The path from cause to effect is dark and dangerous,
but the weapons of econometrics are strong,
wield differences-in-differences when witnessing parallel trends.
♪ [music] ♪
Masters of metrics
look for convincing ceteris paribus comparisons.
The ideal comparison contrasts treatment and control groups
that look similar.
But sometimes this sort of comparability is elusive.
When treatment and control groups
evolve similarly in the absence of treatment,
even if from different starting points,
there's hope for causal inference.
The weapon that exploits parallel evolution,
masters say parallel trends,
is called differences-in-differences...
(voice whispering) Differences-in-differences
- ...or DD for short. - Alright. Nice.
Let's see how DD can help us understand
one of the most important economic events
in US history.
Look back with me now at the Great Depression--
the worst economic catastrophe, our country has ever known.
Unemployment hit 25% in 1933--
a level not seen before or since.
Millions lost their homes or their land.
Suicide spiked, and hungry families
relied on soup kitchens and bread lines
to keep from starving.
Economists argue fiercely over the causes of the Great Depression.
Most agree, however, that a key piece of the puzzle
is an epidemic of bank failures.
This was before deposit insurance.
So if your bank went bankrupt, your savings disappeared with it,
Faced with a banking crisis, the central bank has a choice:
lend freely to troubled banks
or stand aside and refuse to lend.
Lending freely to banks in trouble is called easy money.
Refusing to lend is called tight money.
Monetarist masters Milton Friedman and Anna Schwartz
famously called the Great Depression
the "Great Contraction,"
accusing the Federal Reserve
of inflicting a misguided policy of tight money
on the nation's teetering financial institutions.
They argued that easy money
would have kept many banks in business,
shortening the Great Depression,
But others disagree!
If banks are insolvent
because of unwise lending decisions,
then bailouts just encourage more foolishness.
Economists call this problem,
moral hazard the debate over bailouts in. Moral hazard continues. Today
should Financial Behemoth.
Lehman Brothers, have been allowed to fail on the eve of the Great Recession
in an Ideal World. We'd answer this question by applying different fed policies
to randomly selected regions,
but we can still learn a lot by using differences
and differences to compare Trends across areas with different monetary policies.
How's that even possible? Don't the same fed policies. Apply to all banks in the US?
Yeah, good question.
The Federal Reserve System is divided into twelve districts each headed by
a regional bank. Today fed policy is set at the national level.
But in the 1930s Regional, feds could do pretty much as they liked,
and here's what's so awesome about that
in 1930. The Atlanta fed running the 6th District, followed an easy money.
Policy sending wheelbarrows of cash to rescue insolvent institutions,
the st. Louis fed running the 8th District, followed a Tight money policy.
Let Veil The foolish they said in st. Louis
and so a natural experiment in monetary policy was born even better.
This is a within State experiment,
the border between the sixth and the eighth districts run smack
through the middle of Mississippi.
So northern, Mississippi had tied money while Southern Mississippi.
Had easy money, but under the same state laws in banking regulations, in both.
The treatment group is the district. 6 part of Mississippi,
which had access to Easy Money during the crisis.
The control group is the district 8 part of Mississippi,
which had Tight money during the crisis.
The key year in our natural experiment was 1930,
Caldwell and Company a massive Financial Empire. In the South Came Crashing. Down.
Banking is a business built on confidence and Trust
the Caldwell meltdown caused a panic that led to a widespread Bank Run all at once.
Depositors wanted their money back, causing Banks to go bankrupt
and shut their doors.
We'll use differences in differences to measure the effect
of contrasting monetary policies in response to the Caldwell crisis.
This figure plots. The number of banks in Mississippi by year
for the eighth and sixth districts.
Let's start in 1929 a year before the Caldwell crash.
There are 169 banks open in the eighth and 141 banks open in the
Over the next year,
we see a similar handful of banks fail. In both districts,
the change in the number of banks in operation. Is remarkably similar.
That's what parallel Trends look like
in November. 1930, Caldwell, crashes.
And the Panic begins
Banks. Fail frequently in the 8th District, which had Tight money,
but the decline is slower in the 6th District which had easy money.
The diverging Trends in this period,
might be attributable to easy versus Tight money
in July, of 1931, the 8th District, abandons type money.
So now both districts are easy.
Parallel Trends are restored
in a counterfactual world where the sixth district follows a Tight money policy.
What might have happened
if we extrapolate the trend of the 8th District to the sixth,
it would look like this.
So
The treatment effective easy money is how much the 6th District deviated From
the Path implied by the 8th District trend.
How many banks did the Easy Money treatment save
this table reports data for the treatment group District Six in the first row
and data for the control group District 8 in the second row.
The First Column shows the number of banks in business,
before The Crisis began in 1930. The second column shows 1931.
This is the key period when each district had differing monetary policies during
the crisis the rightmost.
Column
reports changes within the district district, 6 lost 14 Banks while District
8 lost 33, the mathematical formula for the treatment effect is simple.
We subtract the change in banks in operation, in the 8th District
from the change in banks in operation in the sixth.
Hence. The name differences in differences,
negative 14, minus negative, 33 equals 9.
19.
We estimate that 19 Banks were saved by easy money
in practice tables and figures like those shown here are the beginning
rather than the end of a DD analysis,
the problem of how to gauge the statistical, significance of DD, estimates
turns out to be exceedingly, tricky
and a regression is typically part of the solution,
the key assumption behind a
DD analysis is that of parallel Trends recall, the principle of ceteris paribus,
our ideal comparison would have the two districts experienced,
an identical business environment, except for one factor easy or tight money.
Both districts would have identical types of customers who would go bankrupt
at exactly the same rate.
The skill of their employees would be equal and so on
perfect ceteris, paribus comparisons would allow us to clearly see
the causal effect of different fed policies in this case, that's not possible.
But the idea of parallel Trends is based on a similar concept.
If we see that the two regions experienced similar Trends in the number
of banks over.
Time in the absence of treatment, we can assume they are good comparisons.
We see that the two districts move in parallel both before the crisis. And after,
when they have the same fed policy,
the only time the district's behave differently is when the FED policy is different.
In view of this fed policy is a likely cause of diverging Trends from 1930 to 1931.
But we should also check for other changes unique to northern, Mississippi.
What do you mean?
Imagine that bad tornadoes? Hit Northern, but not Southern. Mississippi in 1930,
these tornadoes devastate Farms causing Farmers to default on loans,
which drives their Banks out of business.
Then the sixth and eighth districts would differ in not one, but two ways
fed policy, and whether and we'd have trouble identifying
Policy as the causal Factor behind increased bank failures in the eighth.
DD credibility lives or dies with the claim that the
only reason northern Mississippi was special in 1930
is differing. Regional fed policy.
We're in DD heaven with strong Visual Evidence of parallel Trend in general.
The first step in evaluating whether
to use DD is usually this type of visual confirmation of parallel Trends
outside of the period.
When we expect to see a treatment effect, the treatment in our example,
Easy money in the face of bank failures
metrics Masters, use DD to explore effects of many policies
like the minimum, legal drinking age,
and environmental changes like access to clean water.
In our next video.
We'll see an example of how regression is used to implement a DD approach.
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