Obesity: Class Warfare, Imperfect Information... or both?

Saw this on CNN today: Poor and fat: The real class war, by L.Z. Granderson. Some figures from the article:

Ground beef that is 80/20 is fattier but cheaper than 90/10. Ground turkey breast is leaner than the other two but is usually the more expensive. And many of us can't even begin to think about free-range chicken and organic produce -- food without pesticides and antibiotics that'll cost you a second mortgage in no time at all.
...The American Journal of Clinical Nutrition recently published a study that found $1 could buy 1,200 calories of potato chips but just 250 calories of vegetables and 170 calories of fresh fruit. And it is also true that Mississippi, the poorest state in the country, is also the fattest.
In fact, the five poorest states are also among the 10 fattest, and eight of the 10 poorest states are also among the 10 with the lowest life expectancy.
I guess one could dismiss this as one big coincidence, but is it also a coincidence that half of the top 10 states with the highest median incomes are also in the top 10 in life expectancy?

I would interpret Granderson's argument as: low-income leads to unhealthy foods leads to fat (leads to more healthcare spending and even lower incomes). Looking at calorie counts compared to food prices does seem to support that. However, bringing some micro theory into the discussion complicates this causal story somewhat.

We can quantify the effect of income on food choices through this simplified model. Imagine two different families, both trying to fill a calorie requirement of 2000, but the low-income family has a food budget of $3 and the high-income family has a food budget of $10.

After plugging numbers into the formula above, the high-income family buys only 0.3 servings of potato chips and 9.7 servings of fruit, while the low-income family gets about 1.4 servings of potato chips and 1.6 servings of fruit.

The same intuition is expressed graphically below. Purchasing decisions are represented by points where the red and blue lines cross.

So far, so good: as one would expect, the high-income family buys more fruit and less potato chips than the low income family. One problem for this example, though, is that neither of these families will be gaining any weight!

If people only eat the necessary calories to keep an even weight, it won't matter whether their income is high or low. They'll just adjust their purchasing choices to get the right amount of calories. A dietitian might frown on you for eating chips as a snack instead of fruit, but as long as your consumption of chips is small, it won't necessarily cause you to gain weight.

It takes some extra assumptions to model over-eating. Maybe there's some property of potato chips that causes people to eat too much of them, i.e. what if someone buys potato chips thinking that a $1 serving will be 1200 calories, when it's actually equivalent to 1600 calories? Keeping with the numerical example above, the rich family would overeat by about 120 calories and the poor family by 560 calories.

It's only imperfect information or self-control problems which make food choices cause weight-gain. If we assume that low- and high-income types have exactly the same sort of bounded information, we'll find that the rich gain less weight, because their greater resources have them purchasing less unhealthy food to begin with.

This story gets even more pessimistic if there is some difference between low- and high-income people's capacity to overcome imperfect information. It might be that the poor have less time/energy to research and craft their diet than the rich do, so they are more prone to mistakes. Additionally, there could be some personal attribute - an impulsive nature or low conscientiousness - which both causes someone to have low income and also makes diet control more difficult.

While the costs of obesity are worth addressing given their heavy contribution to public healthcare spending, as Granderson rightly observes, the lens of class warfare isn't the best for understanding the problem.

Ultimately, to prevent obesity people need more incentive to monitor their own health. For me, it's knowing that on the current trajectory of public health care spending, there probably won't be any money left by the time I'm old and infirm. It doesn't entirely surprise that current beneficiaries of public health care are not too concerned about solving this spending problem for the rest of us (morbid fact: about a third of health care spending goes to patients in their last year of life). Which class is under attack, and which class is attacking anyway?

Maybe the obesity problem will resolve itself as young people make the calculations and figure they will likely be on their own, in terms of medical care, by the time it is most necessary. Or maybe the lure of potato chips is simply too great for us as a nation and will lead to our fiscal undoing.

Paycheck Fairness Act is anti-womens' employment

Scheduled to come to a vote in Congress tomorrow, the Paycheck Fairness Act is a bad solution to a statistically trumped-up problem.

The most frequently cited statistic is that women earn 77 cents for every dollar a man makes. However, not all of that gap can be attributed to discrimination.

The Bureau of Labor Statistics reports that comparing male and female full-time workers, men work more hours: 8.2 versus 7.8 hours per day, on average. Just assuming an exactly even hourly rate, we'd expect women to earn 95% of men's total on a yearly basis; however, there are also more women working part-time than men, widening the gap further. Men are also disproportionately likely to die from an injury on the job, as this chart shows.

Source: US Department of Labor, Bureau of Labor Statistics, Current Population Survey, and Census of Fatal Occupational Injuries, 2012.

But put aside those statistical details. A gap in male-female wages undoubtedly remains, and some of it is probably due to gender-bias and discrimination. What does the Paycheck Fairness Act do to fix that?

The Act would strengthen the Equal Pay Act of 1963, which already requires similar workers be paid the same. The new legislation would expand the damages that women can claim in court, and give women more tools to sue their employers if discrimination is suspected.

The new law would result in effectively unlimited liability for a business sued for giving unequal pay. Put yourself in the shoes of a small business owner. Suppose you are considering hiring either a male or female employee for an entry-level position. Suddenly knowing that your business could be shut down if a court decides your payment to the woman is unfair, who would you be more inclined to hire?

Let's think of another group that has been "protected" by sweeping federal legislation. Persons with physical disabilities are given additional tort resources by the Americans with Disabilities Act if it's found that they were treated unfairly. A paper by Acemoglu and Angrist (2001), using reliable econometric techniques, found that employment of disabled people dropped substantially following the ADA's passage. Now, twenty years later, physically disabled persons are unemployed at record levels.

There are obvious weaknesses in the analogy between the Paycheck Fairness Act and Americans with Disabilities Act - women are a larger segment of the population, and aren't physically limited from doing most jobs - but a lesson remains. Creating new protected classes of workers is not always to that group's overall benefit.

Even well-intentioned laws may end up punishing businesses for hiring certain workers, which hurts both individuals and the economy as a whole. The Paycheck Fairness Act is almost certainly dead in the water; even without passage, its political purpose will have been achieved. But, if President Obama and the Democrats want to show they are helping women, a first step is to not shut them out of the labor market.

Fish and Game Dept. targets Asian Supermarket - Flawed Economics in Action

A daring sting operation has brought down another set of dangerous criminals in our midst. The proprietors of Great Wall supermarket (located about 20 minutes from where I live) have been arrested for selling "wild" sea animals including live frogs, crayfish, turtles, eels, and more. The store owners say that all of their stock comes from farmed sources, but that does not appear to be convincing the crusading Commonwealth bureaucrats.

Officer Rich Landers, of the Virginia Department of Game and Inland Fisheries, had this to say:

“History has show when wildlife becomes commercialized, the population dwindles,” Landers said. “Whether it’s elephant tusks or whales, we are trying to reduce the chances that wildlife becomes commercialized.”

Lets take a moment and think of a heavily commercialized animal population, like cows. We may have another disaster on our hands: the cow population is down to the lowest level since 1958, with only 92.6 million in the United States! An estimated 25 million cows are slaughtered each year. That means that in less than four years, there won't be any cows left in the United States. Savor your steaks while you can!

See what's wrong with this story? While commercialization allows animals to be consumed, it also creates strong incentives to rebuild the population for future consumption as well. That's why the decline in the cow population has been in response to reduced profitability of cattle ranching... not an ecological shortfall. Why would this be any different for farmed eels, turtles, or fish?

The historical examples that Landers uses are all cases where no one had ownership rights over the stock of animals being hunted, and therefore no reason to maintain sustainable population levels. That is clearly not the case here when we are discussing farmed seafood.

If anything, the proprietors of Great Wall should be applauded, for meeting consumer demand for uncommon (by American standards) foodstuffs. That way, Asian families can eat farmed eels etc. and do not have to catch them wild or import from abroad, potentially bringing exotic animal diseases to afflict U.S. ecosystems.

I won't go so far as to accuse the Department of Game and Inland Fisheries of racism or xenophobia, as I'm sure they'd be just as happy to apply their short-sighted and fallacious brand of reasoning to a predominantly-American grocery store as well. But, charging honest business owners with felonies, for selling live turtles and bass, does not inspire much confidence in either the agency's competence or its underlying motives.

Productivity is bad for job growth?

Scanning the news feed for something worthy of being shared with Twitter, I happened across this good news/bad news article from USA Today: Unemployment benefit claims, worker productivity fall. Less benefit claims is a sign that more people are going back to work, although drops in productivity temper optimism about the speed of economic recovery.

Instead, apparently the author of this piece took it be good news/good news, claiming

Weaker productivity growth can help boost hiring if economic growth picks up.

This argument is motivated by the lump of labor fallacy (the idea that there are only so many jobs to be done, so higher productivity will leave more out of work) and a preoccupation with firms as purveyors of jobs rather than producers of products. Both of these ideas are largely discredited among economists.

In reality, productivity growth is the driving factor behind economic expansion. For economic growth to pick up, we need the inputs of production (labor, capital, etc.) to become more productive, not slow down! This allows us to both become richer and create more jobs as a society.

At the micro-level, theory predicts that a firm will not pay a worker more than their marginal product; i.e. if a machinist can produce $50 worth of goods in an hour, a company that pays him/her $51 per hour will be losing money. USA Today misses the irony when going on to claim

consumers have been weighed down by wages that haven't kept pace with inflation.

If that is occurring, it's because worker productivity hasn't kept pace with other factors in the economy. This argument is made in more detail by several recent books: Race Against the Machine by Erik Brynjolfsson and Andrew McAfee, and The Great Stagnation by Tyler Cowen both explore the phenomenon of declining worker productivity, and neither are excited about that decline as a source of new jobs.

Lower productivity means reduced living standards for future Americans. It doesn't even rise to the level of a placebo for our current unemployment woes; generally, placebos are expected to do nothing, not make the problem worse.

Do higher tax rates spur more charity? I doubt it.

A few days ago I was talking with my mother about the state of the economy, income inequality, and social obligations... Typical evening conversation on any New Years, I'm sure. From life experience and observations on a (privileged) extended family, her opinion was that more charity occurred when tax rates were higher. I disagreed, and offered to present a mathematical demonstration on why that was the case. After that effort, I wanted to show the Internets the fruits of my labor.

Charitable giving is a very personal decision and the tax law surrounding it is complicated and arcane, so I start with some simplifying assumptions to make the problem more approachable. These are:

• Money given to charity is 100% tax-deductible.
• Each person lives for two periods, then dies, and their entire stock of wealth is donated after death.
• An individual's money earns 10% interest.
• To make the problem concrete, I'll imagine a person earning $100,000 in each period, and two different tax regimes: one with a 0% tax rate, and another with 50%. 

Now a quick exercise in arithmetic, starting with a tax rate of 50%. The individual earns $100,000 in the first period, $50,000 of which would go to the government. Instead that $50,000 is given to charity to avoid taxes. At the start of period two, they earn $5,000 in interest and another $50,000 in after-tax income, then die and donate all of it. Total charity given is $205,000.

Now imagine a tax rate of 0% (and if you're a libertarian, try not to faint with excitement). An individual earns $100,000 and keeps all of it, earns $10,000 in interest before the second period, makes another $100,000 then dies and gives all of it away. Total charity given is $210,000.

One could argue that this result emerges just from the assumptions made, which is partially true. However, as long as individuals can earn a higher return on investment than the government (which is not a controversial claim) and all money is transferred upon death (a de facto necessity) then the result, qualitatively, will still be the same. If you make the example more realistic, and envision a person making money then saving and investing it for more than just two years, the difference between the two tax rates becomes even more apparent.

Of course, someone might say there are distributional issues this exercise neglects. Maybe needy recipients of charity are more sympathetic than the undeserving heirs of some wealthy person. Aside from that, the general point still stands: when government takes money through taxes, the overall social "pie" becomes smaller. When individuals can invest it, they put money into productive activities which can generate more wealth, making the "pie" bigger. Even if higher tax rates drive some people to give more money to charity than they otherwise would, society in the aggregate is better off if that money can be productively invested by individuals instead. Charity is then a pleasant side-benefit of greater social wealth.

Statistical Fallacy #176: Ignoring Selection Effects

I stumbled on a post at a credit-related blog. It starts off with the bombastic first line

"The average consumer is saddled with $29,985 in student loan debt..."

 Wow! That's a lot of debt! It's true that the U.S. population has a giant amount of student loan debt -- even more so than the amount of credit card debt. Last year, I wrote about the subject. But, the figure above is pretty high. That statistic is drawn from "262,887 CreditKarma.com user scores." Sounds pretty robust. But, some simple math reveals there's more to the story.

Facts:

• Total student loan debt in the U.S. is about $1 trillion (~$1,000,000,000,000).
• The U.S. population is 308,745,538. Of that, 24% are under 18, leaving 234,646,609 adult consumers.

Do some division, and you'll find that the average adult consumer has $4261.73 in credit card debt. That's about $25,000 less than the Credit Karma estimate!

What went wrong? My guess: selection effects. Members of a site specializing in credit advice are not a random sample of the population. People who join are probably concerned about their credit... and people who are concerned about their credit probably have a lot of debt.

Nothing personal against the writers for that site, as it would be an easy mistake to make (and they were very nice, even in response to my snarky comment pointing this out). But still, they should have been more careful. A quick test, by multiplying their estimate of average debt by the number of consumers, finds that the U.S. has a total of $7,035,878,570,865 in student loans outstanding, about seven times the real figure. If it were true, that would be about 11% of the entire world GDP owed by American students!

The lesson: look out for non-random sampling due to self-selection, or your numbers will be nonsense.

Tax wedding rings. No one will know the difference.

With our huge budget deficit, there are many ideas on how to raise more government revenue. Most of them involve raising taxes on the highest-earning households. I have a better idea: tax the ultimate in status purchases -- wedding rings.

Not romantic, but practical. The reasoning: wedding rings are purchased largely because they are expensive. No bride wants to feel cheap. Men are usually advised to spend some fixed amount of their income on the ring: somewhere between 5% and two months of salary being the most common advice. If men are looking to spend a certain amount of money, and care very little about the ring's actual attributes, a tax would not affect their purchasing at all!

How much revenue could a wedding ring tax raise? From a little Google-work, here are some starting figures:

• Average price of an engagement ring: between $2,100 and $3,200
• Wedding rings cost an average of $5,000
• Every year an average of 2.4 million weddings are performed in the U.S.

If we split the difference on average engagement ring prices (arriving at mean of $2,650) make the heroic assumption that every bride gets both an engagement and wedding ring, and the less-heroic assumption that wedding ring demand is inelastic with regard to price, it becomes fairly easy to estimate revenue from a tax.

Suppose government taxed half the cost of rings. Price of the ring would remain about the same because it's a status purchase; jewelers would use slightly less high-quality gold, diamonds, etc. to make up lost profits from the tax.

For a quick back-of-the-envelope calculation:  
Revenue = ($1,325 + $2,500) * 2,400,000 = $9,180,000,000 or $9.18 billion dollars per year.

It won't balance the budget but neither will most of the proposals floating around, like turds in the political punchbowl, being pushed back and forth by the Obama Administration and Congress. If taxes are going to be raised, I for one think it would be better to choose targets that will impact consumers as little as possible. From this perspective, wedding rings are an easy target.

"Fat Head": why fat is good and nutritionists are wrong.

My role model.

I try to blog on topics within my field - economics - which is usually easy, because economics encompasses almost everything. However, I recently watched a health documentary which inspired me to brave the big, scary world of health and nutrition. Written and directed by former health writer and comedian Tom Naughton, "Fat Head" is a must-watch for everyone, especially those who liked and/or took seriously Morgan Spurlock's "Supersize Me."

Available on Netflix and Hulu as well for sale off the creators website, "Fat Head" is a quick, fun and informative video. However, for those who want the factual gist of it without the cheesy (but amusing) commentary and animations, I present this partially-digested version of the food documentary, broken into three main chunks for easy consumption.


1. The numbers in "Supersize Me" don't add up. In the movie, Spurlock's nutritionist repeatedly says he's consuming over 5,000 calories per day. Problem is, according to Spurlock's own rules, he only had three square meals per day. Even if he Super-Sized at every opportunity (which he claims not to have done) that still only adds up to a rough 3,600 calories. Where'd the rest come from? He must have added several desserts. If someone stuffs themselves with over twice the calories required for a healthy adult... is it really surprising that they gained weight?

Real causes of debt are simple; debtors' explanations more complicated.

In my constant quest to find the pot of gold at the end of the Internet, I discovered this gem.



Does this make sense to you? As far as I know, there's only one cause of debt: borrowing money. Whether that is "bad" debt depends on the circumstances surrounding efforts to pay it back.

In short, there are two big problems with the statistics above.

1) Data are from surveys of where people say their debt came from (revealed in tiny font at the bottom of the picture). Perhaps I'm too cynical, but I think more people are apt to blame their debt on external events, such as a pay cut, rather than admit they are spending beyond their means. It's more sympathetic and less hard on the ego to say that you were forced into debt rather than led down the path willingly.

2) After losing a job or taking a pay cut, if you continue to spend at the same rate as before, in my book that still counts as "going wild in the aisles." If expectations remain static as situations change, is it really accurate to blame the situation (less pay) for the outcome, rather than one's personal failure to adapt to the new circumstances? If it were the opposite case and income had just increased, I don't think many people would say "I blame this higher wage for my not having time to go shopping and spend as much as I want" (holding hours worked constant, of course). The real problem is not adjusting behavior to fit the new constraints that reality imposes.

I'm sure some people end up in bad debt through no fault of their own, or as a result of unavoidable expenses or unforeseen changes in income which may coincide with less opportunities for work. However, I don't think that number is large enough to make up 48% of all cases of bad debt. Further, by claiming that a pay cut is the largest cause of bad debt this chart implies that people are largely incapable of changing their consumption patterns to fit a more modest standard of living, which is not a very good lesson to live by.

If anything, the big difference between "perceived" and "real" causes of debt would be better labeled as "how I think other people got into debt" and "how I explain my own debt" respectively. Knowing only a little about psychology, it is unsurprising that respondents hold other people responsible for their choices (spending too much) but apply a much more ego-gratifying standard when considering themselves.

Maybe the 21st century version of old proverb "don't take any wooden nickels" will become "don't trust statistics off of online infographics." Less catchy perhaps, but much more common application!

How to Gain Twitter-Fame for Penny Stock Advice, with no Skill, Knowledge (or Profits) Required.

Along with upcoming rappers, Bieber fans, and ad-bots there’s a rash of penny stock advice to be found on Twitter. At first I dismissed it as one of many eccentricities of the platform, but after seeing a few dozen assorted “penny stock” accounts I started to wonder. What could explain these accounts peddling advice on securities that most investors wouldn’t line a litter-box with?

So-called "penny stocks" may range in cost from a few dollars to a fraction of a cent. For example, instead of buying one share of IBM at $164.68, it would be possible to instead purchase 4,450 shares of Double Eagle Gold Holdings (DEGH) at $.037 per share (amusingly, both stocks are currently near their respective peak historical values). DEGH had been running at an average price of about $.003 for most of the last year. If an investor had a crystal ball and could foresee this recent ten-fold run up in price, there would have been a lot of money to be made; therein lies the temptation of penny stocks.

Of course, anyone who actually had that crystal ball and put it to use in the market would be far too rich to bother with running a Twitter account. So why are there hundreds of penny stock tweeters out there? To explain, here is a theory of how ANYONE can appear blessed with penny stock clairvoyance.


The Five-Step Guide to Achieving Twitter-fame with Penny Stock Advice:

Step 1: Pick out 100 penny stocks at random, and buy $10 worth in each of them for a total cost of $1,000 plus brokerage fees (or, if you’re cheap, just consistently follow the prices of 100 penny stocks).

Step 2: Wait. As is normal for inexpensive and highly volatile stocks, the price of some will go up dramatically and others down equally dramatically.

Step 3: Ignore the stocks that go down. Out of the 100, by random chance you’re almost assured to see one go up every now and then. Get on Twitter and brag about how well your picks in the stocks that went up are going.

Step 4: Construct self-promotional statistics to describe how well an investor could have done if they had known exactly when these volatile stocks would move up and down, then tweet about anyone can generate “POTENTIAL 237% PROFITS!!!” based on your expert advice.

Step 5: Bask in fame and adulation. If you are lucky, people will buy a subscription to your newsletter. Or, if they follow your advice, it will drive up the price of penny stocks you own. Then sell off the penny stocks that went up due to your “wisdom” and leave your followers to eat the losses as the stock shifts back down. 


I can’t verify that every penny stock tweeter uses this self-serving strategy. However, it’s the only way I can think of making money off penny stocks, so I’d guess that a large ratio of those Twitter accounts have something like this in mind.

In the time it took me to write the above, DEGH – which I noticed as a result of a penny stock tweet – has dropped 35%. IBM, on the other hand, changed 0.30% in that hour. In a nutshell, this is why investing in penny stocks is probably not a good idea: you get all the risk of stock market speculation without much stake in any real value (or else why is the stock so cheap?). Markets tend to be efficient and integrate available information into stock prices, so when a stock costs a fraction of a cent, it’s probably because many people rate its investment value somewhere near a lottery ticket.

The DEGH rollercoaster, courtesy of Google Finance. Notice the peak, then sudden drop at the end.

To make matters even worse, even if you successfully buy low and sell high with penny stocks – a difficult proposition, given how quickly the values change – you’ll be eaten alive in brokerage fees. For the example above, even if one used a discount brokerage like Scottrade, the cost of each purchase would be a $7 flat fee – making a $1,000 investment cost a total of $1,700. It would take a crystal ball, extraordinary luck, or loads of self-serving information delivered to a mass audience in order to generate enough returns to cover that cost. When you see someone giving investment advice on Twitter, mentally ask which of those three categories you think they fall into.



Note: for entertainment purposes only. I’m not dispensing investment advice; the stocks named were solely for example purposes, not as endorsement. If you’re reading this and run a penny stock service I’m sure you’re the exception to the above, and love children, flowers, kittens and your advisees all equally and would never pull such a scam on them. I’m just writing about your competition. But I would awfully like to peak at your crystal ball sometime when you get a chance.

How to live rent-free the rest of your life. OR, Five Big Mistakes Criminals Make During Police Interrogations.

 "...the technique of violence was first developed in 2 million B.C. by the australopithecines and tried by forthwith primates, who had no brains to speak of, but nonetheless invented the tomahawk and used it on each other. This practice led to the enlargement of the brain, another useful weapon. Yes, murder was invented even before man learned to think. Now, of course, man has become known as the 'thinking animal.'"
- spoken during the credits of Death Race 2000 (1975).

One of the reasons I love reality television is that it can make you feel like an expert in fields you have no personal knowledge or training in whatsoever. From watching many episodes of A&E's crime show, "The First 48" I feel pseudo-enlightened about the workings of the criminal justice system, and I'm here to share that almost-wisdom with you.

Statistical Fallacy #002: Confusing Correlation with Causation. Does a strong handshake really make you live longer?

Even highly educated and intelligent medical researchers aren't immune to statistical errors. A recent study in the British Medical Journal referenced 33 other studies on personal mobility and life expectancy, and compiled their results. According to Reuters, 

They found simple measures of physical capability like shaking hands, walking, getting up from a chair and balancing on one leg were related to life span, even after accounting for age, sex and body size. 

While the phrase "accounting for age, sex and body size" makes this process sound very objective and scientific, there are obviously a lot of other factors that can play a role in life expectancy. Personal differences, such as leading a more active lifestyle, could cause someone to have both more hand strength and also better health in general which contributes to their longevity.


While statistics saying "the death rate over the period of the studies for people with weak handshakes was 67 percent higher than for people with a firm grip" sound very dramatic, it's hard to say if that relationship is reverse-causal; in other words, having a weak grip may signal your lifespan will be short, but will improving your grip really make you live longer? Probably not, which suggests it's far more likely that a common variable - for example, sitting on the coach all day - causes both weak hands and a lower life expectancy.


Common sense says that working with a stress ball or doing forearm exercises to develop a crushing handshake probably won't substantially reduce your chance of death from heart disease, cancer, stroke, or the other leading causes of death for adult Americans. However, this is exactly the impression given by the Reuters article title "Want to live longer? Get a grip!" Heavens forbid someone took this seriously and developed gorilla-like forearms only to find out their fitness investment had been in vain.

Statistical Fallacy #317: Holding Constant that which Changes. See: 'median household income'.

Alternately, 

"Torture numbers, and they'll confess to anything."*

  Our inquisitionist of the day hails from Bloomberg. In an article today, Venessa Wong wrote the following:

While many Americans dream of a windfall that will take care of their financial needs for life, the sobering reality is most of us are not getting far: U.S. Census Bureau data show median household income barely changed in the 10 years following 1998 as the price of housing and other goods increased. In consumer price index-adjusted dollars, the median household income in 2008 was $50,303, compared with $51,295 in 1998. [Emphasis added.]

 What's wrong with the above? In a fairly common maneuver to paint a doom-and-gloom image of the times, average household size is treated as a constant to compare incomes over time. That just isn't the case.

The problem with using 'median household income' as a measuring stick is that it's actually a factor of two other variables: combined income, and number of people per household. The latter aspect is conveniently overlooked by pessimists, who are looking to demonstrate a negative trend over time. When everything is considered, a different picture emerges.