Wait, what was the question again?

Controversies involving Rush Limbaugh are as simple as they are boring: a guy who gets paid to say mean and offensive things says something mean and offensive, resulting in people being offended. These incidents are not worth the attention they receive, but 24-hour cable news being what it is, we all have to hear about it.

More interesting (to me, at least) is the line of reasoning used in his and other conservative's arguments.  For example, as Rachel Maddow ably explains, Limbaugh's statements suggest a profound ignorance about the workings of hormonal contraception.

Beyond the medical issue, there seems to be a lot of confusion about the policy question at hand.  Bill O'Reilly, while eschewing Limbaugh's vitriol, questions whether he personally, or society more broadly, should have to pay for people's sexual activities:

The question O'Reilly seems to be addressing is whether taxpayers should have to pay for birth control coverage. I think this is an interesting question and one that is worthy of debate. But it is simply not the question that is being addressed here. We are not discussing public provision of contraception, or any other healthcare, for that matter. The question here is whether private insurance companies should be required to cover hormonal contraception as part of their insurance packages. Thus, it is not a question of public spending, but rather one of regulation.

So if the concern is the cost of providing contraception, then this would reflect higher insurance premiums, not greater public spending. Does covering contraception increase insurance premiums? It doesn't seem like it. A review of published evidence by the Guttmacher Institute found that, "contraceptive coverage does not raise insurance premiums and that employers providing such coverage can, in fact, save money by avoiding costs associated with unintended pregnancy." Basically the cost of providing contraception is offset by the forgone cost of pre-natal care and delivery services. So Mr. O'Reilly's and Mr. Limbaugh's fears should be allayed.

With all the charged language and demagoguery, we seem to have lost sight of the topic. Instead, we have commentators denouncing non-existing policies and their imaginary consequences. Sure makes for good ratings, though.

Is U.S. inequality special?

In this post, Greg Mankiw argues that the U.S. is not the only country to see an increase in inequality over the past 40 years. Referring to a plot of the top income shares in the U.K., Mankiw notes:

“The figure suggests that the explanation of growing inequality over the past several decades cannot be U.S.-specific but must have broader applicability... You find a similar U-shaped pattern in Australia, Canada, Ireland, and New Zealand but much less so in France, Germany, Japan, and Sweden.”

Mankiw uses the impressive “Top Incomes Database,” compiled by (among others) Thomas Piketty and Emmanuel Saez. It is a fantastic resource; it enables you to plot data on income shares and inequality for a wide-range of countries over more than one-hundred years. Perusing the data, one finds that, in fact, many countries have seen an increase in inequality. But Mankiw seems to be implying that, since this is a global phenomenon, that shifts in U.S. policy aren’t driving the increase in inequality.

Using the database, I generated the following graphs: (1) comparing the U.S. with other rich English-speaking countries; and (2) comparing the U.S. with rich, but non-English speaking countries. I chose the countries Mankiw cites as examples in his post. The data covers the period between 1950 and 2007:*

As Mankiw notes, the changes in the top share of incomes for other rich English-speaking countries largely track those of the U.S. It is worth noting the discontinuous jump in the U.S. series in the mid-1980s, coinciding with the reform of the tax system during the Reagan administration.

In contrast, the rich non-English-speaking countries do not see much of a change in their top income shares. For example, the share of the top 1% in France was 8.98% in 1950 and 8.94% in 2007. The corresponding numbers for the U.S. are 11.60% and 18.29%. It takes a lot of motivated reasoning to detect an upward trend in the non-English-speaking countries.

To explain the difference between the two groups, Mankiw offers the following idea:

“Might the rising share of the top 1 percent be related to the increasing use of English as a global language?”

I’m not exactly sure what this means or what the causal mechanism here would be. I would suggest a simpler explanation: English-speaking countries have tended to follow an economic model (often referred to as the “Anglo-Saxon Model”) that is more market-driven and relies on a smaller welfare state than the rest of Europe. Thus one should expect those countries to have higher levels of market-income inequality. Further, like the U.S., these countries have reformed their tax systems and de-regulated much of their economy, leading to even greater inequality. So while it’s true that increased inequality is not solely a U.S. phenomenon, it does not follow that policy changes aren’t an important part of the explanation. In fact, countries that have followed similar policies to the U.S. have seen increases in inequality, while those that haven’t, well, haven’t.

*I chose the years based on data-availability. I encourage people to play around with the database if they are curious about other countries, years or variables.

It is also worth mentioning that the data presented here is pre-tax gross income. Given that other countries have more progressive tax/transfer systems than the U.S., this is likely an underestimate of the difference in inequality between the U.S. and the rest of the rich world.

A New Way to Measure Poverty

The official federal poverty measure, designed in the 1960s, is the most commonly used indicator of economic hardship in America. Unfortunately, it provides no guidance on pressing questions like the role of regional price variations on poverty or the impact of Food Stamps.

Researchers have been aware of these deficiencies for some time. Now the Census Bureau will begin reporting supplemental poverty measures based on recommendations from the National Academy of Sciences. These new measures will take into account the impact of taxation, in-kind public assistance and medical out-of-pocket costs, and will use more realistic poverty thresholds.

While this is a new step at the federal level, the City of New York has been working on alternative poverty measures since 2008. The efforts of New York City's Center for Economic Opportunity are described here in today's New York Times. A copy of CEO's new report is available on CEO's website for download. It describes the development of the measure as well as poverty trends in NYC between 2005 and 2008.

Why care about inequality?

This is a follow-up post to a previous discussion about economic inequality.

Emmanuel Saez, the UC Berkeley economist, recently produced a fascinating chart on income distribution in the US, depicting the share of national income held by the top 10% of Americans over time:


As you can see, the top 10% of families accounted for roughly 50% of national income in 2007, a level not seen since the time of Jay Gatsby. Though this is only one of numerous measures of income inequality, it clearly shows that the distribution of income in America is more skewed now than at any point since before the Great Depression.

Why should we care about this? There are good economic reasons for discounting measures of inequality. First, economics is not, in general, a zero-sum game. We can all do better even if some gain more than others. And conversely, while some poor societies are highly equal, equal poverty is no great virtue.

Second, there are good reasons why some people make more than others. People who make great innovations (eg the founders of Google) or who have specialized skills (eg neurosurgeons) have every right to be compensated for what they do, since they provide value for society. Bill Gates is enormously wealthy, but he didn't get that way by stealing from others; he became wealthy by providing valuable products to society, making everyone better off (Vista notwithstanding). The carrot of great individual wealth has done much to improve human welfare.

However, there are equally good economic reasons to care about inequality. First, sometimes inequality does result from zero-sum interactions. As Harvard labor economist Larry Katz notes,

"Much of the growth of high-end incomes stemmed from market forces, like technological innovation... But a significant amount also stemmed from the wealthy’s newfound ability to win favorable government contracts, low tax rates and weak financial regulation".

If government is captured by narrow interests, then we are likely to see the growth of policies that privilege one group and do nothing to help (or sometimes even hurt) other groups. A less regressive tax code, for example, helps the wealthy but can hurt the poor.

We should also care about changes in inequality because it can indicate how well the economy is functioning for different groups in society. For this reason it is important to understand what is driving inequality. For example, Katz and co-author Claudia Goldin have argued that inequality has increased because of a decline in the relative supply of highly skilled workers. This suggests that increasing college enrollment (and completion rates) for lower-income groups would stem the growth in inequality and increase incomes for poorer Americans.

On the other hand, Arnold Kling and others have argued that inequality has been driven by changes in technology and the growth of "winner take all" markets, as well as changes in family structure. People today are more likely to marry someone of a similar economic and educational background than they were 50 years ago. This re-enforces inequality among now and in the future, as successful, highly educated parents are likely to have successful, highly educated children. If these are the causes, Kling argues, then there is little government policy to can do to stop them, since we are obviously not going to put restrictions on technological progress or prevent wealthy people from marrying each other.

Inequality is not something that the government can directly set, like interest rates or the budget deficit. It is the product, of complex economic, political and social forces. It is important to recognize that inequality has many causes and that by understanding those causes, we can understand fundamental structures in the economy. We should care about inequality because we should care about an economy that satisfies the needs of everyone in society. By understanding what causes inequality, we can better understand how to get there.

The way we count stuff matters

NYU Law professor Anthony Thompson points out an interesting quirk in the way the census works: prison inmates are counted as living in the same county as their prision, even if they will be released within a year or two. Why does this matter? It has a direct impact on how federal and state congressional districts are drawn and how government money is channeled:

"...the district of State Senator Elizabeth O'C. Little, a Republican in upstate New York, has 13 prisons, adding approximately 13,500 incarcerated "residents." Without the inmate population, Ms. Little would face an uncertain future. Her district would probably have to be redrawn because it wouldn't have enough residents to justify a Senate seat.

The residence rule raises two fundamental issues:

First, inmates in nearly all states aren't allowed to vote, yet their presence affects electoral representation in places where they do not live permanently.

Second, a disproportionate number of state prison inmates are from urban areas. Most state prisons, however, are in rural areas. As a result, resources and electoral authority are transferred from inner cities to rural jurisdictions.

The effects are plain to see. Cities lose out on funds that could be used both for crime prevention and prisoner rehabilitation; rural areas do their best to thwart reform because they don't want to lose the benefits that prisons confer on them."

As I've written before, most American live in what the Census classifies as urban areas. So the residence rule will skew public funds in an inefficient and non-representative way.

Conducting a census presents myriad conceptual issues, and no strategy is perfect. But there's something fundmentally wrong with counting incarcerated citizens who are legally barred from voting towards a district's population total. This will ultimately give voters in those districts disproportionate voting power and will result in policy choices that do not reflect the will of the majority.

Lies, damn lies, refuted by statistics

According to the early reviews, Selena Robert's new book paints a rather unflattering picture of Yankees' third-baseman Alex Rodriguez. Aside from accusing A-Rod of having taken steroids since high school, Roberts alleges that Rodriguez and other opposing players tipped pitches during blow-outs; knowing what pitches were coming, they could improve their statistics.

Unfortunately, Roberts has little more than anonymous sources to support her story. So baseball statisticians had to delve into past seasons in order to find evidence of A-Rod's malfeasance. The stats cast doubt on Robert's allegations:

"If a tipping conspiracy were in place, one would expect that Rodriguez and rival middle infielders in games he played to have hit better in low-leverage situations than in high-leverage ones. Using a fairly loose definition of high leverage as a L.I. above 1.5 and low leverage as below 0.7, the data provide a resounding answer: either no tipping was going on or it was pathetically ineffective.

Contrary to his reputation as a choker, Rodriguez was actually at his best when the game was on the line as a Ranger. According to data compiled by Sean Forman of Baseball-Reference.com, his combined on-base and slugging percentages (O.P.S.) from 2001 to 2003 was 1.076 in high-leverage situations, compared with 1.017 for medium leverage and .982 in low leverage. Opposing second basemen and shortstops showed the same pattern. They registered an .899 O.P.S. when leverage was high, .825 when it was middling, and .817 when it was low. Unless Rodriguez’s behavior was even more nefarious — tipping only when it mattered most — the numbers give no reason to believe he was involved.

Using a more stringent definition of blowouts yields the same result. In plate appearances in which the teams were separated by seven runs or more, Rodriguez mustered just a .851 O.P.S., compared with 1.021 when the margin was six or fewer runs. His middle infield counterparts compiled a .744 mark in the laughers and .840 the rest of the time."

Of course, we should not mistake absence of evidence for evidence of absence. It is possible that A-Rod tipped pitches on rare occasions; rare enough that one or two extra home-runs wouldn't show up in this kind of analysis. But this does provide strong evidence against the possibility that this kind of behavior was widespread. That conclusion may not restore our collective innocence, but it's nice to know.

Making gay marriage count

With Iowa becoming the fourth state in the US to legalize gay marriage, it would seem reasonable to assume that the number of married couples (both heterosexual and homosexual) would increase. Unfortunately, when it does, the federal government won't (officially) take notice. The reason for this, is that the Census Bureau--the government's statistical agency--can't legally count these couples as married:

The federal law banning gay marriage bars the agency from counting same-sex marriages, the Census Bureau says, even though they are legal in Massachusetts, Connecticut, and, most recently, Vermont and Iowa.

Last summer, census officials announced that legally married same-sex couples would be reported as unmarried, same-sex partners.

The 1996 Defense of Marriage Act allows states to refuse recognition of gay marriages from other states, and bars the federal government from recognizing gay couples as "married". This means that when legally married gay couples are surveyed by the Census Bureau, their answers to questions pertaining to marital status will be recoded by Census Bureau statisticians.

It's not all that uncommon for research to be subject to political pressures. But the purpose of the Census Bureau is to be the nation's "leading source of quality data about the nation's people and economy". It's hard to fulfill this role when you're legally bound to deny reality.

And it's not as if this issue is going away anytime soon. According to polling and statistics expert Nate Silver, a majority of states could oppose gay marriage bans by 2012. Momentum is on the side of greater freedom and equality and if the Census Bureau wants to accurately measure marriage rates in the US, they will have to count gay married couples sooner or later.

Fortunately, New York Mayor Mike Bloomberg and City Council Speaker Christine Quinn are advocating for equality and for sanity:

"Although we understand that federal law may not recognize same-sex marriages for the purposes of administration of federal benefits programs," they wrote, "we do not believe it prevents the Census Bureau from reporting statistics from the forms of self-identifying same-sex couples married under state law, like all married couples."

Getting mugged by a girl named Apple

There must be something about being famous that compels parents to give their children stupid names. These crazy celebrity offspring appellations range from place names (like David and Victoria Beckham's child "Brooklyn") to fake-profession titles (Jason Lee's child "Pilot Inspektor") to the obviously drug-induced (Bob Geldof's child "Fifi Trixibell").

Are stupid baby names a problem? According a new study from two economists at Shippensberg University in Pennsylvania, these oddly-named children are more likely to commit crimes than those of us with boring names, like John or Dan. The authors find that:

"The distribution of first names in the state’s population is different from the names of juvenile delinquents. Our results show that unpopular names are positively correlated with juvenile delinquency for both blacks and whites."

The authors note that it is unlikely that having an unpopular name causes juvenile delinquency, but rather that unpopular names are "correlated with factors that increase the tendency toward juvenile delinquency, such as a disadvantaged home environment and residence in a county with low socioeconomic status." This seems strange to me. Why would they embark on a study to show that something correlated with factors that increase crime also are linked with more crime? It seems a little roundabout.

Further, Steven Levitt critiques the questionable methods used in this paper:

"The authors first compute criminality for each name by taking the ratio of the number of juvenile delinquents with that name and dividing it by the number of children total with that name. The higher that ratio, the more criminal the name. But then the authors take the log of that ratio. The problem is that the log of zero is equal to negative infinity, so any name for which that ratio is equal to zero gets dropped from the analysis.

The kinds of names that will have a ratio of zero are uncommon names for which no one with that name is a juvenile delinquent.

If I understand correctly what they are doing, if exactly one person has a particular name, the only way that the observation for that name will be included in their sample is if that person is a juvenile delinquent! This leads to a powerful bias toward mistakenly concluding that people with uncommon names are more likely to be criminals."

Quantitative research is fraught with pitfalls that can bias your results. It seems weird to me that they would have missed something like that, but then again, this study makes little sense to begin with.

Since the success of Malcom Gladwell's "The Tipping Point" and Levitt's "Freakonomics", there has been a tendency for researchers to look for novel and completely unexpected relationships in data. But if you look hard enough (and use certain methods) you can find almost anything. It's really important to ground this sort of research in some sort of theory that one is trying to prove.

The good news is that we don't have to fear the wave of kids with unusual names eminating out of Hollywood.

Enhancing Child Safety and Online Technologies

As promised, here are the links to the Harvard study on the risks faced by minors on the internet. The executive summary is here and the full study is here.

Page 75 of the full study PDF discusses the evidence regarding sexual solicitation online.

Safer than we thought

As I've written recently, many parents and child advocates view social networking sites as online swamps full of lurking sexual predators, kind of like this:



But a new study from researchers at Harvard's Berkman Center for Internet and Society suggests that may be more the product of media hype and parental fears than reality. According to the New York Times (who received a draft version of the report due out tomorrow*):

"The report criticized previous findings that one in five or one in seven minors are sexually propositioned online, saying that in a strong majority of those situations, a child’s peers are responsible for the proposition, which typically amounts to an act of harassment or teasing."

Further, the authors of the study note that in most cases of online sexual predation, "teenagers are typically willing participants and are at risk in other ways (with poor home environments, depression or substance abuse, for example)."

It's doubtful that a study like this will have much impact in the psyche of parents. The dangers of online behavior have been greatly exaggerated for years and empirical evidence is usually overwhelmed by an anecdote or 10 minutes of "To Catch a Predator". But the research supports the conclusion that while the internet provides a new medium for social interaction, people are still people. As John Cardillo--chief executive of Sentinel Tech Holding, which maintains a sex offender database and was a member of the task force--is quoted saying:

“Social networks are very much like real-world communities that are comprised mostly of good people who are there for the right reasons.”

*I'll be sure to post the link as soon as the study is available online.

This just in: 18 year olds talk about sex!

If you want to frighten parents and educators, mention "MySpace". The social networking site has become public enemy number one in the fight against teenage vice. Now, even the medical community is getting involved. According to a study published in the Archives of Pediatrics & Adolescent Medicine, "54 percent of teens talk about behaviors such as sex, alcohol use, and violence on the social networking giant MySpace".

Actually, that quote is a bit misleading. A few paragraphs down, we find out:

The study looked at MySpace profiles of 500 people who identified themselves as 18-year-old males and females in the United States. References to risky behaviors included both words and photos, the authors said.

So this means that 54% of 18-year-olds on MySpace reference sex or drugs (there's no mention of "rock-n-roll" in the study) in their profiles. Let's put aside for a moment the fact that 18-year-olds are legal adults. Studies of the sexual behavior of Ameircan teens reveal that 58% of 18-year-olds in this country have had sex. If you believe these statistics, MySpace users are actually less likely to have sex than the general population.

You may be wondering why anyone would be interested in this (I know I was). Accodring to one of the authors:

Even if teens have not actually engaged in risky behaviors but merely brag about them online, this can still affect their future behavior, said study co-author Dr. Dimitri Christakis, professor of pediatrics at the University of Washington and director of the Center for Child Health, Behavior and Development at Seattle Children's Hospital.

Those who lie about the behaviors to show off may receive positive feedback from others -- comments such as "that's great" or "I do the same thing" -- that encourage them to actually try out the behaviors, he said.

So the danger here is not MySpace, per se, but rather peer pressure--pressure that results from essentially any contact with peers.  That means that if MySpace is dangerous, then so are cell phones, or any other communication device.  If MySpace is dangerous, so is talking.

Interestingly, one of the researchers makes this point, though it is buried in the article:

"It's really not that MySpace is bad or good. I think the lesson is that it's a tool, and how you use it determines the kinds of outcome you're going to get," Moreno said.

Technology changes, but people typically stay the same.  Teenagers--in this case, young adults--think about, and talk about, sex.  It's easier to see that now that social networking sites have gained popularity.  But just because it's more apparent, doesn't mean it's new.  

Doogie Howser, PhD

In the Funny or Die video "Proposition 8 - The Musical", Neil Patrick Harris brings together supporters and opponents of the ballot measure by reminding everyone that there's money to be made in gay marriage. According to Ian Ayers over at Freakonomics, NPH isn't the first to have this idea. Jennifer Gerard Brown, Ayers co-author, estimated that:

"...the present value of a change in marriage law for the first-mover state could reach three or four billion dollars. [E]ach tourist dollar spent generates additional private income, tax revenue, and jobs. Forbes magazine recently estimated that if same-sex couples currently living together would marry, they would spend $16.8 billion in the first several years following legalization."

Ayers also points out that "Brad Sears and Lee Badgett have estimated that same-sex marriage would “boost California state and local government revenues by over $63.8 million.'"

Same-sex marriage doesn't need to be justified on the basis of economic benefits. But it's a useful reminder that restrictions on human liberty don't lead to prosperity.

There's a 94% chance that my marriage will succeed!

I'm getting married next year, so I was intrigued when Justin Wolfers, writing in the Freakonomics blog, posted about a widget that calculates your risk for divorce.

The divorce calculator is based on research from Wolfers partner and frequent collaborator, Betsy Stevenson. One of the interesting trends that it highlights is that divorce risk varies greatly among different groups. Specifically, women with higher levels of education are much more likely to be married and stay married. Good news for me, as my fiance has a graduate degree.

In the past 30 years, there has been a shift from marriage as a division of labor (the 50's-style woman as homemaker and man as bread winner) to marriage as a matching of consumption patterns (both partners earn money and use it to enjoy their leasure time together)*. This is in part due to the increase in labor saving technologies that reduce the relative value of low-educated marriage partners. This, of course helps explain the differences in marriage rates by education level.

Of course, this presents a public policy dilemma. Stable families are a very strong predictor of student academic achievement. But education levels are a good predictor of family (more specifically marriage) stability. Clearly you can't address one problem without addressing the other.

*yes, my fiance loves it when I use econ-jargon to talk about marriage.

I hope the TV was wearing protection

Journalists have a tendency to get over-excited when reporting the results of scientific research. So I wasn't surprised yesterday when I saw the following headline:

Study links sex on TV to teen pregnancy

Just when we thought we could keep our kids safe at home!

According to CNN:

Researchers at the nonprofit organization found that adolescents with a high level of exposure to television shows with sexual content are twice as likely to get pregnant or impregnate someone as those who saw fewer programs of this kind over a period of three years.

So is it time to turn off Gossip Girl? Perhaps not. Studies like this are good for showing correlations, or the fact that a relationship between two variables exists. They are less apt at proving what causes what. Consider this critique from the Tara Parker-Pope:

"...a closer look at the data shows the relationship between television, sexual content and teen pregnancies is complex. The same study, published today in Pediatrics, also found that teens who watch a lot of television in general are less likely to become pregnant. How can that be? The answer may be that kids who watch a lot of television obviously aren’t out dating and socializing with friends. So as unhealthy as it may be to spend hours in front of a screen, the behavior appears to be oddly protective against teen pregnancy...The link between television and teen pregnancy only shows up when a high proportion of the television shows watched by a teen are filled with sexual content."

So TV has two potential effects on teen sexual behavior. But it is also possible that there is some unobserved factor out there, which is actually at work. It is quite likely that teens who are more sexually active have a preference for more sexually explicit shows. This might make sense given the fact that while TV overall has gotten steamier, the overall teen pregnancy rate has gone down.

Either way, the authors conclude with a point that's hard to argue with:

“If the type of sexual portrayals that teens see on TV are the only messages they’re getting about sex, then they’re likely to approach sexual relationships in a way that might not be the healthiest way,” said Steven Martino, study co-author and a behavioral scientist at the RAND Corporation, the nonprofit health care research firm that conducted the study. “It’s important to talk to them about that and see how they’re reacting, and offer other perspectives to them about sex that they might not be getting on television.”