Quotes from Charles Wheelan

All accounts of the crisis document a chain of events in which rising real estate prices led to reckless borrowing and ultimately the equivalent of a modern bank run.

our ability to analyze data has grown far more sophisticated than our thinking about what we ought to do with the results. You

We want the impossibility set: the benefits of free-flowing capital without the disruptions; the flexibility of floating exchange rates without the unpredictability; and the ability to adapt monetary policy to domestic needs without the headaches caused when other countries do the same.

were a lot of bad actors). Let's start at the bottom: too many people borrowed too much money to buy real estate.

The challenge with any "before and after" kind of analysis is that just because one thing follows another does not mean that there is a causal relationship between the two.

The purpose of any program evaluation is to provide some kind of counterfactual against which a treatment or intervention can be measured.

The typical real estate purchase was far more leveraged than the stocks purchased on margin in the run up to the 1929 crash. Putting 5 percent down on a house means the other 95 percent is borrowed.

In the case of a randomized, controlled experiment, the control group is the counterfactual

Your condo loan might be packaged with 999 other mortgages and sold off to an investor who wanted to receive the steady stream of income as those mortgages were (hopefully) paid off.

So do you want to fly?" he asked. "Because it's faster and cheaper." "No," I said. I tried to explain to him that the overnight train would offer a more complete Indian experience for our family and for Sophie's friend Isabel. He looked at me as if I had told him that I was hoping to contract syphilis in order to better understand what it was like to have a venereal disease.

Recognize that your own motivation, ambition, and talents will determine your success more than the college name on your diploma."8

The ratings agencies were supposed to be the ones who made sense of this process by evaluating individual securities and assigning them a rating based on their relative risk: AAA, AA, BBB, and so on.

But probability triumphs in the end. An important theorem known as the law of large numbers tells us that as the number of independent trials increases, the average of the outcomes will get closer and closer to its expected value.

Commodity money solves the hyperinflation problem. No government can produce huge new quantities of gold, silver, or mackerel.

I won $2 playing the lotto today. And I might win $2 again tomorrow. But if I buy thousands of $1 lottery tickets, each with an expected payout of $.56, then it becomes a near mathematical certainty that I will lose money.

By the time I've spent $1 million on tickets, I'm going to end up with something strikingly close to $560,000.

The law of large numbers explains why casinos always make money in the long run.

For now, the key insight is that changing the number of chips on the table does not change the value of what's in the shoebox, which is all anyone cares about at the end of the night.

The Fed could not create new money to act as the lender of last resort for failing banks, as new money had to be backed by gold.

But who says that everyone using statistics is smart or honest? As mentioned, this book began as an homage to How to Lie with Statistics, which was first published in 1954 and has sold over a million copies.

You should see that a bigger sample makes for a shrinking standard error, which is how large national polls can end up with shockingly accurate results.

If your $99 printer breaks and you have to pay out of pocket to fix or replace it, this will not meaningfully change your life.

Productivity is the efficiency with which we convert inputs into outputs. In other words, how good

But even the finest recipe isn't going to salvage a meal that begins with spoiled ingredients. So it is with statistics; no amount of fancy analysis can make up for fundamentally flawed data. Hence the expression "garbage in, garbage out.