Clark Griswold can forget about driving all the way to Walley World.

If “National Lampoon’s Vacation” had been shot today, he just couldn’t have taken the time off work. That’s according to data from the Bureau of Labor Statistics, which show that Americans are taking fewer, shorter vacations.

Workers pay a career penalty for vacation

Nine million Americans took a week off in July 1976, the peak month each year for summer travel. Yet in July 2014, just seven million did. Keeping in mind that 60 million more Americans have jobs today than in 1976, that adds up to a huge decline in the share of workers taking vacations.

Some rough calculations show, in fact, that about 80 percent of workers once took an annual weeklong vacation — and now, just 56 percent do.

Long vacations are going out of style (BLS)

It’s not as if Americans are cutting back on an excessive vacation habit, either. The United States is the only developed economy that doesn’t guarantee its workers a paid vacation. Most of its peer nations promise about 20 days off a year, according to a report by Rebecca Ray, Milla Sanes, and John Schmitt of the Center for Economic and Policy Research.

About a quarter of the American workforce doesn’t get paid vacation, according to data they cite from the National Compensation Survey. The no-vacationers usually work part-time or for small employers in low-wage jobs.

The average American gets 14 days off from work, according to an annual survey by the travel company Expedia, but actually uses only 10 of those days each year. It’s an open question why Americans don’t use it all. They say their bosses are supportive and that scheduling got in the way. Others say they’re are just stockpiling it for some future trip —but wouldn’t someone, then, eventually take that trip?

One possibility is that vacation suffers from a “Prisoner’s Dilemma.” It’s dangerous to be “that guy” who uses all the time off they get when everyone else is on the job, so workers limit their vacations. On balance, The Wall Street Journal says, the evidence does support that theory. Workers pay a career penalty for vacation. If Americans could establish a pro-vacation norm, those pressures would lessen.

That seems to be happening in some workplaces, where bosses require workers to use their time off. That might be, for the most part, just a management fad. Yet it is surprisingly normal in one industry: finance. That’s not out of kindness, however. Regulators have long recommended banks require vacations as a way of making it harder to conceal embezzlement.

It’s not clear what’s driving the trend towards fewer, shorter vacations. Tourism tends to be very cyclical, but the decline of the great American vacation seems to have been a gradual affair. There aren’t any shortage of possible explanations: lessened job security, stagnant median incomes, rising part-time employment, and an increasing share of households with more than one member employed could all be parts of the story.

There’s no obvious sign that any of this has hurt the travel industry, though. Hotel occupancy is back to pre-recession highs, and employment in the leisure and hospitality industry has been one of the bright spots of the recovery. It seems like they’re carrying on, Griswolds or not.

* Here’s how the math works.

The Current Population Survey surveys workers once a month about a specific “reference week.” If an employed person says they were absent that week — that is, they worked zero hours — and the reason why is “vacation,” they’re counted here. There’s no reason to think that workers are more likely to take off during the survey’s reference week than any other, so we can divide the number of vacation absences by the number of workers, and raise that to the fourth power to get the percentage of workers who took a weeklong vacation in one month.

Now we multiply the percentage of Americans who didn’t across the last twelve months, since vacation is (obviously) seasonal. That gives you the share who haven’t taken a vacation in the last year. The calculations assume that nobody takes more than one weeklong vacation each year.

What is a minimum wage?

A minimum wage, in general, is a law that sets the lowest possible amount that work can pay. In the United States, 130 million workers are covered by the Fair Labor Standards Act, the 1938 law that established a national minimum wage.

It has stood at $7.25 an hour since 2009. The District of Columbia and 21 states have a minimum wage higher than the federal one.

Minimum wage increases are a politically popular means of helping low-income families that meet with fierce resistance from employers of low-skilled workers. The constant presence of minimum wage hikes on the political agenda has created a very extensive empirical economics literature that lets us say a great deal about the impact of small increases in incomes and employment.

Who earns the minimum wage?

3.6 million Americans earn at or below the federal minimum wage, according to an annual report from the Bureau of Labor Statistics. That’s 4.7 percent of all hourly workers.

Demographically speaking, minimum-wage workers tend to be younger than the average American with a job. The median age of a minimum-wage worker in 2012, according to data from the Bureau of Labor Statistics, was 24. Take a look at this chart, which breaks down the 3.6 million into bins from age 16 to 69:

Or look at it in a slightly different way: what percentage of workers in a certain age group are minimum-wage workers? 21.1 percent of workers age 16 to 19 earn the minimum wage or below, whereas just 1.6 percent of workers age 55 to 59 do.

Women are also more likely to be earning the minimum wage than men. 2.3 million out of the 3.6 million Americans earning the minimum are women, or 6.0 percent of all female hourly workers versus 3.4 percent of all male hourly workers.

Minimum-wage workers roughly match the United States in terms of racial composition, though black and Hispanic Americans are slightly overrepresented. 4.7 percent of non-Hispanic white hourly workers earn the minimum wage, as compared to 5.3 percent of black hourly workers, 3.4 percent of Asian hourly workers, and 5.0 percent of Hispanic hourly workers.

The demography of minimum-wage workers has changed over time, skewing older and more educated since 1979, according to John Schmitt and Janelle Jones of the left-leaning Center for Economic and Policy Research. The share of minimum-wage workers who are teenagers fell from 26 percent then to 12 percent, for example, and the share with less than a high school education dropped from 40 percent to 20 percent.

What jobs pay minimum wage?

One occupation dominates the field: food preparation and service, which employs 43.8 percent of all minimum-wage workers. Another 15.4 percent work in sales — think retail associates at a Walmart. 7.5 percent work in personal care, such as barbers, child-care workers, and home-care aides for the elderly and disabled. Transportation, building maintenance, and office support each employ another 6.0 percent of minimum-wage workers.

Minimum-wage workers also tend to be in part-time positions rather than full-time ones. (“Part-time” is defined as less than 35 hours a week.) 64.4 percent of minimum-wage jobs were part-time and 35.5 were full-time, as compared to 27.1 percent and 72.7 percent for part- and full-time among all workers. A job is roughly five times more likely to pay minimum wage if it is part-time rather than full-time.

How has the minimum wage changed over time?

The first federal minimum wage was set on October 24, 1938, according to a table from the Department of Labor, at $0.25 an hour. Congress has changed the minimum wage 28 times since then, though increases have become both larger and less frequent since the 1970s.

The last increase took effect on July 24, 2009, following a 2007 law that raised the minimum wage in three steps from $5.15 to its current level of $7.25.

Congress sets the minimum wage in nominal terms — that is, in the actual dollars and cents you are paid per hour. Inflation gradually reduces the purchasing power of the dollar, so the inflation-adjusted (or real) value of minimum wage declines over time.

Is the minimum wage going to go up?

Probably not this year. US Senator Tom Harkin and Representative George Miller, both retiring this year, supported a high-profile effort to raise the minimum wage to $10.10 an hour, which won the support of President Barack Obama. Obama has previously supported plans to raise the minimum wage to $9 an hour in his 2013 State of the Union address and to $9.50 as a presidential candidate in 2008. Democrats say they intend to push for minimum wage increases in the 2014 election.

Public opinion polls show strong support of increases in the minimum wage. About 70 percent of Americans, a wide variety of polls suggest, currently favor a hike. The polls also show that Democrats are most strongly in favor of the increase, whereas Republicans are split in half.

Congressional Republicans generally oppose minimum wage increases. The National Restaurant Association is also a significant opponent of increases, as the single most common occupation of minimum-wage workers is food service and preparation.

Action in Congress on the minimum wage is currently stalled. There is little support for an increase in the House of Representatives, where Republicans unanimously voted down a bill in 2013. The Senate failed to move a bill after a vote on April 30, 2014, on a minimum wage hike. The bill received 54 votes to 42 votes, but it needed 60 votes to overcome a filibuster.

Where did the minimum wage come from?

New Zealand was the first country to establish a national minimum wage in 1894, followed by Australia two years later. (See David Neumark and William Wascher’s book on minimum wages for a full history.) In the United States, the history of the minimum wage is one of gradual expansion and of Supreme Court intervention.

Several US states established minimum wages in the 1910s, mostly as Progressive “protective laws” for women. Amid the Lochner era, the US Supreme Court found state minimum wages unconstitutional in 1923 case Adkins v. Children’s Hospital as a violation of liberty of contract.

The US federal government first tried to establish a national minimum wage in 1933 of $0.25 an hour as part of the National Industrial Recovery Act. The Supreme Court, however, struck down the wage law in the 1935 decision Schechter v. US.

Nevertheless, states continued to try to pass minimum wages — and in 1937, the Supreme Court reversed course in the decision West Coast Hotel v. Parrish, upholding Washington’s minimum wage and ending the Lochner era. The US reestablished its national minimum wage at $0.25 an hour a year later. And the Supreme Court finally recognized its constitutionality in the 1941 decision United States v. Darby Lumber Co. The US has had a minimum wage ever since.

Why do some states and cities have a higher minimum wage?

US state and local governments are allowed to set minimum wages above the federal level, which effectively functions as a “minimum minimum wage.” 21 states have minimum wages above the federal minimum, as shown in the map below:

States that do not have minimum wage laws, or those with rates below the federal, must follow the federal minimum wage. Of the states in green with elevated minimum wages, Washington has the highest at $9.32 an hour as of January 1, 2014. A detailed table of state minimum wages is available here from the National Conference of State Legislatures.

The city with the highest minimum wage for all workers is SeaTac, Washington, where voters approved a $15-an-hour minimum wage in 2013. The much larger city of Seattle is also moving toward a $15-an-hour minimum wage, but it will be phased in over several years.

Is it possible to earn less than the minimum wage?

Confusingly, yes. Workers can earn below the minimum wage in specific cases. But in most, the minimum wage is really the minimum. If you’re an hourly worker who is paid less than the minimum wage without special clearance, you should talk to the Wages and Hours Division of the Department of Labor.

What workers can be paid less than the minimum wage? The most common exception is for tipped employees, such as waiters and bartenders. Employers may pay them just $2.13 an hour, called the “tipped minimum wage,” if they expect employees to make up the difference in tips. That difference, $5.12 an hour, is called the maximum “tip credit.” A 2009 report by the National Employment Law Project, however, found that employers routinely overestimate worker tips.

Millions of workers are also not covered by the minimum wage. If a business has an annual revenue less than $500,000, then its employees do not receive minimum-wage protections. Those who do not work at hourly wages, such as independent contractors, also do not qualify. Farmworkers at small farms, fishermen, amusement-park workers, newspaper delivery boys, babysitters and a few other classes of workers have special exemptions from the minimum wage.

Younger workers and workers with disabilities also may qualify for reduced minimum wages. Employers can pay teenagers just $4.25 an hour for the first 90 days of employment. Full-time students and students in vocational programs also have their minimums reduced 15 and 25 percent. Workers with disabilities can be paid any amount “commensurate” with their productivity — though a recent investigation by the New York Times finds this exemption is abused.

What do other countries do about the minimum wage?

Almost every country in the world has some form of minimum wage. Among rich countries the big divide is between countries like the United States and France that have a statutory minimum wage and countries like Canada and Sweden (and until this year Germany) where minimum wage rates are hashed out as part of the collective bargaining process.

Australia has the world’s highest minimum wage at $16 an hour, and European nations like France, Belgium, Ireland and the Netherlands are a bit behind, with minimum wages in the $11 to $10 range. Canada has a minimum wage of $9.95 an hour.

Does the minimum wage cause unemployment?

There is considerable disagreement, but the consensus among economists is that small increases in the minimum wage have small if any negative effects on employment.

Of course, a very simple theoretical account of supply and demand says that if you raise the price of labor you’ll reduce the quantity employers purchase. So it’s a surprising fact that many economists have stopped worrying about large increases in unemployment from minimum-wage hikes.

The first major empirical paper taking issue with the simple supply-demand acount arrived back in 1993, when two top labor economists, David Card and Alan Krueger, decided to do a case study of what happened to employment in fast-food restaurants along the New Jersey-Pennsylvania border when New Jersey hiked the minimum wage but Pennsylvania did not. The short answer: Nothing happened. Despite the higher minimum wage in New Jersey, New Jersey’s fast-food restaurants did not lay off workers.

Card and Krueger’s study sparked hundreds of follow-up studies, scouring the US and the globe for employment effects of minimum wages. For instance, an important 2010 paper by economists Arindrajit Dube, T. William Lester, and Michael Reich took counties that abutted each other but were in different states and looked at employment when one state chose to raise minimum wage while another did not. Dube, Lester, and Reich also found no employment effect.

Researchers do regularly detect small effects on employment, however. The research teams of David Neumark and William Wascher and Richard Burkhauser and Joseph Sabia both have well-known papers showing a reduction in employment. Another new line of research comes from economists Jonathan Meer and Jeremy West, who find that higher minimum wages slow the rate of hiring for new businesses. A 10-percent increase in the minimum wage, Meer and West find, slows job growth by a quarter.

One useful meta-analysis of all these studies comes from economist Hristos Doucouliagos, who showed that precise studies cluster close to zero impact on employment with a majority showing a very small decline.

How is it possible to increase wages without reducing employment?

John Schmitt, an economist at the Center for Economic and Policy Research, has a useful summary of 11 different potential explanations. Schmitt concludes that four are most important:

• Turnover. A higher minimum wage makes working at the minimum wage more attractive. That makes it easier for employers to hire and retain workers, reducing turnover in employment, which is usually high in low-wage industries. The reduction in the cost of turnover offsets the increase in the cost in wages. Underlying this view are the economics ideas of “monopsony” and “labor-market frictions” — that is, that the labor market isn’t perfectly competitive, and employers have some power to set wages. A higher minimum wage forces employers to raise wages rather than tolerate vacancies.
• Efficiency. Employers respond to a higher minimum wage by raising expectations for their workers’ productivity. Though the wage may have risen in dollar-per-hour terms, the business may squeeze more work out to compensate. A related idea is that of the “efficiency wage” — that is, employees themselves may respond positively to a higher wage by more work effort.
• Wage compression. Employers of minimum-wage workers usually have a defined pay scale for all employees. When the minimum wage rises, employers respond by holding down wages for workers higher up the pay scale to keep labor costs down. The busboys get a raise this year, in essence, because the maître d’ didn’t.
• Prices. When labor costs rise, employers have three general options. They can pay the costs out of their own profits. They can cut costs in other areas. Or they can just pass on the higher costs to their customers in the form of higher prices. When the minimum wage rises a dollar, so might the price of your haircut.

Would raising the minimum wage help the poor?

Probably. Of the 54 published estimates on the relationship between the minimum wage and poverty, 48 find that increases in the minimum wage reduce poverty. The average effect is that a 10 percent increase in the minimum wage would reduce the poverty rate by 1.5 percent.

The latest and most complete treatment of the issue comes from economist Arindrajit Dube, who finds that poverty rates fall between 1.2 and 3.7 percent for a 10 percent increase in the minimum wage.

Another study by economists Richard Burkhauser and Joseph Sabia, however, find no evidence that increases in minimum wages between 2003 and 2007 reduced poverty. And research by David Neumark and William Wascher argues that minimum-wage hikes have opposing effects on poverty: lifting some out of poverty while driving others into it.

Who loses from a higher minimum wage?

The people who end up paying higher minimum wages, of course. Businesses who employ minimum-wage workers appear to pay for the increase in the minimum wage out of their profits, according to a trio of economists who studied the introduction of the minimum wage in the United Kingdom.

Customers of minimum-wage businesses may also bear some of the cost of increases if the businesses raise prices to compensate for higher wages. Last but by no means least, to the extent that minimum wage hikes cost jobs some potentially employed people lose out.

Can I survive on the minimum wage?

Judge for yourself! The New York Times built a simulator that allows you to enter in expenses for housing, food, and so on — and you can see whether you could even make a livable budget at $7.25 an hour.

Most minimum-wage earners, however, supplement their income with government aid — including 52 percent of fast-food workers, according to a study by Sylvia Allegretto and a team of other economists. The cost of this public assistance to fast-food workers, they found, totaled $7 billion a year.

How would increasing the minimum wage affect this? A new study by economists Michael Reich and Rachel West for the left-leaning Center for American Progress finds that a 10 percent increase in the minimum wage would reduce enrollment in the food-stamp program by about three percent and reduce its costs by about two percent. A higher minimum wage means workers earn more, making them no longer eligible for government money.

Why not set the minimum wage high enough to make everyone rich?

It almost certainly wouldn’t work. It’s important to understand what research does and doesn’t say about the minimum wage. It says increasing the minimum wage slightly — say, to $9 or $10 — would have at most modest effects on employment. Since governments never enact extremely large minimum wage increases, there are no empirical studies of them. Even the labor economists who believe the former think that at some point minimum wages would create unemployment.

But let’s suppose that a government did pass a crazy-high minimum wage. What would happen? Some combination of unemployment and inflation. If workers cost far more than they’re worth, businesses won’t employ them. The only way such a large increase could work is if prices rose so much that it wiped out all of the inflation-adjusted gains of the minimum-wage hike. A minimum wage simply can’t overcome the fact that workers earn low wages because what they produce isn’t that valuable.

Can raising the minimum wage stimulate the economy?

That’s unclear. Economists like Christina D. Romer, the former chair of the Council of Economic Advisers, seem doubtful.

The basic argument is that since the poor consume a larger fraction of their income than the rich, a higher minimum wage results in more consumption. Doug Hall and David Cooper of the Economic Policy Institute find a $40 billion stimulus effect from hiking the minimum wage from $7.25 to $9.80.

Economists Daniel Aaronson, Sumit Agarwal, and Eric French of the Federal Reserve Bank of Chicago find mixed effects on consumption. A $1 increase in the minimum wage leads to $700 dollars in additional consumption per quarter. That’s far more than would be supported by the actual minimum wage — so the increase in consumption proves temporary, and poor households end up with increases in debt of about $440 per quarter.

What do economists think about the minimum wage?

A survey of economists by the Initiative on Global Markets at the University of Chicago’s Booth School of Business found they supported a minimum-wage increase.

They weren’t sure, however, whether increases would create unemployment. Most said that, on balance, the benefits exceeded the costs.

Why do economists disagree about the minimum wage?

The simple answer is that the effects of the minimum wage are particularly hard to measure. That’s for two reasons. It’s hard to control for all of the other economic variables affecting wages, and historically, most changes in the minimum wage have been small.

Economics doesn’t get to have clean, controlled experiments. That’s forced researchers to come up with innovative ways to test the minimum wage. Many rely on “natural experiments.” The problem is that, even with these plans, it remains hard to control for all outside influences so that any measurement is just of the minimum wage’s impact.

To put it differently, estimating the minimum wage’s effect on employment relies on constructing a counterfactual — that is, employment had the minimum wage not changed. Your estimate is only as good as your counterfactual — which can never be certain.

Another problem is that most changes in the minimum wage are small, and it’s hard to distinguish a slight signal amid the noise from no signal.

Are there other ways to boost low-wage workers’ incomes?

Yes.

One option is simply giving low-wage workers more money. The main way the US government does this already is with the earned income tax credit (EITC), which gives a maximum of $6,143 to large families with working parents making around $20,000. This graph from the Tax Policy Center shows how it works:

President Barack Obama proposed expanding the EITC to the childless in his 2015 budget, who currently receive substantially smaller benefits. Republicans, however, frequently pose EITC increases as a rival policy option to the minimum wage.

Nothing makes the earned income tax credit and the minimum wage alternatives. Government could do both at the same time. Economists David Lee and Emmanuel Saez have argued, in fact, that the two policies are complementary — in other words, the minimum wage and the EITC are better together than separately. That’s because the tax credit tends to depress pre-tax wages, even though it boosts after-tax wages, which reduces the boost to low-wage workers’ incomes. A higher minimum wage prevents pre-tax wages from falling in response to a more generous EITC.

And there is a universe of other policy options to indirectly boost low-wage workers’ incomes, including “pre-distribution” policies and policies to push the economy towards full employment.

What else should I read about the minimum wage?

David Neumark and William Wascher’s book Minimum Wages is the best-known history of minimum wages. For more history, check out A Measure of Fairness by Robert Pollin, Mark Brenner, Stephanie Luce, and Jeanette Wicks-Lim on the movement to create living wages and raise the minimum wage.

David Card and Alan Krueger wrote a book outlining their conclusions about the minimum wage in Myth and Measurement.

Barbara Ehrenreich published the book Nickeled and Dimed in 2001, which detailed her experience living as a low-wage worker.

Here’s a list of some key economists to follow on minimum-wage issues, with their most important papers:

• David Card and Alan Krueger: “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania.”
• Alan Krueger and Lawrence Katz: “The Effect of the Minimum Wage on the Fast-Food Industry.”
• Arindrajit Dube and Michael Reich: “Minimum wage effects across state borders: Estimates using contiguous counties.”
• Arindrajit Dube: “Minimum Wages and the Distribution of Family Incomes.” “
• Sylvia Allegretto, Arindrajit Dube, and Michael Reich: Do Minimum Wages Really Reduce Teen Employment? Accounting for Heterogeneity and Selectivity in State Panel Data.”
• Michael Reich: “The Effects of Minimum Wages on SNAP Enrollments and Expenditures.”
• David Neumark and William Wascher. “Minimum Wages and Employment.” “Employment Effects of Minimum and Subminimum Wages: Panel Data on State Minimum Wage Laws.”
• Richard Burkhauser. “A Reassessment of the New Economics of the Minimum Wage Literature with Monthly Data from the Current Population Survey.”
• Joseph Sabia. “Minimum Wages and Poverty: Will a $9.50 Federal Minimum Wage Really Help the Working Poor?”
• Jonathan Meer. “Effects of the Minimum Wage on Employment Dynamics.”

How have these cards changed?

This is a running list of substantive updates, corrections, and additions to this card stack. Here is a summary of edits:

• April 30: Card 5 was updated to reflect that on April 30, 2014, the Senate failed to overcome a Republican-led filibuster on a bill that would have raised the federal minimum wage to $10.10.

Amir Sufi is a professor of finance at the University of Chicago Booth School of Business and the co-author of a new book and a new blog on debt and the Great Recession, House of Debt, with Princeton economist Atif Mian. The book goes on sale May 21. I interviewed Sufi over the phone to talk about it.

The following is a lightly edited transcript of our conversation.

Evan: Your book makes the case that there’s something uniquely dangerous to the economy about debt — something that makes debt the cause of wild bubbles and crushing depressions. What, exactly, is wrong with debt?

Amir: Debt exacerbates downturns because it concentrates the brunt of a recession on people who have debt, who tend to be the poorest members of society. In response to having losses imposed upon them, these people cut spending dramatically and send the economy into a tailspin from which it is very hard to recover.

When we’re looking for clues as to what drives the most severe downturns, the one jumps right out at you is that it’s something about debt. One that we use in our book, for example, is that countries with higher debt levels tend to have deeper recessions and weaker recoveries. We’ve garnered a lot of evidence, and now we’re trying to give a theory for why.

From a macroeconomic perspective, the key issue that has led to skepticism of why debt might be important is the view that debt is just a distributional contract. Suppose I have a house worth $100,000 and a mortgage worth $80,000. If the house’s value falls $20,000, all the loss is born by the debtor. Economists like Ben Bernanke have said who cares who takes the loss, the homeowner or the bank — it shouldn’t matter.

We’re saying that’s wrong. When you have a lot of wealth inequality in the economy, people have to use debt to maintain spending. Then when the aggregate economy collapses, and people have debt, the losses are forced on the poor, who have the highest marginal propensity to consume and are now credit-constrained, so they have no recourse but to cut spending substantially.

Part of the logic here is that if Bill Gates were to lose $35,000, it wouldn’t affect his spending. bill gates loses 35k doesn’t change spending — but when the average homeowner loses $35,000 in home equity, they change their spending plans substantially.

Evan: This isn’t a conventional argument that accumulating too much debt is bad, but rather a more radical one that the idea of debt is a bad one — that it’s flawed by design, right?

Amir: There are basically three flaws. The first is that debt contract have horrible risk-sharing. They’re protecting people who don’t need any protection and forcing losses on those who do. That is a failing of the financial system. It’s not doing the proper risk-sharing job we need it to do.

The second is the foreclosure effect of debt. Imagine that a downturn occurs, and the economy has a misallocation of resources and needs to reallocate. Maybe we have too many houses, and we don’t need so many of them. One of the major points we make in this book is that debt does a horrible job of facilitating that reallocation. The foreclosure process exacerbate prices declines, and that has its own knock-on effect on economic activity.

The third is that one thing debt does is that it gives buying power to the most optimistic people in the economy. That theory comes from the economist John Geanakoplos, and it works like this. If you’re in an economy without only debt, only someone with has enough money to buy a house can bid prices up. But what debt does is allow the guy who doesn’t think house prices are going up to lend to the guy who does.

Evan: One of the things you do in the book is identify the Great Recession as a prototypical example of a debt-driven recession. Talk me through some of the numbers on the debt buildup in the 2000s.

Amir: One statistic I like to give is the national ratio household debt to income — if you think about it in two pieces, that’s the aggregate stock of debt versus the aggregate flow of income that can be used to pay that debt down. It went up from 1.4 to 2.2 in just six years during the 2000s. To put that in perspective, it’s trended upwards historically, but it took 35 years to go up the same amount. The nation’s debt burden went up in the six years before the recession as much as it had in the 35 before that.

That’s the national average — and in some areas of the country, like California and Florida, the rise was much sharper.

Evan: So the severity of the Great Recession, once it began, really shouldn’t have been that surprising.

Amir: If you look at the Great Depression, you see the same picture. There was a large rise in households’ debt burdens in 1929 and 1930, right as the downturn began.

What’s even more convincing here is that, internationally, it’s exactly those countries with the biggest rise in debt right before the Great Recession that had the most severe downturn. Work by Kevin Lansing and other researchers at the International Monetary Fund basically shows that you could have predict which countries would have the worst time in the recession from their debt level right before.

And this rule turns out to keep working over and over. U.S. counties with the greatest rise in debt also had the deepest recession. Mervyn King, who ran the Bank of England, found that the countries that had the worst recession in the early 1990s also had the worst debt going into it. It’s just a very robust correlation through history that needs an explanation.

Evan: In 2008, by the time we realized the mess we were in, it was too late to do anything about the level of debt. What did we do wrong during the recession, given all that debt? And what did we do wrong to end up where we did before the recession?

Amir: During the recession, we just completely and totally bungled the housing mess. And what’s interesting is that officials from the Obama administration say that openly now. There should have been much more aggressive facilitation of principal write-downs and a more aggressive effort on cramdowns.

What would have changed things during the recession was some recognition from policymakers that household debt burdens were crucial to understanding why the recession was so severe. Instead of focusing on household debt, most policymakers were overly concerned with the banking sector. This made the debt problem a zero-sum game, because you end up thinking that you can’t help the homeowners because that would hurt the banks. What’s happened in Spain is just an awful example of where this kind of thinking gets you.

On what happened before the recession, I’m not in this camp that blames Fannie Mae or Freddie Mac or policymakers pressuring them to lend. What happened in the 2000s was that the private sector started producing mortgages that people were never going to be able to repay. Now why did that happen? The securitization of mortgages had been designed to produce AAA-rated securities.

So economists have gotten to the point where we see that debt exacerbates downturns and fuels bubbles. And yet our government has massive subsidies for debt: the mortgage interest deduction, for one, or the requirement that money market funds have to hold AAA-rated debt, which gives an incentive to financial corporations to issue that debt. We end up subsidizing exactly the kind of financial set-up that economists now think is dangerous. So those seems like some terribly ill-advised policy choices.

Evan: How about some better policy choices, then?

Amir: In the book we offer two broad policy prescriptions, one for the short run and one for the long run. The one for the short run is more aggressive debt forgiveness amid severe downturns. In 2014, that recommendation is probably not going to help now. But imagine a scenario in which the default rate on student loans skyrockets: right away, the government should start to facilitate debt reduction. I don’t mean bailouts. I mean government pushing losses onto creditors.

The long-run answer is to make debt financing more equity-like, to correct the bad risk-sharing. We’re calling our proposal “shared responsibility mortgages.” The idea is that you have a mortgage contract where your debt is indexed to the average home price in your zip code. If the value of homes go down, the principal balance and the monthly payment would go down. That would reduce foreclosures in a major way because you would have more equity in the home amid downturns. It would also prevent bubbles in the first place, because lenders would understand they are taking on some downside risk, changing their incentives to lend.

We understand this is an enormous challenge and that the current financial system is dependent on debt. What we hope to do is prod people to think about debt in this way. What’s good news is that the financial industry has become more interested recently in this equity-sharing idea — though for a funny reason. They’re angry that coupon payments on mortgage bonds are so low, so they want some upside on home value.

You’re reading this article. Should it change your opinion of the piece’s quality to know that its author was white, black, or of another race? No, if you’re evaluating it on its merits.

Yet a new study by the consultancy firm Nextions shows that reviewers of a legal brief did just that.

The idea

In an experimental context, when reviewers were told the author of a legal brief was black they consistently rated identical pieces lower in quality and identified more spelling, grammar, factual, or analytical errors. It’s evidence that, even if the days of overt bigotry and explicit discrimination are mostly past, the United States still struggles with a deep problem of implicit racism.

Arin N. Revees, the president of Nextions and the author of the study, argues that the implicit racism happened because reviewers take the racial information she provided as a cue for how they should judge the work. When the author is supposed to be white, reviewers excused errors as out of haste or inexperience. They commented that the author “has potential” and was “generally a good writer but needs to work on” some skills. When the author is supposed to be black, those same errors became evidence of incompetence. A reviewer said he “can’t believe he [the author] went to NYU,” and others said he “needs lots of work” and was “average at best.”

The evidence for

Nextions recruited five lawyers at five different law firms to co-write a research memo about trade secrets at Internet start-ups. Then they inserted several errors into the memos — errors in spelling, grammar, legal terminology, fact, and analysis. Last, they created two different headers for the memo. Both identified the author as “Thomas Meyer,” a third-year associate with a degree from the New York University School of Law, a top-ranked school. Yet in one version of the header, Thomas Meyer was identified as “Caucasian”; in another, he was identified as “African American.”

They sent these otherwise-identical memos to 60 different partners at law firms who had agreed to review the pieces and identify errors. The reviewers, though, weren’t told that the experiment was about race — they were just asked for their opinion on the quality of the memo.

They judged the memo far more harshly when they were told the author was black than when they were told the author was white. On a scale of one to five, reviewers gave the black Thomas Meyer a 3.2 and the white Thomas Meyer a 4.1.

More troublingly, not only was the overall score lower, but reviewers seemed to find more errors when they believed the author was black. Out of seven spelling and grammar errors in the text, they found 2.9 of them on average in white Thomas Meyer’s memo and 5.8 of them on average in black Thomas Meyer’s memo. Out of six technical writing errors, reviewers found an average of 4.1 in the white version and 4.9 in the black version. Out of the five factual errors, they found an average of 3.2 in the white version and 3.9 in the black version.

There was no apparent effect from the race of the reviewer, and the sample of reviewers included a mix of races.

Possible grounds for doubt

There are two serious shortcomings in the Nextions study. It should be taken as suggestive, but not conclusive, evidence of the power of implicit racism. Those two flaws are that the sample size was puny and, more dangerously, the study design makes it impossible to control for the harshness of the reviewer.

Only 60 reviewers participated, and only 53 actually sent back their reviews. That’s not enough for strong conclusions.

What was more problematic was that each reviewer only looked at one memo. This is a problem because some reviewers will be harsher in general, and a better study would control for differences in the reviewer. The Nextions report assumes that all reviewers are equivalent — but, with such a small sample size, this is a very risky assumption. If the reviewers that received memos from black Thomas Meyer were just harsher overall, this study would conclude that the blackness of Thomas Meyer, and not the harshness of the reviewer, was at play. The way to solve this problem would be to have each reviewer look at more than one memo.

One of the biggest changes for workers in America over the past 50 years is that unions have gone from dominant to dying. The percentage of Americans working in the private sector who are union members has fallen from 35 percent in the 1950s to 6.7 percent in 2013, according to data from Barry T. Hirsch, a well-known labor economist, and the Bureau of Labor Statistics.

Another change is that more Americans than ever work in professions with occupational licensing — state rules that say you have to meet certain qualifications, or pass an exam, before you can ply your trade. Barbers, for example, are generally now licensed in the United States, with the exact rules varying considerably from place to place.

That’s where Alan Krueger, formerly President Barack Obama’s top economic adviser, comes in with a fascinating idea: What if these two trends are related?

As American unions shrank, Krueger suggests in a paper with economist Morris Kleiner, occupational licensing expanded to fill the gap. Nearly 30 percent of workers are now licensed, as compared with less than 5 percent in the 1950s.

(Kleiner and Krueger)

Connecting the stories of unions and licensing makes sense. Both are institutions workers created to raise wages — and occupational licensing seems about as effective as unions, raising wages by about 15 percent relative to what similarly skilled workers earn in states where they’re not protected by licensing from competition.

Yet there’s something unions did that occupational licensing doesn’t, and that’s reduce inequality, Kleiner and Krueger find. Whereas unions tend to push up wages at the bottom and restrain them at the top, compressing the wage distribution, there’s no such effect for occupational licensing. Wage dispersion within a given trade is not effected by licensing.

In other words, the most successful workers will find that occupational licensing recreates the wage gains that unions once provided. But licensing seems to do little to help the bargaining power of the most vulnerable workers.

A new book by author Michael Lewis describes how trading algorithms that detect and exploit tiny, fleeting profit opportunities, called high-frequency traders, have transformed the stock market. And not by ripping off middle class investors. But that doesn’t mean there are no problems. Read on to understand what high-frequency trading is, and what the real issues with it are.

What is high-frequency trading?

If you’re an average human being, your eyes take around 400 milliseconds to blink once. High-frequency trading is a kind of market activity that moves in less than one millisecond to spot and take advantage of an opportunity to buy or sell. It happens through trading algorithms, programs that determine how to trade based on fast-moving market data.

The kind of profit opportunities that high-frequency trading looks for aren’t the things most investors ever think about. They’re not betting that technology companies will see their profits grow more quickly than expected, for example, or that a recession is coming.

Instead, they’re looking for tiny opportunities for arbitrage. Imagine that, at precisely 10:30:01.01 AM, a share of Bank of America’s stock was trading at $16.02 on the New York Stock Exchange – but it was $16.04 on a smaller exchange called BATS. A high-frequency trading computer might spring into action by buying up shares of stock on the New York Stock Exchange and selling them on BATS. To make money this way you need to move super-fast, because the opportunity could vanish at any moment.

Is high-frequency trading growing?

Not anymore, according to most data. High-frequency trading came into vogue during the 2000s, but after many traders entered the market, profits are way down, and there seems to be slightly less high-frequency trading than there used to be:

Profits in high-frequency trading have fallen to about 0.0005 per share, or a twentieth of a penny, mostly due to rising competition and less volatility, which create profit opportunities for the trading algorithms. There’s new reporting, however, that suggests that high-frequency trading may be retreating from the stock market only to spread to other financial markets, like bonds, currencies, and derivatives.

This “electronic front-running” happens because the high-frequency traders have an advantage in terms of speed

How does high-frequency trading make money?

In his book, Lewis says there are three main activities that happen inside of high-frequency trading computers:

The first they called electronic front-running – seeing an investor trying to do something in one place and racing ahead of him to the next … The second they called rebate arbitrage – using the new complexity to game the seizing of whatever legal kickbacks, called rebates within the industry, the exchange offered without actually providing the liquidity that the rebate was presumably meant to entice. The third, and probably by far the most widespread, they called slow-market arbitrage. This occurred when a high-frequency trader was able to see the price of a stock change on one exchange and pick off orders sitting on other exchanges before those exchanges were able to react.

Let’s unpack that. Imagine you’re a huge institutional investor, like the California Public Employees’ Retirement System, which invests pension dollars saved for California’s retired state-government workers. You’ve decided to buy up lots of shares of Apple. When you place your trade, you don’t just send the order at one time to a single exchange, like a small investor would. Instead, you often have to break up your order to many exchanges and over a period of time. That’s because there simply aren’t enough people looking to sell as many shares as you want in a particular moment at a particular exchange.

That’s the first kind of behavior that Lewis says high-frequency trading exploits. When the traders see CalPERS place a bid for Apple shares on the tech-heavy Nasdaq exchange, they quickly buy shares on other exchanges, inferring that CalPERS’ orders are coming down the wires. Then the high-frequency traders sell the Apple shares back to CalPERS at a higher price than they paid for them a millisecond ago. This “electronic front-running” happens because the high-frequency traders have an advantage in terms of speed, and because “the stock market” doesn’t really exist — what exists are many stock exchanges in a trading network.

Small investors don’t place the kind of orders that HFT could attack

The second idea Lewis mentions is “rebate arbitrage,” and it requires a bit of backstory. Before trading went electronic, there used to be actual people standing on the floor of stock exchanges who would both buy and sell the same stock at different times, helping to accommodate the flow of orders. They were called “market makers.” And while some stock exchanges do still have people nominally in this role, the real market-making happens from high-frequency trading computers. They make markets because the stock exchanges pay them to fill that role, giving them a “rebate” on the cost of their trading.

The third exploits the network structure of markets, and the fact that they don’t all adjust instantly to changes in price. If high-frequency traders can figure out where a stock price will be in the next millisecond before other investors can get a quote, that’s a huge advantage they can use for profit.

So, does that mean the market is "rigged"?

There’s no good definition of that term. It’s not rigged in the sense most people mean “rigged,” as the outcome of the market is not decided in advance. But it’s reasonable to argue, as Lewis does, that high-frequency traders have a speed advantage – and, as a result, an informational advantage – that they use in an exploitative way.

What isn’t at all right in Lewis’ book, though, is its view that high-frequency trading hurts small investors. Small investors, as Reuters’ Felix Salmon writes, don’t place the kind of orders that high-frequency traders could attack, or would even find it worth their while to do so. The target of high-frequency trading is mostly institutional investors investment banks, pension funds, insurers, and so on — who trade in large volumes. On the other hand, people who have money and those institutions are hurt. High-frequency trading ended up skimming $7 billion off these investors in 2009. That’s mostly coming out of the pockets of other rich people, but some middle class people with defined benefit pensions are also losing out

Does high-frequency trading make the market more efficient?

Nobody knows. There’s a world in which that kind of rapid action could be good news. Responding instantly to earnings announcements, economic data and political events would be an advance for the efficiency of the market – and with that, the deployment of capital. Economists Jonathan Brogaard, Terrence Hendershott and Ryan Riordan have found that high-frequency trading tends to get the movements of prices right. Lots of trading volume might also narrow “bid-ask spreads,” the differences between prices at which buyers want to buy and sellers want to sell, and make those orders clear more quickly. That’s all good news for efficiency.

One of the biggest concerns, though, is that high-frequency trading may reduce the amount of liquidity in markets – that is, how easy it is to buy or sell – rather than increase it. The problem, as Nicholas Hirschey of the London School of Economics has found, is that the front-running makes financial investment more costly. It may also push institutional investors out of stock exchanges, further shrinking liquidity.

Can high-frequency trading cause stock-market crashes?

High-frequency trading might not cause the stock market to swing — markets have always done that — but research does suggest it may magnify volatility and, in particular, make financial markets more vulnerable to freezing up suddenly.

The high-frequency trading algorithms simply move too fast for humans to intervene with better judgment. When stocks drop, the trading programs may decide to stop trading, withdrawing liquidity from the market, or they may add to the sell-off.

That wouldn’t surprise many people who remember what happened to the stock market on May 6, 2010 at 2:45 p.m. — the “Flash Crash,” in which U.S. stocks fell 9 percent and then recovered in the course of a few minutes. Shares in companies like Accenture, a management consultancy, fell from $40 a share to a penny.

How did the Flash Crash happen? Some accounts, such as the report by the U.S. Commodity Futures Trading Commission and the Securities and Exchange Commission, center around the the “e-mini,” a heavily-traded futures contract that tracks the Standard & Poors 500, a broad index of U.S. stocks.

The crash happened when a trading algorithm sold $4.1 billion of the contract, overwhelming demand for the e-mini. As liquidity ran out, the value of the contract plunged. High-frequency traders piled on, dumping the e-mini and and selling off other stocks, causing the rapid decline to cascade through the stock market. (See here for a minute-by-minute timeline of the crash.)

Another account of the crash from the market-data firm Nanex, however, focuses on two problems with price quotes, or when market participants send in the prices at which they want to buy or sell. During the Flash Crash, transmission of these quotes slowed sharply, as exchanges became overloaded. What caused the overloading, Nanex argues, was “quote stuffing” — high-frequency traders that sent in a blizzard of orders to buy and sell at the same time, only to cancel those orders milliseconds later before they went through. This behavior paralyzed market trading, and the processing delays caused a panic among traders who knew they had unreliable data.

A related theory is that markets froze up and crashed because of what’s called “order flow toxicity,” a complicated way of saying that people in the market became convinced that the other parties in their trades were “informed,” or had newer or better information than they did. The market crashed as traders chose to dump shares or withdraw from the market rather than lose money to an informed trader. In this view, the problem with high-frequency trading is adverse selection: the fast traders drive out the slow until no market is left.

oneVillage Initiative/Flickr

Are there other possible problems with high-frequency trading?

Yes, and three in particular often come up.

1) Much high-frequency trading exploits data before it is public for an advantage.

Until last summer, the data firm Thomson Reuters, for example, sold to elite investors the right to see an important economic statistic, the University of Michigan’s consumer confidence survey, five minutes earlier than the rest of the market. An “even-more elite” group of high-frequency trading clients could purchase an extra 500 millisecond head start.

Reuters isn’t doing this any longer. Yet similar practices still exist – one is called “paying for order flow.” The idea is that a financial firm can pay brokers to route their clients’ orders through them, so that they finish the broker’s role of executing your trade. Why would these firms pay for that? Because they get to see orders to buy and sell before anyone else, giving them milliseconds’ worth of advance knowledge of future prices.

A similar example that Lewis talks about is “co-location.” High-frequency traders will locate their

computers as physically close to the exchange as possible, sometimes even right on the exchange’s own servers. This gives them the first look at price changes.

2) Some strategies in high-frequency trading, such as “pinging” and “spoofing,” are unethical or illegal.

“Pinging” is a strategy in which the high-frequency trader sends many small orders to an exchange. If these orders are all filled instantly, the high-frequency trader can infer that on the other side of the trade is a big investor looking to move a large volume of shares. The high-frequency trader then takes this knowledge and uses it against the big investor by moving the price against him – buying if he wants to buy and then selling it back to him at a higher price, selling if he wants to sell and then buying it back at a lower one.

“Spoofing” is a strategy, ostensibly banned in 2010, in which high-frequency traders send in orders with the idea of trying to confuse, or “spoof,” other traders – and especially other trading algorithms – into thinking that demand to buy or sell a stock is coming. If the other traders fall for it, the algorithm quickly reverses course to take the side of the trade it actually wanted. There’s evidence that this is what trading algorithms sending in bizarre orders, as they did during the Flash Crash, might be up to.

3) High-frequency trading is socially wasteful.

High-frequency trading is a zero-sum game. The winning side wins whatever the losing side loses. Yet millions of dollars have been spent to play this game faster – laying shorter cables across the country to transmit trades, massive investments in trading programs, and so on. That “arms race,” as economists Eric Budish, Peter Cramton, and John Shim argue, is a pure waste.

What are some ways we could curb high-frequency trading?

One idea is to tax financial transactions, a proposal called a Tobin tax, after economist James Tobin. A slight fee of, say, 0.1 percent might have little effect on the ability of most investors to buy and sell profitably. Yet it might render unprofitable most of high-frequency trading, which makes a small profit per trade but makes countless trades.

The European Union planned to introduce a Tobin tax in 2014 on stocks, bonds, and derivatives trading, but the proposal has since been stalled. Sweden had a 0.5-percent tax on financial transactions from 1984 to 1991.

Another proposal is to redesign the way markets work. Instead of processing orders as they come in, there would be a “batch auction.” All the orders that arrive over a given period of time would clear at once and at a single price. This would make it impossible to trade at the speeds high-frequency traders do, eliminating their informational advantage or their ability to preview other traders’ orders.

The Securities and Exchange Commission, the Federal Bureau of Investigation, and the Justice Department all have ongoing investigations of high-frequency trading practices. Mostly, they’re trying to determine whether the programs break laws against insider trading.

Regulators might end up opting for milder solutions. They might, for example, restrict particular types of trading activity or high-frequency traders’ ability to co-locate inside stock-exchange servers. Another possibility is that they might adjust regulations to force high-frequency trading to abandon some of its shadier practices. They could assess a fee on high volumes of order cancellations, for instance, or require traders who submit quotes to honor them for a minimum period of time.