0:00:00.400,0:00:05.700
The path from cause to effect[br]is dark and dangerous,

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but the weapons[br]of econometrics are strong,

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wield differences-in-differences[br]when witnessing parallel trends.

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♪ [music] ♪

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Masters of metrics

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look for convincing[br]ceteris paribus comparisons.

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The ideal comparison contrasts[br]treatment and control groups

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that look similar.

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But sometimes this sort[br]of comparability is elusive.

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When treatment and control groups

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evolve similarly[br]in the absence of treatment,

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even if from different[br]starting points,

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there's hope for causal inference.

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The weapon that exploits[br]parallel evolution,

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masters say parallel trends,

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is called differences-in-differences...

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(voice whispering)[br]Differences-in-differences

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- ...or DD for short.[br]- Alright. Nice.

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Let's see how DD[br]can help us understand

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one of the most important[br]economic events

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in US history.

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Look back with me now[br]at the Great Depression--

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the worst economic catastrophe,[br]our country has ever known.

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Unemployment hit 25% in 1933--

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a level not seen before or since.

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Millions lost their homes[br]or their land.

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Suicide spiked, and hungry families

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relied on soup kitchens[br]and bread lines

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to keep from starving.

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Economists argue fiercely over[br]the causes of the Great Depression.

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Most agree, however,[br]that a key piece of the puzzle

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is an epidemic of bank failures.

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This was before deposit insurance.

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So if your bank went bankrupt,[br]your savings disappeared with it,

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Faced with a banking crisis,[br]the central bank has a choice:

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lend freely to troubled banks

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or stand aside and refuse to lend.

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Lending freely to banks in trouble[br]is called easy money.

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Refusing to lend is called tight money.

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Monetarist masters Milton Friedman[br]and Anna Schwartz

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famously called[br]the Great Depression

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the "Great Contraction,"

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accusing the Federal Reserve

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of inflicting a misguided policy[br]of tight money

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on the nation's teetering[br]financial institutions.

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They argued that easy money

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would have kept[br]many banks in business,

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shortening the Great Depression,

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But others disagree!

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If banks are insolvent

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because of unwise[br]lending decisions,

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then bailouts just encourage[br]more foolishness.

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Economists call this problem[br]"moral hazard."

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The debate over bailouts[br]in moral hazard continues today.

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Should financial behemoth[br]Lehman Brothers

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had been allowed to fail[br]on the eve of the Great Recession,

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in an ideal world,[br]we'd answer this question

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applying different Fed policies[br]to randomly selected regions.

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But we can still learn a lot

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by using differences-in-differences

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to compare trends across areas[br]with different monetary policies.

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How's that even possible?

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Don't the same Fed policies[br]apply to all banks in the US?

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- Yeah.[br]- Good question.

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The Federal Reserve System[br]is divided into 12 districts,

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each headed by a regional bank.

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Today, Fed policy is set[br]at the national level.

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But in the 1930s, regional Feds[br]could do pretty much as they liked.

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Ah, interesting.

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And here's what's[br]so awesome about that.

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In 1930, the Atlanta Fed,[br]running the 6th District,

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followed an easy money policy,

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sending wheelbarrows of cash[br]to rescue insolvent institutions,

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The St. Louis Fed,[br]running the 8th District,

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followed a tight money policy.

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"Let fail the foolish!"[br]they said in St. Louis.

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And so a natural experiment[br]in monetary policy was born.

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Even better, this is[br]a within-state experiment.

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The border between the 6th[br]and the 8th districts

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ran smack through[br]the middle of Mississippi.

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So northern Mississippi[br]had tight money,

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while southern Mississippi[br]had easy money,

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but under the same state laws[br]in banking regulations in both.

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The treatment group

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is the District 6th part[br]of Mississippi,

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which had access to easy money[br]during the crisis.

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The control group

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is the District 8th part[br]of Mississippi,

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which had tight money[br]during the crisis.

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The key year[br]in our natural experiment

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was 1930,

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Caldwell & Company,

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a massive financial empire[br]in the South

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came crashing down.

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Banking is a business[br]built on confidence and trust.

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The Caldwell meltdown[br]caused a panic

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that led to a widespread[br]bank run all at once.

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Depositors wanted their money back,

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causing banks to go bankrupt[br]and shut their doors.

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We'll use differences-in-differences

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to measure the effect[br]of contrasting monetary policies

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in response to the Caldwell crisis.

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This figure plots the number[br]of banks in Mississippi by year,

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for the 8th and 6th districts.

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Let's start in 1929 - a year[br]before the Caldwell crash.

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There are 169 banks[br]open in the 8th,

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and 141 banks open in the 6th.

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Over the next year,

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we see a similar handful[br]of banks fail, in both districts.

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The change in the number[br]of banks in operation

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is remarkably similar.

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That's what parallel trends look like.

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In November 1930, Caldwell crashes,

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and the panic begins.

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Banks failed frequently[br]in the 8th district,

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which had tight money.

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But the decline is slower[br]in the 6th District,

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which had easy money.

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The diverging trends in this period

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might be attributable[br]to easy versus tight money.

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In July of 1931, the 8th district[br]abandons tight money,

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so now both districts are easy.

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Parallel trends are restored.

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In a counterfactual world,

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where the 6th district[br]follows a tight money policy,

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what might have happened?

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If we extrapolate the trend[br]of the 8th district to the 6th,

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it would look like this.

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So the treatment effective[br]easy money

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is how much the 6th district[br]deviated from the path

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implied by the 8th district trend.

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How many banks[br]did the easy money treatment save?

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This table reports data[br]for the treatment group, District 6,

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in the first row

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and data for the control group,[br]District 8, in the second row.

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The first column shows[br]the number of banks in business

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before the crisis began in 1930.

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The second column shows 1931.

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This is the key period

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when each district[br]had differing monetary policies

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during the crisis.

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The rightmost column[br]reports changes within the district.

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District 6 lost 14 banks,[br]while District 8 lost 33.

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The mathematical formula[br]for the treatment effect is simple.

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We subtract the change in banks[br]in operation, in the 8th District

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from the change in banks[br]in operation in the sixth.

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Hence. The name[br]differences in differences,

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negative 14, minus negative, 33 equals 9.

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19.

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We estimate that 19 Banks[br]were saved by easy money

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in practice tables and figures like[br]those shown here are the beginning

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rather than the end of a DD analysis,

0:07:55.400,0:08:00.000
the problem of how to gauge the[br]statistical, significance of DD, estimates

0:08:00.100,0:08:02.300
turns out to be exceedingly, tricky

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and a regression is typically[br]part of the solution,

0:08:09.200,0:08:10.700
the key assumption behind a

0:08:11.100,0:08:17.700
DD analysis is that of parallel Trends[br]recall, the principle of ceteris paribus,

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our ideal comparison would have[br]the two districts experienced,

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an identical business environment, except[br]for one factor easy or tight money.

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Both districts would have identical[br]types of customers who would go bankrupt

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at exactly the same rate.

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The skill of their employees[br]would be equal and so on

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perfect ceteris, paribus comparisons[br]would allow us to clearly see

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the causal effect of different fed[br]policies in this case, that's not possible.

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But the idea of parallel Trends[br]is based on a similar concept.

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If we see that the two regions[br]experienced similar Trends in the number

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of banks over.

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Time in the absence of treatment, we[br]can assume they are good comparisons.

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We see that the two districts move in[br]parallel both before the crisis. And after,

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when they have the same Fed policy,

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the only time the district's behave differently[br]is when the Fed policy is different.

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In view of this Fed policy is a likely[br]cause of diverging Trends from 1930 to 1931.

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But we should also check for other[br]changes unique to northern, Mississippi.

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What do you mean?

0:09:33.500,0:09:39.100
Imagine that bad tornadoes? Hit Northern,[br]but not Southern. Mississippi in 1930,

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these tornadoes devastate Farms[br]causing Farmers to default on loans,

0:09:44.600,0:09:46.800
which drives their Banks out of business.

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Then the sixth and eighth districts[br]would differ in not one, but two ways

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Fed policy, and whether and[br]we'd have trouble identifying

0:09:57.600,0:10:02.500
Policy as the causal Factor behind[br]increased bank failures in the eighth.

0:10:07.200,0:10:10.200
DD credibility lives or[br]dies with the claim that the

0:10:10.200,0:10:13.600
only reason northern[br]Mississippi was special in 1930

0:10:13.900,0:10:16.000
is differing. Regional Fed policy.

0:10:16.600,0:10:22.100
We're in DD heaven with strong Visual[br]Evidence of parallel Trend in general.

0:10:22.200,0:10:24.200
The first step in evaluating whether

0:10:24.200,0:10:30.200
to use DD is usually this type of[br]visual confirmation of parallel Trends

0:10:30.200,0:10:31.700
outside of the period.

0:10:31.700,0:10:36.900
When we expect to see a treatment[br]effect, the treatment in our example,

0:10:37.100,0:10:39.700
Easy money in the face of bank failures

0:10:40.500,0:10:45.000
metrics Masters, use DD to[br]explore effects of many policies

0:10:45.800,0:10:47.900
like the minimum, legal drinking age,

0:10:48.500,0:10:52.200
and environmental changes[br]like access to clean water.

0:10:52.900,0:10:54.200
In our next video.

0:10:54.500,0:10:59.200
We'll see an example of how regression[br]is used to implement a DD approach.

0:11:00.800,0:11:06.900
Are you a teacher click to explore ways to[br]use these videos in class if your learner

0:11:07.000,0:11:11.200
Make sure this video sticks by taking[br]a few quick practice questions,

0:11:11.600,0:11:14.200
or if you're ready.[br]Click for the next video.

0:11:14.600,0:11:20.000
You can also check out Mr. Use website for[br]more courses, teacher resources and more.