What People Get Wrong About Payday Loans | Thomas Sowell - YouTube

Words are not the only things that enable political rhetoric to magically transform

reality.

Numbers can be used just as creatively—and many voters are even more gullible about statistics

than they are about words, apparently because statistics seem more objective.

The latest Congressional crusade is to clamp down on small finance companies that provide

“payday loans” and check-cashing services in many low-income neighborhoods where there

are few banks.

A common practice in making small loans of a few hundred dollars for a few weeks is to

charge about $15 per hundred dollars lent.

Politicians, the media, community activists and miscellaneous other busybodies are able

to transform these numbers into annual percentage charges of several hundred percent, thereby

creating moral melodramas and demands that the government “do something” about such

“abuses.”

Of course, these loans are seldom borrowed for a year.

They are often loans for a couple of weeks or less, to meet some difficulty of the moment

by people who live from payday to payday, whether they are being paid by a job or are

receiving checks from Social Security, unemployment compensation or welfare.

The alternative to getting a payday loan may be having the electricity cut off or not having

money to buy some medication.

It is worse to borrow from illegal loan sharks, who have their own methods of collecting.

While $15 per hundred dollars may sound like a high rate of interest, it is not all interest.

The finance company incurs costs just to process a loan, and these costs are a higher proportion

of the total cost for a small loan than for a large loan.

When Oregon imposed a limit of 36 percent annual interest on what a finance company

could charge, that meant charging less than $1.50 for a hundred dollar loan for a couple

of weeks.

A dollar and a half would probably not even cover the cost of processing the loan, much

less the risks of default.

Not surprisingly, most of the small finance companies making payday loans in Oregon went

out of business.

But there are no statistics on how many low-income people turned to loan sharks or had their

electricity cut off or had to do without their medicine.

This is just one of the many ways in which self-righteous busybodies leave havoc in their

wake, while going away feeling noble.

Statistics played a key role in creating the housing boom and bust that led to the current

economic crisis.

Back in the 1990s, politicians, the media, community activists like Jesse Jackson and

others all made a lot of noise about statistical studies showing that (1) non-whites had lower

rates of home-ownership than whites, (2) were turned down for mortgage loans more often

than whites, and (3) resorted to more expensive subprime mortgage loans than whites.

All this led to pressures and even quotas for banks to lend to more low-income and minority

applicants.

That in turn led to lower mortgage lending standards, more risky mortgages, higher default

rates and the collapse of financial institutions that bought these more risky mortgages or

securities based on them.

We have seen and heard the same kinds of things when statistics about other racial differences

have been cited in the same strident voices when other statistics showed blacks laid off

more than whites during economic downturns or the children of black women having higher

infant mortality rates than the children of white women.

What we have very seldom seen or heard in such parading of statistics are other statistics—which

are readily available—showing that (1) whites are turned down for mortgage loans more often

than Asian Americans, (2) whites resort to subprime loans more often than Asian Americans,

(3) whites have been laid off more in a downturn than Asian Americans, and (4) the children

of white mothers have higher infant mortality rates than the children of mothers of Filipino

or Mexican ancestry, even though these mothers receive less prenatal care than white mothers.

In other words, numbers do not “speak for themselves.”

Politicians, the media and others speak for them—very loudly, very cleverly and often

very wrongly.