Chapter 19: Earnings and Discrimination

Welcome to Last Minute Lecture.

This free chapter overview is designed to help students review and understand key concepts.

These summaries supplement not replaced the original textbook and may not be redistributed or resold.

For complete coverage, always consult the official text.

Okay, let's try and unpack this.

Have you ever really stopped to think about the huge differences in what people actually earn?

I mean, we're talking a physician making what, $200 ,000 a year, a police officer maybe $65 ,000, and a fast food cook around $22 ,000.

These aren't just numbers, are they?

They translate into vastly different lifestyles.

Mansions versus small apartments, you know, fancy vacations versus staycations.

Well, it's a huge disparity.

Last time we talked a bit about the basic theory, the neoclassical view, where wages depend on labor supply and demand and kind of reflect how productive a worker is.

But honestly, as useful as that is, it's just the beginning, isn't it?

To really get why the differences are so wide, we need to dig deep.

What specifically drives supply and demand for different kinds of jobs?

Exactly.

That foundational theory gives us a framework, sure, but the details matter, the characteristics of the job, the characteristics of the person doing it.

So in this deep dive, we're going to shed light on those factors.

And we'll also get into a really important, sometimes difficult topic,

discrimination in the labor market.

We want to figure out why earnings vary so much and what complex forces are really driving things.

Okay, so let's start with some of those key factors influencing pay, beyond just basic supply and demand.

First one economists talk about is compensating

differentials.

Sounds a bit technical.

It does, but the idea is pretty simple, actually.

A compensating differential is just a difference in wages that offsets the non -money aspects of a job.

Think about it, some jobs are just nicer or safer or easier than others, right?

Right.

The research pointed to a great example.

Picking a summer job, you could be a beach badge checker.

Nice gig.

Yeah, strolling on the sand.

Or you could be a garbage collector,

waking up super early, noisy trucks.

Less appealing for sure.

Definitely.

So if the pay was the same, who'd choose garbage collection?

Almost nobody, you'd think.

Exactly.

So the town has to offer more money to get people to do that less pleasant job.

That extra pay is the compensating differential.

And you see this all over coal miners, for instance.

They tend to earn more than workers with similar education.

Why?

Dangerous job, health risks.

Precisely.

It compensates for the danger and the long -term health issues.

Same for night shift workers, they usually get paid a premium for working unsociable hours.

And it works the other way too.

Professors, even with lots of education, like doctors or lawyers, often earn less.

Why is that?

Well, the argument is the job offers other rewards, like intellectual freedom, personal satisfaction, things that aren't money, but still have value.

Okay, that makes sense.

So job characteristics matter.

What about the workers themselves?

Let's talk about human capital.

Right.

Human capital isn't like physical capital, factories, machines.

It's the investment in people.

Education is the biggest example.

It's an investment someone makes in themselves.

Like spending time and money on college.

Exactly.

You spend resources now, hoping to be more productive and earn more in the future.

It's tied to the person, not a physical asset.

And it clearly has a big payoff.

I mean, in the U .S., college grads earn nearly double what high school grads do, on average.

But what's really striking is how that gap has changed over time.

It's gotten much wider.

We looked at some data, table one in the chapter.

Back in 1977, a male college grad earned about 44 % more than a male high school grad.

Okay.

By 2017, that difference jumped to 76%.

And for women, the gap went from 31 % to 74 % over the same period.

Wow.

That's a huge increase.

The financial return to education has really climbed.

So why?

Why has this college premium grown so much?

Well, economists have a couple of main theories.

The first one points to international trade.

As the U .S.

imports more goods made with unskilled labor and exports more goods made with skilled labor, that tends to decrease the demand for unskilled workers here at home and increase the demand for skilled workers, pushing their wages further apart.

Okay.

Trade is one factor.

What's the other?

The other big one is skill -biased technological change.

Think about computers and automation.

Technology often complements skilled labor.

You need people to design, program, operate complex systems.

But it can substitute for unskilled labor think databases, replacing filing clerks.

So technology increases demand for skilled workers and reduces it for unskilled ones.

Exactly.

Both trade and technology seem to be pushing in the same direction, increasing the demand for skills and widening that wage gap.

Okay.

Beyond education and job type, what about more personal things like just natural talent or how hard someone works or even just luck?

Absolutely critical factors.

Natural ability is a big one.

Think about professional athletes.

Yeah, like a top baseball player versus a minor leaguer.

Right.

The major leaguer earns vastly more, not because they have more degrees or a tougher job necessarily, but because they have exceptional innate talent.

And this applies everywhere.

Some people are just naturally stronger or smarter or better communicators.

That affects their productivity and their pay.

And effort seems tied to that too.

If you work harder, you're generally more productive.

Often, yes.

Think about salespeople paid on commission.

More effort usually means more sales, means higher pay.

But then there's chance.

You mentioned the example of a technician trained on old vacuum tube TVs.

Classic case.

Suddenly, solid state electronics come along.

Their skills become obsolete almost overnight.

Through no fault of their own, they're earning potential plummets.

That's just bad luck, really.

It's fascinating how much random events can shape things.

And speaking of maybe unexpected factors, there was that case study on the benefits of beauty.

Ah, yes.

Hammer, mesh and biddles work.

Quite intriguing.

They found that people considered more physically attractive tend to earn more, like 5 % more than average -looking people, who in turn earned 5 -10 % more than those rated less attractive.

It raises some interesting questions, doesn't it?

How do we interpret that?

Well, the study suggested a few possibilities.

Maybe attractiveness is a kind of innate talent useful in jobs dealing with the public.

That's one view.

Or maybe it's not beauty itself, but something correlated with it, like confidence or better presentation skills.

Or could it just be a form of discrimination, bias from employers or customers?

That's the third possibility, and it ties into the discrimination topic we'll discuss more later.

It certainly makes you think about what merit really means in the labor market.

Okay, let's circle back to education for a moment.

We talked about it building human capital, making people more productive.

But there's an alternative view, right?

The signaling theory.

Yes, the signaling theory.

Yeah.

This perspective suggests that maybe education doesn't primarily increase your productivity.

Instead, it acts as a signal,

a way for you to show potential employers that you already have high ability.

How does that work?

The idea is that getting a degree, especially from a challenging program, is easier for people who are already intelligent, diligent, and resilient.

So by completing the degree, you're signaling those underlying traits to employers, even if specific course content isn't directly used on the job.

It's like the effort itself is the signal, similar to that advertising theory where spending lots of money on an ad signals the company believes in its product.

Exactly.

Analogous, yes.

The willingness to invest the time and effort in education signals your quality as a potential employee.

Firms use the diploma as a sorting device.

So human capital says education builds productivity.

Signaling says it reveals productivity.

What are the implications?

Well, policy -wise, they differ.

If human capital theory is dominant, then investing more in everyone's education should raise overall productivity and wages.

But if signaling is the main story, then just giving everyone more degrees wouldn't necessarily boost overall productivity much.

It would just make people get more education to signal their ability relative to others.

The sorting function remains.

So which is it?

Like most things in economics, the truth is probably somewhere in between.

Education likely does both.

It enhances skills and it signals ability.

Okay.

Now what about those really extreme earners, the superstars, like actors, musicians, top athletes earning millions?

Ah, the superstar phenomenon.

This happens in markets with two specific features.

What are they?

First, every customer in the market wants to enjoy the good supplied by the very best producer.

You don't want to see the second best actor half as much.

You want to see the top star.

Right.

You want to see Emma Stone, not someone kind of like her.

Exactly.

And the second feature is that the technology exists for that best producer to supply every customer at a low cost.

Ah, so movies can be copied, concerts streamed, matches broadcast.

One performance reaches millions.

Precisely.

That technology allows the superstar to leverage their talent across a massive market.

This isn't true for say a plumber or a chef.

Even the best plumber can only fix so many sinks a day.

Exactly.

They can earn a good living, maybe more than average, but they can't scale their service to millions like a movie star can.

Hence the astronomical earnings for superstars.

Okay.

So far we've mostly assumed wages adjust to balance supply and demand reaching an equilibrium, but sometimes wages are set above that level.

Why?

There are three main reasons economists point to for above equilibrium wages.

First, minimum wage The legal floor on wages.

Right.

For low skill or less experienced workers, the minimum wage can be higher than what the market might otherwise set, potentially leading to job losses for that group.

Second reason.

Labor unions.

Unions act as a collective voice for workers, bargaining with employers.

Using the threat of strikes sometimes.

Yes, that's their main leverage.

Through collective bargaining, they can often secure wages that are say 10 to 20 percent higher than what similar non -union workers earn.

And the third one, it sounds a bit counterintuitive.

Efficiency wages.

It does seem odd at first.

This is the theory that firms might choose to pay wages above the equilibrium level.

Not because they're forced to, but because they believe it's actually profitable.

How could paying more be more profitable?

Several ways.

Higher wages can reduce worker turnover, saving the firm money on recruiting and training.

It can increase worker effort.

People work harder if they feel well paid and fear losing a good job.

And it can attract a bitter pool of applicants to begin with.

So the higher wage pays for itself through increased productivity or lower costs elsewhere.

That's the idea.

But it's important to note that all three of these minimum wages, unions, efficiency wages, tend to have a similar side effect.

Which is?

By pushing wages above the market clearing level,

they tend to increase the number of jobs offered.

Labor demand.

This gap results in a surplus of labor or unemployment.

Okay.

Before we move on, you mentioned another interesting study about education schooling as a public investment.

Ah, yes.

Noah Smith's piece.

He argued against the idea that just throwing money at schools doesn't work.

What did the evidence show?

He cited research suggesting a 10 percent increase in cake hole spending led students to get about a quarter year more schooling, earn over 7 percent higher wages later on, and significantly cut their chances of falling into poverty.

That sounds like a pretty good return.

Especially because the benefits were much stronger for children from poorer families.

And beyond the individual benefits, the argument is that society gains too.

Better educated workers mean more productive companies, which helps stockholders.

It stimulates the local economy, leads to better civic participation, maybe even lower crime rates.

It positions education not just as a private good, but a public investment with broad benefits.

A really powerful perspective.

Okay.

Let's shift gears now to a really complex and sensitive topic.

Discrimination.

How does this fit into wage differences?

Discrimination occurs when the market offers different opportunities or pay to similar individuals just because of their race, gender, age, or some other personal characteristic unrelated to productivity.

How do economists even measure something like that?

It seems tricky.

It is very tricky.

We can observe wage gaps for sure.

We looked at data showing, for example, that in 2017, black men earned about 21 percent less than white men and white women about 20 percent less than white men.

That sounds like discrimination right there.

Not necessarily, or at least not the whole story.

Seeing a gap is an automatic proof of labor market discrimination against equally qualified people.

Why not?

What else could explain it?

Well, we have to account for differences in things like human capital education,

experience levels, which often vary systematically between groups.

So if one group has, on average, less schooling or fewer years on the job, their average wages might be lower for that reason, separate from direct discrimination by an employer.

Also, compensating differentials matter.

If men and women tend to choose different occupations with different non -monetary characteristics,

that could explain some of wage gap, too.

Like women being more concentrated in administrative roles and men in truck driving, perhaps.

Potentially, yes.

Those choices can lead to different average wages.

However, and this is crucial, those differences in human capital or occupational choice might themselves be the result of past or ongoing discrimination outside the labor market.

Ah, like discriminatory access to quality schools, historically, or societal pressures channeling people into

Exactly.

So poorer schools for black children in the past limited their human capital accumulation.

That's discrimination just happening earlier.

It's complex to untangle.

But are there ways to isolate discrimination in the hiring process itself?

Yes, and some studies do this quite effectively.

The Emily versus Lakeisha study is a famous example.

What did they do?

A researcher sent out thousands of identical resumes to job postings, changing only the names to be either typically white sounding, like Emily, or typically African American sounding, like Lakeisha.

And the results?

Resumes with white sounding names got about 50 % more callbacks for interviews.

A similar study in Canada found English names got significantly more callbacks than Indian, Pakistani, Chinese, or Greek names, even when qualifications were identical and gained in Canada.

Wow.

Wow.

That's pretty clear evidence of bias in the initial screening process, isn't it?

It strongly suggests bias.

Yes, it indicates that discrimination based on race or ethnicity can still be a very real barrier, even for employers who might say they are equal opportunity.

So if discrimination exists, who's responsible?

Is it primarily biased employers?

That's often the assumption.

But economists argue that competitive markets actually contain a kind of natural antidote to employer discrimination.

The profit motive.

Think about it.

If an employer is prejudiced against a certain group, say blondes, and pays them less than equally productive brunettes,

then a non -prejudice employer can gain an advantage.

They can hire the equally skilled blondes at the lower wage, have lower production costs, and potentially undercut the discriminatory firms on price.

So competition should drive out the discriminatory firms over time.

In theory, yes.

Firms focused purely on profit have an incentive to ignore prejudice and hire the cheapest qualified labor.

The entry of non -discriminatory firms and the exit of discriminatory ones should eventually equalize wages for equally productive workers.

There's a historical example of this, right?

The segregated streetcars.

Exactly.

In the early 20th century South, streetcar companies were forced by law to segregate black and white passengers.

But they didn't want to.

Economic historians found the companies actually approved these laws.

Why?

Because having separate sections, or separate cars, raise their costs and cut into profits.

Their desire for profit was stronger than any prejudice they might have held.

It shows how the profit motive fights discrimination unless something else interferes.

Okay, so if the profit motive works against employer discrimination,

why does discrimination sometimes persist?

Good question.

There are limits to the power of the profit motive in this context.

Two main ones.

That's the first.

Customer preferences.

If the profit is served by, say, brunettes instead of blondes, then firms might cater to that prejudice.

So the discrimination survives because the customers are essentially paying for it.

Exactly.

The firm isn't leaving profit on the table.

They're responding to discriminatory demand.

And the second limit.

Government policies.

If the government mandates discrimination, like the apartheid laws in South Africa that barred black people from certain jobs or those streetcar segregation laws,

then the market's natural tendency towards equal wages is blocked by force of law.

So customer bias and government rules can override the competitive pressure against discrimination.

Precisely.

The discrimination in sports example touches on customer preference.

Some older studies found evidence suggesting fan preference might have led to pay gaps between black and white players in basketball or affected baseball card values.

Though you mentioned newer studies in baseball didn't find that gap anymore.

Correct.

Which might indicate shifts in customer attitudes or other market changes over time.

It's complex.

Okay.

Besides direct prejudice from employers or customers, is there another type?

You mentioned statistical discrimination earlier.

Yes.

This is a more subtle but potentially quite harmful form.

It happens when employers lack perfect information about individual job candidates.

How does that lead to discrimination?

Well, imagine an employer knows that on average, people from group A are more likely to have some desirable but hard to observe trait, like punctuality, than people from group B.

If they can't easily assess that trait in an individual applicant,

they might rely on the group average as a proxy.

They might favor applicants from group A, even if the specific individual from group B they're interviewing is actually very punctual.

They're using group statistics to judge an individual.

They're stereotyping based on

Exactly.

It's not necessarily based on malice or dislike, but on imperfect information and perceived risk reduction.

The ban the box example really highlights this, doesn't it?

It does.

These laws stop employers asking about criminal records upfront, trying to help ex -offenders, but employers know that statistically certain groups, like young black men without college degrees, have higher conviction rates.

So if they can't ask the individual?

They might become hesitant to hire anyone from that group, fearing they might unknowingly hire someone with a record.

So the policy intended to help could inadvertently harm innocent members of that group through statistical discrimination.

That's a really tough policy challenge.

How do you help one group without unintentionally causing harm to others through this statistical effect?

It's a profound dilemma, and research suggests these laws have negatively impacted employment for some young black men.

Finding solutions that help ex -offenders without triggering statistical discrimination is a major ongoing challenge for policymakers.

Wow.

So we've covered a lot of ground here.

We really have.

We've gone from compensating differentials for job features through human capital and the signaling debate, natural ability, effort, chance, even the economics of beauty.

And look at superstars, why wages might be above equilibrium due to minimum wages, unions, or efficiency wages.

And then dive deep into the incredibly complex issue of discrimination, its different forms, and why it can persist even in competitive markets.

It shows how economic theory helps explain these vast wage differences we see all around us.

Absolutely.

The labor market framework gives us the tools to understand why earnings differ.

But it's also crucial to remember, as the research points out, that the resulting distribution of income isn't necessarily equal or fair or morally desirable.

That's a really important takeaway.

Economic efficiency doesn't automatically equate to social equity.

Definitely food for thought.

Well, thank you for joining us on this deep dive into the economics of earnings and discrimination.

We hope it's given you, our listeners, a clearer, maybe more nuanced view of the powerful forces shaping wages and opportunities in our economy.

It's a reminder that behind the numbers are complex interactions of skills, choices,

market forces, and yes, sometimes bias.

Indeed.

As you go about your day, maybe think about the jobs people do and the wages they earn through this economic lens.

What other factors might be at play that we didn't even touch on today.

Until next time.