Author: Tom Slee

Following on from the previous post, here are two other places where they talk about the consequences of inequality:

Mark Thoma, yet again, brings us a piece from the New York Times which discusses what can happen in a city when the middle ranges of income leaves, so that only the rich and poor are left. Basically, the two become separate cultures.

With a dwindling middle class, rich and poor become more separate. Alan
Berube, an author of the Brookings study, said a two-tiered marketplace can
develop: Whole Foods for the upper classes, bodegas for the lower, with no
competition from stores courting the middle…

“This trend toward living and interacting with people who are like you is
intensifying a lot,” said Professor Gyourko, who lives in the affluent suburb of
Swarthmore, Pa. “I do not meet the full range of incomes and social classes
within my neighborhood. Well, think about what happens if metropolitan areas
like New York, San Francisco and the like turn into my suburb. You’ll have even
less interaction. The most interesting and potentially foreboding implication of
this sorting is that it changes the way we view life.”

And Matthew Kahn asks When the rich get richer, what happens to the poor? and answers

It depends. If the super-rich use some of their $ to finance nice
musuems and art galleries and Buffett-Gates their money to solve public
health challenges then society could be improved along some dimensions.

Alternatively
if this crew uses their money to purchase 100,000 square foot homes in
desirable areas then the price of land will skyrocket and the middle
class will be squeezed out.

The studies of Piketty and Saez seem to be becoming the standard for the description of inequality within the USA. Every now and then they update their figures, and recently they published an updated set that described what happened to American Inequality in 2004. There has been a rush of comments about the numbers on some economic weblogs. So I’ll collect them together here – I don’t have anything to add myself: it’s fascinating to see this kind of real-world issue being debated among experts in public.

First, the update itself is in an Excel spreadsheet here, at the web site of Emmanual Saez.

Paul Krugman (in the New York Times, but reposted in part by Mark Thoma here) describes the main feature as follows:

Thomas Piketty and Emmanuel Saez, whose
long-term estimates of income equality have become the gold standard for
research on this topic … show that even if you exclude capital gains from
a rising stock market, in 2004 the real income of the richest 1 percent of
Americans surged by almost 12.5 percent. Meanwhile, the average real income of
the bottom 99 percent of the population rose only 1.5 percent. In other words, a
relative handful of people received most of the benefits of growth.

There are a couple of additional revelations in the 2004 data. One is that
growth didn’t just bypass the poor and the lower middle class, it bypassed the
upper middle class too. Even people at the 95th percentile of the income
distribution — that is, people richer than 19 out of 20 Americans — gained only
modestly. …

The other revelation is that being highly educated was no guarantee of
sharing in the benefits of economic growth. There’s a persistent myth,
perpetuated by economists who should know better … that rising inequality …
is mainly a matter of a rising gap between those with a lot of education and
those without. But census data show that the real earnings of the typical
college graduate actually fell in 2004.

Greg Mankiw, another prominent economist who was also high up in the Bush administration until recently, saw things differently here:

Here is what I see: After rising substantially from 1986 to 2000,
income inequality is essentially the same in 2004 (the most recent year
of data) as it was in 2000.

In a separate post, Mankiw also challenges Krugman’s sentence about "a persistent myth, perpetuated by eonomists who should know better…that rising inequality…is mainly a matter of a rising gap between those with a lof of education and those without". While Krugman claims that the big story is the growth of income at the very top of the scale, Mankiw reasserts the role of a more broadly based change:

My
understanding is that there is a widespread consensus that the returns
to education have risen substantially over the past few decades. But
the education wage premium is not the whole story, as wage inequality
within education categories has also increased substantially.

…part
of the increase in inequality is measurement error, and part of the
increase is attributable to the fact that the labor force is older and
more educated–characteristics that are associated with higher residual
variance.

Brad DeLong takes up the thread, weighing in on Krugman’s side:

The big rise in inequality in the U.S. since 1980 has been
overwhelmingly concentrated among the top 1% of income earners: their
share has risen from 8% in 1980 to 16% in 2004. By contrast, the share
of the next 4% of income earners has only risen from 13% to 15%, and
the share of the next 5% of income earners has stuck at 12%. The top 1%
have gone from 8 to 16 times average income, the next 4% have gone from
3.2 to 3.7 times average income, and the next 5% have been stuck at 3
times average income.

It’s hard to attribute this pattern to a rise in the premium salary
earned by the well-educated by virtue of the skills their formal
education taught them.

But Greg Mankiw is not convinced:

I would guess that the top 1 percent of income earners (those earning
more than $276,945) are disproportionately very well educated–doctors,
lawyers, MBAs, etc. So the rise in the income of the top 1 percent
could well represent in large part a higher education premium.

What
might well be true is that the returns to education have become
increasingly non-linear: The most educated are now getting a bigger
return from a marginal year of education than those with moderate
amounts of education. In other words, two years getting an MBA from
Harvard Business School may increase a person’s income more in
percentage terms than does two years getting an Associate Degree from
Mass Bay Community College. My understanding from my labor economist
friends is that some evidence favors this hypothesis of increasing
nonlinearity.

And Mark Thoma adds his two cents:

We can debate what has happened the last few years and whether this year or
that year had special circumstances such as the problems Brad notes with using
2000 as a base year. But in doing so, we shouldn’t lose sight of the overall
upward trend in inequality.

Top Decile Income Share

Top 0.01% Income Share

Average Real Income of bottom 99% and top 1%

The little dip at the end is what the fuss is all about. But even if Greg’s claim holds up to the types of qualifications Brad talks about, and there are good reasons to worry about using 2000 as a base year, the upward trend in income inequality since the 1970s is undeniable. And in any case, as the last graph shows, real income for the bottom 99% of the distribution has been flat since the early 1970s despite large gains in productivity.

Meanwhile, in keeping with Thoma’s theme of focusing on the bigger picture, Brad Delong reminds us that

Real wages for low-paid workers aren’t rising at all. It’s not the
well-paid benefit "most." It’s that only the well-paid are, as a group,
benefitting at all.

I’ve just changed the design at my nonblog web site.

Why? Well, because it was pretty hideous before, and also because I recently put together a web site for my better half, and I thought my own place deserved a bit of spit and polish. I’m not really sure about the colour scheme, but I’ll give it a week or so and see how it looks after that time.

Update: I just made a few more changes so it looks better in Internet Explorer. It still looks best in Firefox, but the differences are now pretty minor.

For anyone who cares about such things, the colour scheme was inspired by the Dark Rose design by Rose Fu at the css Zen Garden, which has lots of great ideas for anyone looking to design a site.

Update 2: I added fancier scrolling behaviour, for Firefox only, so that only the main column moves as you scroll the page (you have to look at one of the longer pages to see it, or have your browser in a small window). There are workarounds that let you simulate this CSS position:fixed behaviour in IE, but that seems like too much work.

Via Brad DeLong, a piece in the LA Times that covers some of the ground I cover  about movies in Chapter 9, although the LA Times has better stories. Here are a few excerpts, but it’s worth reading the whole thing:

That no one can know whether a film will hit or miss has been an
uncomfortable suspicion in Hollywood at least since novelist and
screenwriter William Goldman enunciated it in his classic 1983 book
"Adventures in the Screen Trade." If Goldman is right and a future
film’s performance is unpredictable, then there is no way studio
executives or producers, despite all their swagger, can have a better
track record at choosing projects than an ape throwing darts at a
dartboard.

That’s a bold statement, but these days it is hardly conjecture: With
each passing year the unpredictability of film revenue is supported by
more and more academic research…

What the research shows is that even the most professionally made films
are subject to many unpredictable factors that arise during production
and marketing, not to mention the inscrutable taste of the audience. It
is these unknowns that obliterate the ability to foretell the
box-office future.

But if picking films is like randomly tossing darts, why do some people
hit the bull’s-eye more often than others? For the same reason that in
a group of apes tossing darts, some apes will do better than others.
The answer has nothing to do with skill. Even random events occur in
clusters and streaks.

Imagine this game: We line up 20,000 moviegoers who, one by one, flip a
coin. If the coin lands heads, they see "X-Men"; if the coin lands
tails, it’s "The Da Vinci Code." Since the coin has an equal chance of
coming up either way, you might think that in this experimental
box-office war each film should be in the lead about 10,000 times. But
the mathematics of randomness says otherwise: The most probable number
of lead changes is zero, and it is 88 times more probable that one of
the two films will lead through all 20,000 customers than that each
film leads 10,000 times. The lesson I teach in my course is that the
fairness of the goddess of fortune is expressed not in alternations of
the lead but in the symmetry of probabilities: Each film is equally
likely to be the one that grabs and keeps the lead.

If the mathematics is counterintuitive, reality is even worse, because
a funny thing happens when a random process such as the coin-flipping
experiment is actually carried out: The symmetry of fairness is broken
and one of the films becomes the winner. Even in situations like this,
in which we know there is no "reason" that the coin flips should favor
one film over the other, psychologists have shown that the temptation
to concoct imagined reasons to account for skewed data and other
patterns is often overwhelming.

In science, data are not accepted as meaningful if they’re the result
of chance alone. People in the film industry are diligent about
gathering data, but are far less skilled at understanding what the
numbers mean. The fact is, financial success or failure in Hollywood is
determined less by anyone’s skill to pick hits, or lack thereof, than
by the random nature of the universe. The typical patterns of
randomness—apparent hot or cold streaks, or the bunching of data into
clusters—are routinely misinterpreted and, worse, acted upon as if a
new trend had been discovered or a new epiphany achieved. And so,
despite a growing body of evidence that box-office revenue follows the
laws of chaotic systems, meaning that it is inherently unpredictable,
the superstructure of Hollywood’s culture—that pervasive worship of
who’s hot and the shunning of who’s not—continues to rest on a
foundation of misconception and mirage.

RAD points me to a New York Times article by Stephen Dubner and Steven Levitt about buying and selling organs. That’s organ as in kidney or liver, not organ as in church or Hammond. It’s an interesting entry to a very topical topic: one that still has shock value but which we are going to hear about more in the future.

My point of view, unsurprisingly, is that I don’t trust market
mechanisms to deal with the problem. This essay is a starting point for
thinking about it. I hope to follow it up later with a second attempt.

* * *

The reason people are talking about buying and selling kidneys
is that organ transplants are safe and cheaper than they used to be, so lots of
sick people could benefit from an increase in organ donations, and so that
spare kidney you’ve been keeping around is now a very popular kidney, used and
second-hand though it be. So why, ask Dubner and Levitt, don’t we let people
buy and sell their kidneys? After all, “most people can live safely on one
kidney”, they say. They suggest that the main reason we don’t allow buying and
selling of kidneys is what they call “the repugnance factor”, and they have a
point, even though another reason is that it’s impossible to read that sentence
without it looking like this: “most BUT
NOT ALL!!! people can live safely on one kidney UNLESS SOMETHING GOES WRONG WITH THE OTHER ONE”.

The Dubner and Levitt article is a bit odd actually. It
suggests it’s talking about how paying people for their kidneys may save the
lives of people who need a new kidney, while also letting people with spare
kidneys earn some cash on the side. But when it comes to the specifics they don’t
talk about buying and selling at all. Instead, they talk about a matching
program that matches incompatible donor-patient pairs. In these pairs, each
potential donor’s kidney is a bad match for the immune systems of their partner—but
the system matches them with similarly incompatible pairs and the two matched
pairs can basically swap a kidney. No money involved. Then they talk about a
potential donor who was going to sell his kidney to a stranger and, when he discovered
that accepting payment for organs is illegal, went ahead and donated it anyway.
No money exchanged. They don’t really investigate payment for organs at all.

* * *

Still, even if D&L don’t actually talk about trading our
internal garbage collectors for money, other people are doing so. Down the hall
from Steven Levitt at the University of Chicago is Gary
Becker, the Nobel Prize winner who is in favour of markets in everything.
Together with graduate student Julio Elias, Becker has talked up the idea for
several years now and – Becker being Becker — he gets a fair amount of press
for it.

There are some technical reasons why I’m not convinced by
Becker and Elias’s argument (PDF). They aren’t at the centre of my problems with the
idea, but effectiveness does matter, so let me pursue these problems here.

First, they maintain that right now the supply curve for
kidneys is vertical. That is, a fixed amount of people are prepared to donate
kidneys. But the people most likely to donate kidneys are the relatives of
those on the operating table, so when the number of operations increases, so
the number of those relatives increases, and so the supply of kidneys increases.
It looks to me like that line should be sloping. Have I missed something? Hey,
it’s been known.

They go on to suggest that the actual number of kidneys
needed for transplants, compared to the total renal population of North
America, is so small that once you offer a reasonable amount of money you could
get as many kidneys as you could possibly want. That is, by offering payment
the supply curve goes from vertical to horizontal. And then they go on to
calculate how much you’d need to offer to induce people to sell. What they
don’t take account of (though in a more recent essay Becker considers and
dismisses this argument) is the possibility that offering to pay for kidneys
might actually cut down the supply. This would be counter to most economic
thinking, of course. The argument goes back to Richard Titmuss, a British
academic who wrote a few decades ago about blood donation in a book entitled
“The Gift Relationship”. Titmuss argued that offering to pay for blood would
actually dissuade some people from donating, because whereas people feel good
about themselves for donating blood, they don’t feel good about themselves for
selling blood. Recent experiments in Sweden suggest that there is
something to Titmuss idea. Becker doesn’t provide a real case against it, he
just asserts that the effect would be small.

Put these two things together and the effectiveness of even
a perfect market with no cheating or deception is less attractive than Becker
suggests. Instead of a dramatic change from a vertical supply curve to a
horizontal one, you have a more nuanced change. And that’s if everything else
works dine.

* * *

Becker also dismisses the other main arguments about the
introduction of payments, which are:

•  that the result will be poor people selling
  their kidneys in order to supply longer life to the rich, giving yet another
  twist to the growing gap between rich and poor in the world.
•  that the dangers of malpractice and deception of
  one form or another are so large – especially for those without the resources
  to get legal assistance and advice, that poor people in particular will be
  preyed on.
•  that just about any system you put in place
  provides incentives for all kinds of nastiness. This applies to presumed
  consent mechanisms as well. And although this kind of thing can sometimes be
  dealt with, it’s costly to do so.

Well, I hope to look at some of these in a Part II later.

* * *

There are some countries that have already taken deliberate
steps to make it easier for people to get new organs. Nancy Scheper-Hughes is a
sociologist at the University of California, Berkeley, and she has carried out research on organ trading around the world. In a 2003 forum she described these efforts:

There’s the
Israeli model: very low donation rates so you export your transplant patients
elsewhere and you give them medical insurance to pay for it, even at the cost
of their buying kidneys from poor peasants in Eastern
Europe. There are the Philippine, Iranian and Iraqi models:
government-sponsored payments that allow very poor people to sell their organs
for as low as $500, which leads to deep social resentments. The Chinese model:
you can use the organs of executed prisoners. The Russian model: in which there’s
not such a careful monitoring of confirmatory tests for brain death. The Spanish
model: paying the procurers. More humanely, there is the Austrian and Belgian model
of presumed consent.

There’s no doubt other countries will be dealing with the
issue in the future. But Scheper-Hughes is on the money (so to speak) when she
points out that the presumed consent model requires a trust in the fairness of
the medical system that certainly doesn’t exist in the US.

“we don’t
have the kind of social consensus whereby people feel that their organs will be
fairly and equally distributed among the poor as well as the wealthy or well
insured, among women as well as men, or that all will have an equal right to
get an organ should they need one. So first we have to address the lack of
national health care, the 44 million uninsured, and the contradiction in asking
poor people in America
– who tend by and large to be over-represented in emergency rooms and ICUs – to
donate organs when they and their relatives may not even have basic health
care.

Canada may not be in quite the same straights as the US in that way, but it’s got some
real issues, and they need to be dealt with in order to deal with the issues surrounding
organ transplants.