The 2021 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was awarded
to these three gentlemen, David Card, for his empirical contributions to labour economics,
as well as Joshua Angrist & Guido Imbens for their methodological contributions to the
analysis of causal relationships.
causal relationships, not casual relationships, nerdy economists certainly aren’t winning
any awards for those, but these are perhaps even more interesting.
The fact that this year was a joint prize with two groups being recognized for their
contributions to the field of economics goes to show just how consequential their work
really has been.
Labour Economics is something that impacts all of us directly, but perhaps this has never
been more apparent than right now in the midst of a global pandemic with hundreds of countries
all trying to put the economies back on track without causing greater issues down the road.
So was this just a coincidence?
No, not really, no.
In recent years to Royal Swedish Academy of Sciences has actually been specifically targeting
academic work that has direct applications in modern economies. A great example of this
was the winners that we explored last year,
Paul Milgrom and Robert Wilson, whose contributions
to auction theory are actually being put to good use as we speak, linking the best buyers
with sellers in some of the most complex transactions
in the world.
This focus on practical economic applications means that these awards are a whole lot more
than some self-congratulatory academic pomp fest, they are genuinely an insight into new
and creative ways that some of the greatest minds ever are changing the world around us.
It also means that long-held economic opinions
that most economists simply assume to be self-evident
are being challenged. The work of this year's winners actually changed my mind on an economic
function that I had spoken about pretty openly in a lot of my videos, so this will be a great
chance to have some of the most brilliant economists in the world set the record straight
for both you and I.
But I am getting ahead of myself. To truly appreciate the Nobel Prize and the contributions
it’s recipients make, we need to as always understand a few specific things.
So
How does one actually qualify to win a Nobel Prize?
What did this year's winners contribute to the field of economics to win their prize?
And
How are their academic advances actually being put to good use
in the real world?
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The Nobel Prize was created by Alfred Nobel, a Swedish chemist and industrialist who was
best known at the time for stabilizing an incredibly reactive compound called nitroglycerin.
By basically combining this chemical with clay it became much easier to handle, while
still maintaining it’s explosive potential. What he had invented was dynamite. Literally.
Now in the interest of not being put on a watchlist that’s all I am going to say about
that.
Alfred Nobel immediately saw the destructive potential of his invention. Sure it had industrial
applications like mining and controlled demolitions,
but let’s be real, it was also going to
be used in war.
This fact haunted the scientist which is why upon his death in 1896 he bequeathed the vast
majority of assets to create a foundation which would award people who had made the
greatest contributions to humanity in five distinct fields.
physics, chemistry, medicine, literature, and peace.
Now you might notice something missing there.
Maths maybe, but they have the fields medal, which is basically the same thing just with
a lot less prize money, but more specifically, there is no economics.
Economics as a separate academic discipline wasn’t really a thing until the mid 19th
century, and even then most people just saw it as a combination of political science,
business, and finance.
It really wasn’t until the great depression and the rise of people like Keynes and Friedman
that economics became the topic of dinner table conversations around the world.
Nevertheless, it still had the potential to do a lot of good.
Being able to efficiently and effectively allocate resources has been instrumental at
lifting hundreds of millions of people out of absolute poverty over just the last five
decades.
Obviously, I might be a bit biased here, but advancements in economic policy can do just
as much good for humanity as advancements in all of these other fields.
Now the Central Bank of Sweden thought so too, and that is why in 1968 it partnered
with the Nobel Foundation to create the Sveriges Riksbank Prize in economic sciences in honor
of Alfred Nobel.
The sixth Nobel prize.
Since then, it has been awarded every year around the same time all of these other prizes
are given out. The recipients are awarded the same solid gold medal, and they share
in the same prize money, although the economists have their cut provided by the Swedish central
bank, not the Nobel Foundation.
This prize money is no joke. This year the prize was ten million Swedish kronor, or about
the equivalent of 1 million American dollars.
Typically the people that win these awards are already quite wealthy in their own right,
certain, more controversial recipients were worth tens of millions of dollars when receiving
their award so the social expectation was that this prize money would get donated, which
it is, more often than not.
But of course, to some career academics, this is a life-changing amount of cash, and most
people don’t begrudge these individuals hanging onto the money for themselves.
Now you might say, oh but Mr economics man, the real gift is being recognized as a Nobel
laureate, you could make much more money just by leveraging the notoriety that gives you,
and you would be absolutely right, mostly.
The reason that I mention the money at all is the initial award criteria was that these
prizes would be given to individuals or institutions
that had, had the greatest impact on their
respective field in the year preceding the award.
So if I wanted to win the Nobel prize next year in 2022 I would need to publish my research
before the end of 2021.
While this system made sense in theory and it made for a very exciting competition, the
unfortunate reality is that academia is not like sport, or the performing arts, where
a contribution's merit is immediately verifiable and appreciable.
This caused some embarrassment with awards being given to people who really shouldn't
have received it like the Portuguese neurologist who won the award for his pioneering research
on lobotomies, and Johannes Fibiger who won his award for the discovery of a parasite
that caused cancer.
Of course, the peer review process later showed that these theories were completely unfounded,
but by then the winners had already walked away with their honors and their prize money.
It’s because of this that the preceding year rule has mostly been abolished in favor
of recognizing contributions that have stood the test of time, and even more importantly
actually been used in practical applications outside theoretical settings where disclaimers
like “ceteris paribus” and “ignore air friction” can’t save you.
So this brings us along to this year's winners in the field of economics, who have exemplified
this application over theory approach to generate some insights that could fundamentally change
The Way We Work
Labour is one of the factors of production, alongside land and capital.
The theory is to make anything you need some combination of these three factors. They are
not always equal, but you always need at least a little bit of each.
Labour is the unique variable here because almost all of us have access to an equal amount
of it by default. We are one person and we can do the work of one person, whereas one
person can own a lot of land and capital while others own none.
This has made labour, more commonly called jobs, a major factor in people’s lives,
determining everything from where they live to who they vote for.
Now despite its importance, most economists try to simplify labor's role in the economy
as just another good or service.
As such they assume that there is a negative relationship between wages and employment.
If you take a step back and think about it, this makes perfect sense. Wages are just the
price that a business pays for a set quantity and quality of labor, and employment rates
are a function of demand for labor.
Even people with the most elementary understanding of economics know that as the price of something
increases the demand for that good or service decreases because less people are willing
and able to pay the higher price for that item.
This has led many to assume that raising minimum wages would do more harm than good because
it would force employers to cut back on staffing in an attempt to maintain business profitability.
By this logic the reverse is also true, by reducing the minimum wage it makes it cheaper
for businesses to employ people, therefore, they will employ more of them.
Some infamous reports have actually called for establishing a zero dollar minimum wage
because by this logic it would lead to zero unemployment.
Even the laziest of staff members would be worth having around if a business only needed
to pay them fifteen cents an hour.
Now despite the huge social problems this would cause, there is one other more immediate
issue. It just doesn’t work.
Remember when I said at the beginning of this video that the Nobel Prize for Economics was
increasingly being awarded to economists that
emphasized practical applications and experimentations
in their research?
Well, this is how our first laureate won their prize.
David Card is most famous for a paper he co-authored
in 1994 which found no indication that the
rise in the minimum wage reduced employment.
He did this by studying fast-food workers at major chains in New Jersey after the state
raised its minimum wage from $4.25 an hour to $5.05 an hour in 1992.
He then compared employment numbers in these restaurants to restaurants from the same chains
just over the border in easter Pennsylvania where the minimum wage had not been altered.
If the traditional economic theory was correct then employment levels in New Jersey should
have fallen as they needed to cut hours to compensate for the increased cost of labor.
In reality, the opposite happened, employment in New Jersey actually increased relative
to eastern Pennsylvania.
It’s important to note that the study didn’t actually suggest increasing the minimum wage
increased employment, it was instead trying to prove that the minimum wage had no impact
on employment. So even no relative change would have been a positive outcome for this
study.
The paper itself also didn’t actually set out to explain why this was happening, it
was instead trying to show if there was or
was not a relationship between these two variables.
It did inspire follow-up research though that pointed to higher disposable incomes increasing
aggregate demand in local areas.
In general, employing people is expensive and difficult. Employers only do it if they
absolutely need to, and if they absolutely need to employ someone, because let’s say
more people are eating out thanks to their new higher salaries, then within reason an
extra dollar an hour in staff costs isn’t going to make or break on that hiring decision.
Card followed this paper up with a similar study on the labor supply side of this equation.
He did this by studying the Mariel Boatlift
of 1980 which brought thousands of Cuban immigrants
fleeing communism into the United States.
See if you can answer this question. What happens to wages and unemployment when a city
like Miami sees a 7% increase in its labor force? made up primarily of unskilled laborers
mind you.
A reasonable expectation would be that these excess workers would compete with existing
workers or just not be able to find jobs at
all, which would simultaneously increase unemployment,
and lower wages.
But it didn’t.
Again the paper itself didn’t actually cover the why, it was more concerned about proving
or rather disproving that this relationship actually existed.
These papers along with a series of other research papers published by Card and his
peers have had drastic impacts on the way that economists understand labor market dynamics.
These real-world studies are now having real-world impacts on policy decisions.
Now these papers, as impressive as they might be, would not have been possible if it were
not for the work of the other two winners of this year's prize. Joshua Angrist and Guido
Imbens who both shared 50% of the prize with the remaining 50% having been claimed by David
Card. They all got their own gold medal though, so that’s nice.
These two won their award for their methodological
contributions to the analysis of causal relationships.
In plain English, economists around the 1990’s had a real problem of lying with statistics.
They had gotten their hands on computers that were powerful enough to crunch huge data sets
and they were drawing relationships everywhere and anywhere.
The problem with these relationships was that correlation doesn’t equal causation.
The famous example of this is that ice cream sales are highly correlated with drownings.
Despite this correlation, ice cream does not drown people, and people that have been drowned
are not going to be hungry for ice cream. Rather it is a third variable: a hot day which
causes both of these. On a hot day, people are more likely to go swimming and more likely
to eat ice cream.
This is an obvious example, but when it comes to economics, finding these hidden third factors
can be extremely difficult but it’s not impossible.
I actually got called for my video exploring why cold countries are richer than hot countries
because
I concluded that this correlated relationship was not spurious, as in it did not have some
hidden third variable. A lot of people rightfully asked how I knew that, given a hidden third
variable would be well, hidden.
That is where Instrumental Variables Estimation comes in, which sounds really scary, because
it kinda is, I am not gonna lie to you on this one guys, this is an advanced statistical
method which aims to find causality, not just correlation, but it’s actually not too difficult
to understand the theory behind it.
The best example of this is one of Angrist's early papers on the relationship between lifetime
earnings and military service.
Angrist wanted to find if the experience of serving in the military caused lower lifetime
earnings because of factors like PTSD or acquired injuries.
The problem was that there were hidden variables that had a direct impact on both the independent
and dependant variables in this study. Now some of these could be controlled for.
For example, people from lower socio-economic backgrounds are more likely to join the military
and are also more likely to have lower lifetime incomes, but that’s not the fault of military
service, that’s just the inherent relationship between being born wealthy and living wealthy.
The researchers knew this is a factor and could easily adjust for it. But what about
variables that can’t be controlled for.
Someone that hates the idea of working a professional
9-5 job is also going to be more likely to
join the military and also going to tend to have lower lifetime earnings.
Again this isn’t the fault of the military, this is a personality trait that would have
impacted their career earnings regardless of if they decided to join the military or
not.
The problem is that data pertaining to people's opinions on professional working environments
is a lot harder to collect and therefore a lot harder to control for.
Angrists solution to this was to use the data of conscripts from the Vietnam war.
The theory was that since conscripts did not willingly volunteer to be part of the military
they would be devoid of the hidden variables that willing volunteers would have which could
impact both earnings and military service.
This allowed Angrist to just look at how military service affected earnings in isolation as
in how much does military service cause a fall in income.
The results were that conscripted veterans earned just over $400 a year less than their
peers who were not conscripted,
a pretty significant sum back in the 1970s.
I only use this example because it is one of the easier ones to understand but both
Angrist and Imbens have made massive contributions towards the responsible use of data in economics.
A clear example of where this influenced cards work from earlier was his decision to use
fast-food chains.
By just studying fast-food restaurants like KFC and McDonalds Card could be confident
that he was assessing the causation and not just correlation, because fast-food restaurants
make sure to standardize their operations in all of their locations across the country.
The practical applications of the research these three gentlemen have conducted over
their careers cannot be overstated. It will continue to have very real impacts on the
way that we formulate labor laws, deal with immigration and conduct research on these
issues well into the future.
So congratulations to them and all their fellow laureates who I am sure have made equally
consequential contributions towards their respective fields.
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