferences... and those that are driven by labor market discrimination."

7. **Gender Norms and Economic Outcomes**:
- "The sources of violence... both domestic violence and... violence in other spheres... have distinctly male components."

8. **Cultural Effects on Gender Behavior**:
- "There’s a lot of interesting historical research being done... about men that we have failed to pursue."

9. **Norms of Femininity and Early Marriage**:
- "Early marriage is in these societies a signal that you are the kind of girl that married dear old dad, right? You are a traditional, submissive, good woman."

10. **Nuanced Understandings of Gender**:
- "Economists are developing more nuanced senses of the role of gender in different societies and how heterogeneous it is."

These quotes encapsulate the speaker's views on how gender influences economic behavior and outcomes and the necessity of considering social and cultural factors when analyzing these issues.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

00:00.025 --> 00:03.525
As economics has drastically broadened its conceptual

00:03.525 --> 00:06.285
framework to include more realistic psychological

00:06.385 --> 00:08.805
and social influences on people's behavior,

00:09.025 --> 00:11.845
gender economics really has fallen behind somewhat,

00:12.035 --> 00:14.085
despite the recent presence of a lot

00:14.085 --> 00:16.165
of truly superb empirical work.

00:17.345 --> 00:20.845
And this paper pursues that point in the specific case of

00:20.865 --> 00:22.925
how we think about discrimination.

00:23.625 --> 00:24.685
Um, why, why?

00:25.035 --> 00:27.685
Well, we're still a fairly male dominated discipline.

00:27.865 --> 00:30.845
And I think that what's going on is the phenomenon

00:30.845 --> 00:33.565
that psychologists call gender essentialism,

00:33.735 --> 00:35.285
which I think is really biased.

00:35.585 --> 00:38.405
Our understanding of gender differences as a discipline.

00:38.945 --> 00:40.725
And this is the belief that there are

00:41.475 --> 00:44.365
fundamental differences between men and women,

00:44.745 --> 00:47.205
and that any observed differences in behavior

00:47.385 --> 00:51.085
or outcomes has to reflect those fundamental

00:51.625 --> 00:55.285
and inherent differences, in their essential natures.

00:56.045 --> 00:58.865
And so that's, I think what's going on is we tend to default

00:58.925 --> 01:01.385
to this notice, this notion that men

01:01.385 --> 01:02.625
and women are just different.

01:02.625 --> 01:05.345
Labor market discrimination is usually defined as

01:05.875 --> 01:09.065
systematic differences between groups in labor,

01:09.065 --> 01:12.105
market outcomes, employment wages, and so on.

01:12.565 --> 01:14.545
Um, groups that have identical productivity

01:14.645 --> 01:18.345
or at least identical productive potential, recognizing

01:18.345 --> 01:20.265
that things like training might,

01:20.725 --> 01:22.145
be differentially available too.

01:22.805 --> 01:27.065
Um, and in the case of gender economics has tended

01:27.065 --> 01:30.585
to treat differences in, for example, your field

01:30.585 --> 01:34.065
of study in university or your occupation.

01:34.765 --> 01:37.425
And both of those things contribute dramatically

01:37.425 --> 01:39.745
to gender differences in wages as due

01:39.745 --> 01:42.665
to some pre-market factors that we don't need

01:42.665 --> 01:44.705
to be concerned with as economists.

01:44.765 --> 01:46.385
And that usually get attributed

01:46.725 --> 01:48.025
to differences in preferences.

01:48.885 --> 01:52.905
Um, and the bizarre thing is that this intense focus on

01:52.905 --> 01:54.745
what happens only in the market,

01:55.215 --> 01:58.425
only in the labor market is long passed in economics

01:58.425 --> 01:59.425
as a more broadly.

01:59.965 --> 02:03.225
So the field in general has become very concerned

02:03.225 --> 02:06.505
with early influences on adult economic outcomes

02:06.565 --> 02:08.625
and, you know, prenatal tuition

02:09.125 --> 02:11.865
or nutrition rather pollution,

02:11.925 --> 02:15.265
and its effects on later health, early education.

02:15.645 --> 02:16.985
And so as a social science,

02:18.005 --> 02:21.225
we should be concerned about the totality of factors

02:21.255 --> 02:23.425
that drive gender differences in earnings.

02:24.085 --> 02:25.625
And we now know that one

02:25.625 --> 02:29.225
of those early influences is socialization, no surprise

02:29.245 --> 02:31.665
to anybody in one of the other social sciences

02:32.095 --> 02:35.505
that leads women to, for example, avoid STEM fields

02:36.005 --> 02:39.185
and to take on heavier domestic responsibilities than men.

02:39.645 --> 02:42.465
So what we thought of as labor market discrimination,

02:43.485 --> 02:46.105
that's dis differential treatment of men

02:46.105 --> 02:47.305
and women by employers.

02:48.015 --> 02:51.705
Free market discrimination is differential treatment

02:51.885 --> 02:54.985
by parents, schools, society.

02:55.445 --> 02:57.185
And so there's not, you know,

02:57.185 --> 02:58.505
from a scholarly point of view,

02:58.845 --> 03:01.405
Any useful distinction to be made between

03:01.935 --> 03:05.005
labor market discrimination by employers

03:05.465 --> 03:07.405
and these sort of pre-market factors.

03:07.635 --> 03:10.125
Here, I think we can rely on a large quantity

03:10.345 --> 03:12.325
of insightful empirical work

03:12.325 --> 03:14.365
that tells us a lot about the connections

03:14.365 --> 03:18.645
between these gender stereotypes and later productivity.

03:19.105 --> 03:21.775
We know, for example, that the decisions

03:21.775 --> 03:24.695
of second generation immigrant women about work

03:24.695 --> 03:28.935
and family, are very strongly affected, not just

03:29.195 --> 03:30.535
by their current communities

03:30.715 --> 03:32.415
and the labor market that they are in,

03:32.875 --> 03:36.135
but by the work family norms in their parents' country

03:36.155 --> 03:37.215
of origin, right?

03:37.275 --> 03:40.815
So we know that a lot of those attitudes, towards work,

03:40.815 --> 03:43.175
family trade-offs are culturally driven.

03:44.365 --> 03:49.165
Um, we know that a young woman's interest in stem fields

03:49.745 --> 03:53.325
and her relative performance on math tests, for example,

03:53.465 --> 03:56.885
and there's a lot of studies on this, is affected

03:57.025 --> 04:00.285
by the attitudes of their parents, their teachers

04:00.585 --> 04:05.205
and their peers about whether women can do math,

04:05.425 --> 04:07.405
and whether they should be scientists.

04:07.745 --> 04:09.325
And, and we know that parents do their best

04:09.325 --> 04:12.205
to prepare their children for success in the world

04:12.205 --> 04:14.645
that they believe their children will be entering.

04:15.025 --> 04:17.645
And sometimes that means encouraging

04:17.705 --> 04:20.205
as parents stereotypical gendered behavior

04:20.315 --> 04:22.325
because you think it'll be best for your kids.

04:23.965 --> 04:26.705
We, we know that undergraduate students,

04:27.095 --> 04:29.265
when they choose majors, women report

04:29.495 --> 04:31.665
that if they're considering a STEM field,

04:31.855 --> 04:34.465
they take into account both the implications

04:34.485 --> 04:36.225
for their own income positive

04:36.965 --> 04:40.665
and the implications for their future marriage prospects,

04:40.665 --> 04:42.145
which they think would be negative.

04:43.005 --> 04:45.225
Um, so these kinds of gender norms

04:45.225 --> 04:48.945
and gender stereotypes as they get conveyed by parents

04:49.045 --> 04:50.745
and by other influential figures,

04:51.615 --> 04:54.155
are tremendously important drivers of the skills

04:54.185 --> 04:57.315
that young men and women decide to cultivate

04:57.665 --> 04:59.315
what they think will be useful to them

05:00.095 --> 05:02.315
and to the extent that they are internalized

05:02.415 --> 05:05.435
as the right way to behave affects their preferences.

05:05.535 --> 05:07.995
We need to get rid of this sharp dichotomy between

05:09.305 --> 05:12.635
differences in, in economic outcomes between men

05:12.635 --> 05:14.595
and women that are due to preferences,

05:15.825 --> 05:17.855
which we say your free choice

05:18.235 --> 05:20.775
and those that are driven by labor market discrimination.

05:20.885 --> 05:23.695
There's really not a useful distinction to be made here.

05:23.985 --> 05:25.095
There are economic

05:25.155 --> 05:27.735
and social forces driving,

05:28.695 --> 05:30.895
economic differentials in both of these spheres.

05:31.195 --> 05:35.175
And we now know as economists a lot more about those early

05:35.225 --> 05:37.375
influences than we did say 20 years ago.

05:37.445 --> 05:39.935
There's so many missed opportunities in research,

05:40.155 --> 05:41.615
involved in this question.

05:41.775 --> 05:45.095
I think, I would have trouble convincing my

05:45.095 --> 05:46.295
colleagues of this one, by the way.

05:46.795 --> 05:50.175
Uh, it's very clear that the default economic agent is male,

05:50.875 --> 05:54.735
and the focus of this new field of gender economics

05:55.275 --> 05:57.095
is always effectively

05:57.305 --> 05:59.005
On why are women so weird?

05:59.435 --> 06:01.765
Like why do women deviate from what we think of

06:01.785 --> 06:03.885
as the norm for human behavior?

06:04.545 --> 06:08.205
And we almost never consider male behavior patterns

06:08.805 --> 06:11.585
as reflecting, for example, norms of masculinity.

06:12.285 --> 06:15.505
And that limits our understanding of a lot

06:15.565 --> 06:19.225
of really serious social and economic issues, right?

06:19.325 --> 06:22.025
The sources of violence of all sorts, right?

06:22.025 --> 06:23.585
Both domestic violence and,

06:23.685 --> 06:25.825
and violence in in other spheres.

06:26.445 --> 06:28.465
Um, why do men frequently appear

06:28.465 --> 06:30.865
to have adverse health outcomes as a result

06:30.865 --> 06:33.185
of insufficient use of medical services,

06:33.665 --> 06:35.905
preventative services,

06:37.085 --> 06:38.465
and a lot of other issues

06:38.465 --> 06:41.545
that have distinctly male components that

06:41.545 --> 06:43.145
because we don't label them that way,

06:43.365 --> 06:47.385
we simply don't look at them effectively, as economists.

06:47.485 --> 06:52.065
So one example is we know that mass layoffs of workers

06:53.045 --> 06:56.345
are associated with both bad economic outcomes in

06:56.345 --> 06:57.465
the future, right?

06:57.465 --> 07:00.265
People lose the skills that were well suited

07:00.265 --> 07:02.905
to the particular job they'd had in the last 20 years,

07:03.405 --> 07:05.065
but also with poor health

07:05.085 --> 07:07.145
and with even higher rates of mortality.

07:08.465 --> 07:11.515
This is true only for men who are laid off.

07:11.815 --> 07:14.995
If we fall and women experience mass layoffs as well,

07:15.575 --> 07:19.475
we don't experience the same kind of adverse health

07:19.495 --> 07:21.955
and mortality, results for women.

07:22.215 --> 07:25.155
Now why is that? That's an interesting question I think

07:25.325 --> 07:28.395
about men that we have failed to pursue.

07:29.175 --> 07:31.355
Um, there's a lot

07:31.375 --> 07:34.195
of really interesting historical research being done.

07:34.355 --> 07:35.515
I mean, economists love data.

07:35.695 --> 07:38.235
And so, you know, this, this whole area

07:38.335 --> 07:40.315
of research opens up all kinds of new data.

07:40.335 --> 07:44.235
We can look at locations in Australia that during

07:44.895 --> 07:47.355
the period when, convicts were being

07:47.875 --> 07:48.875
transported from England

07:48.955 --> 07:52.235
and settled in Australia, some areas ended up

07:52.235 --> 07:56.675
with extremely high male to female population ratios, right?

07:56.675 --> 08:00.915
They were very male intensive in the present day, right?

08:01.395 --> 08:02.835
A hundred more than a hundred years later.

08:03.245 --> 08:05.715
Those areas, even though their gender ratios,

08:05.885 --> 08:09.555
population ratios are normal, still experience higher rates

08:09.555 --> 08:10.995
of male suicide and violence.

08:12.505 --> 08:14.405
So there's some cultural effect

08:15.075 --> 08:17.805
that clearly involves masculinity norms

08:17.985 --> 08:19.765
that's being transmitted over time.

08:19.985 --> 08:21.205
That's fascinating.

08:21.545 --> 08:25.605
But I think until we recognize that,

08:26.315 --> 08:28.565
male is a gender too, right?

08:28.625 --> 08:32.965
And has specific implications for human behavior,

08:33.555 --> 08:35.285
that regarding male behavior

08:35.305 --> 08:38.965
as the default is preventing us from an entire, I think,

08:38.965 --> 08:40.685
range of, of productive research.

08:40.885 --> 08:45.125
I think this, this has implications for how we tackle,

08:46.025 --> 08:47.845
gender discrimination

08:47.905 --> 08:49.765
and gender differentials in a

08:49.765 --> 08:50.925
variety of different societies.

08:51.035 --> 08:54.725
That is we have to take seriously as economists more

08:54.725 --> 08:56.645
Than we have in the past, right?

08:56.825 --> 08:59.405
The implications of social norms, for example.

09:00.325 --> 09:04.065
And, I think there's increasing amounts

09:04.065 --> 09:07.105
of work on the role of gender norms

09:07.105 --> 09:09.425
and how they vary across different societies.

09:09.845 --> 09:12.425
And I think the thing that we're coming to recognize is

09:12.425 --> 09:16.785
that often those are part of a social equilibrium

09:17.045 --> 09:18.785
that's very difficult to shift.

09:19.605 --> 09:23.265
So there's a recent paper, for example, on

09:23.725 --> 09:28.145
can we reduce very early marriage for women in some,

09:28.325 --> 09:29.385
in some countries?

09:29.805 --> 09:31.465
And what they've discovered is trying

09:31.465 --> 09:33.905
to apply the usual sec economic tools

09:33.925 --> 09:37.505
of giving people incentives and so on can backfire

09:38.015 --> 09:42.665
because early marriage is in these societies a signal

09:43.575 --> 09:46.145
that you are the kind of girl

09:46.145 --> 09:47.705
that married dear old dad, right?

09:47.705 --> 09:52.065
You are a traditional, submissive,

09:52.725 --> 09:53.985
good woman.

09:54.485 --> 09:56.305
And if you stay in school longer

09:56.525 --> 09:59.665
and you marry later, that breaks that signal

10:00.005 --> 10:02.985
and can lead to serious difficulties

10:03.645 --> 10:05.625
in your marriage market, right?

10:05.645 --> 10:07.705
And so it's reasonable that families

10:07.705 --> 10:10.865
therefore will expect young women to marry early.

10:11.255 --> 10:13.305
It's a good signal in this society

10:13.695 --> 10:15.185
that you are a proper woman.

10:15.645 --> 10:18.185
And so changing these things is very complicated

10:18.245 --> 10:19.345
and I think it's important.

10:19.925 --> 10:21.945
Um, and it's actually, I think coming about

10:21.945 --> 10:24.545
that economists are developing more nuanced senses

10:25.045 --> 10:28.625
of the role of gender, in different societies

10:28.765 --> 10:30.185
and how heterogeneous it is.

"Reevaluating Gender Economics: The Impact of Societal Norms and Market Discrimination"

00:00:00 - As economics has drastically broadened its conceptual framework to include more realistic psychological and social influences on people's behavior, gender economics really has fallen behind somewhat, despite the recent presence of a lot of truly superb empirical work. And this paper pursues that point in the specific case of how we think about discrimination. why, why? Well, we're still a fairly male dominated discipline. And I think that what's going on is the phenomenon that psychologists call gender essentialism, which I think is really biased. Our understanding of gender differences as a discipline. And this is the belief that there are
00:00:44 - and that any observed differences in behavior or outcomes has to reflect those fundamental and inherent differences, in their essential natures. And so that's, I think what's going on is we tend to default to this notice, this notion that men and women are just different. Labor market discrimination is usually defined as systematic differences between groups in labor, market outcomes, employment wages, and so on. groups that have identical productivity or at least identical productive potential, recognizing that things like training might, be differentially available too.
00:01:27 - to treat differences in, for example, your field of study in university or your occupation. And both of those things contribute dramatically to gender differences in wages as due to some pre-market factors that we don't need to be concerned with as economists. And that usually get attributed to differences in preferences. and the bizarre thing is that this intense focus on what happens only in the market, only in the labor market is long passed in economics as a more broadly. So the field in general has become very concerned
00:02:06 - and, you know, prenatal tuition or nutrition rather pollution, and its effects on later health, early education. And so as a social science, we should be concerned about the totality of factors that drive gender differences in earnings. And we now know that one of those early influences is socialization, no surprise to anybody in one of the other social sciences that leads women to, for example, avoid STEM fields and to take on heavier domestic responsibilities than men. So what we thought of as labor market discrimination,
00:02:46 - and women by employers. Free market discrimination is differential treatment by parents, schools, society. And so there's not, you know, from a scholarly point of view, Any useful distinction to be made between labor market discrimination by employers and these sort of pre-market factors. Here, I think we can rely on a large quantity of insightful empirical work that tells us a lot about the connections between these gender stereotypes and later productivity. We know, for example, that the decisions of second generation immigrant women about work
00:03:29 - by their current communities and the labor market that they are in, but by the work family norms in their parents' country of origin, right? So we know that a lot of those attitudes, towards work, family trade-offs are culturally driven. we know that a young woman's interest in stem fields and her relative performance on math tests, for example, and there's a lot of studies on this, is affected by the attitudes of their parents, their teachers and their peers about whether women can do math,

"Gender Norms and Stereotypes: Their Impact on Educational Choices and Economic Outcomes"

00:04:07 - And, and we know that parents do their best to prepare their children for success in the world that they believe their children will be entering. And sometimes that means encouraging as parents stereotypical gendered behavior because you think it'll be best for your kids. We, we know that undergraduate students, when they choose majors, women report that if they're considering a STEM field, they take into account both the implications for their own income positive and the implications for their future marriage prospects, which they think would be negative. so these kinds of gender norms and gender stereotypes as they get conveyed by parents
00:04:51 - are tremendously important drivers of the skills that young men and women decide to cultivate what they think will be useful to them and to the extent that they are internalized as the right way to behave affects their preferences. We need to get rid of this sharp dichotomy between differences in, in economic outcomes between men and women that are due to preferences, which we say your free choice and those that are driven by labor market discrimination. There's really not a useful distinction to be made here. There are economic and social forces driving, economic differentials in both of these spheres.
00:05:35 - influences than we did say 20 years ago. There's so many missed opportunities in research, involved in this question. I think, I would have trouble convincing my colleagues of this one, by the way. it's very clear that the default economic agent is male, and the focus of this new field of gender economics is always effectively On why are women so weird? Like why do women deviate from what we think of as the norm for human behavior? And we almost never consider male behavior patterns as reflecting, for example, norms of masculinity.
00:06:15 - of really serious social and economic issues, right? The sources of violence of all sorts, right? Both domestic violence and, and violence in in other spheres. why do men frequently appear to have adverse health outcomes as a result of insufficient use of medical services, preventative services, and a lot of other issues that have distinctly male components that because we don't label them that way, we simply don't look at them effectively, as economists. So one example is we know that mass layoffs of workers
00:06:56 - the future, right? People lose the skills that were well suited to the particular job they'd had in the last 20 years, but also with poor health and with even higher rates of mortality. This is true only for men who are laid off. If we fall and women experience mass layoffs as well, we don't experience the same kind of adverse health and mortality, results for women. Now why is that? That's an interesting question I think about men that we have failed to pursue. there's a lot of really interesting historical research being done.
00:07:35 - And so, you know, this, this whole area of research opens up all kinds of new data. We can look at locations in Australia that during the period when, convicts were being transported from England and settled in Australia, some areas ended up with extremely high male to female population ratios, right? They were very male intensive in the present day, right? A hundred more than a hundred years later. Those areas, even though their gender ratios, population ratios are normal, still experience higher rates of male suicide and violence. So there's some cultural effect

"Reevaluating Gender Norms: The Complexity of Male Behavior and Its Implications for Economic Research"

00:08:17 - that's being transmitted over time. That's fascinating. But I think until we recognize that, male is a gender too, right? And has specific implications for human behavior, that regarding male behavior as the default is preventing us from an entire, I think, range of, of productive research. I think this, this has implications for how we tackle, gender discrimination and gender differentials in a variety of different societies. That is we have to take seriously as economists more Than we have in the past, right?
00:09:00 - And, I think there's increasing amounts of work on the role of gender norms and how they vary across different societies. And I think the thing that we're coming to recognize is that often those are part of a social equilibrium that's very difficult to shift. So there's a recent paper, for example, on can we reduce very early marriage for women in some, in some countries? And what they've discovered is trying to apply the usual sec economic tools of giving people incentives and so on can backfire
00:09:43 - that you are the kind of girl that married dear old dad, right? You are a traditional, submissive, good woman. And if you stay in school longer and you marry later, that breaks that signal and can lead to serious difficulties in your marriage market, right? And so it's reasonable that families therefore will expect young women to marry early. It's a good signal in this society that you are a proper woman. And so changing these things is very complicated
00:10:28 - and it's actually, I think coming about that economists are developing more nuanced senses of the role of gender, in different societies and how heterogeneous it is.

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