Do tax increases discourage the wealthy from working hard?

Judge Richard Posner (who's considered "conservative") has this to say on the subject:

Increasing income taxes can . . . reduce the amount of work. But when the issue is increasing marginal income tax rates, the likelihood of a significant effect on work depends critically not only on the amount of the increase but also on where the margin is set. The Obama Administration proposes by allowing some of the Bush tax cuts to expire on schedule to increase the marginal income tax rate of persons whose taxable income exceeds $250,000 a year from 35 to 39.6 percent. . . . The effect on most of these taxpayers would be small. Suppose a person earning $300,000 in taxable income pays $75,000 in taxes currently. If his marginal rate (the rate for taxable income above $250,000) rises from 35 to 39.6 percent (for simplicity I’ll round this up to 40 percent), then his total income tax bill will rise from $75,000 to $77,500 (because on the last $50,000 of his income he will pay an extra 5 percent in tax). Will this increase in his total federal income tax bill, of 3.3 percent, cause him to work less? I would like to see evidence that it would.

Because of tax avoidance opportunities, it seems that very few people pay more than about a quarter of their income in federal income tax. Suppose someone has an income of $10 million on which he currently pays $2.5 million in income tax. The Administration’s tax increase would raise his income tax by $487,500 ([$10 million - $250,000] x .05), or slightly less than 20 percent. Would that affect how hard he works? I’m skeptical.

Income tax on earned income . . . does increase the cost of work relative to leisure, which is the basis for concern that increasing income tax rates, especially marginal rates, will cause a shift from work to leisure (and . . . to nonpecuniary work such as household production). But there is another effect: by lowering disposable income, an increase in income tax may cause a person to work harder in order to maintain his previous standard of living. The net effect on income of a higher tax is therefore uncertain. . . .

Americans are accustomed to working hard and to achieving and maintaining a high level of expenditure on consumer goods. In addition, people who earn high incomes tend to be highly competitive and to rate themselves by their income relative to the income of peers. Because of the absence of an aristocracy and the presence of a generally philistine attitude toward culture, money is the key index to prestige and social standing in the United States and, for many Americans, to a feeling of self-worth. These features of American society lead to me to be skeptical in general about the effect on work and therefore income of increasing marginal income tax rates to the levels contempated by the Administration.

A Berkeley economics professor, Owen Zidar, has studied the macroeconomic effects of tax changes on different income groups by looking at decades of data on U.S. federal and state taxes (respectively, from 1945-2010 and 1980-2011). (Here's the abstract with a link to download the whole paper.) He concludes:

Do tax cuts that go to high income taxpayers generate more output and employment growth than similarly sized tax cuts for low and moderate income taxpayers? . . .

If tax cuts for high-income earners generate substantial economic activity and job creation, then we should expect to see three things in the data. First, employment growth should tend to be higher in the years following exogenous tax cuts for the rich. Second, places with a higher share of rich people should grow faster following national tax cuts for the rich (since these areas receive more tax cuts for rich people in dollar per capita terms). Similarly, growth should be lower following tax increases on the rich, especially in places where many rich people live. None of these predictions are born out out in the data.

I find that the relationship between upper income tax changes and growth is negligible in magnitude and substantially weaker than equivalently sized tax changes for the bottom 90%. The point estimates suggest that almost all of the stimulative effect of exogenous tax cuts is due to tax cuts for the bottom 90%. Differential consumption responses help explain why a dollar of tax cuts for the top 10% produces less growth than those for the bottom 90%. Investment responses are also stronger following tax cuts for the bottom 90%, suggesting that the effects of additional economic growth tend to exceed the effects from income changes among those who are more likely to save. Overall, tax cuts for the bottom 90% tend to result in more output, employment, consumption and investment growth than equivalently sized tax cuts for the top 10%.

(You might object that this kind of study is skewed by the fact that taxes are sometimes raised or cut in response to specific economic conditions. But Professor Zidar tried to exclude those kinds of tax changes from his study.)

Attorney General Eric Holder: “The facts are clear. Intimate partner homicide is the leading cause of death for African-American women ages 15 to 45."

And he's right that the facts are clear. The facts are clear that Holder is wrong.

As that Volokh Conspiracy blog post explains (corroborating a column by Christina Hoff Sommers), homicide is not the most common cause of death of African-American women ages 15 to 45. It's the 5th most common. And those are homicides by anyone, including strangers; only a fraction of them involve domestic violence.

Sommers adds:

Holder's patently false assertion has remained on the Justice Department website for more than a year.

How is that possible? It is possible because false claims about male domestic violence are ubiquitous and immune to refutation. During the era of the infamous Super Bowl Hoax, it was widely believed that on Super Bowl Sundays, violence against women increases 40%. Journalists began to refer to the game as the "abuse bowl" and quoted experts who explained how male viewers, intoxicated and pumped up with testosterone, could "explode like mad linemen." During the 1993 Super Bowl, NBC ran a public service announcement warning men they would go to jail for attacking their wives.

In this roiling sea of media credulity, one lone journalist, Washington Post reporter Ken Ringle, checked the facts. As it turned out, there was no source: An activist had misunderstood something she read, jumped to her sensational conclusion, announced it at a news conference and an urban myth was born. Despite occasional efforts to prove the story true, no one has ever managed to link the Super Bowl to domestic battery.

Snopes has a longer takedown of the Super Bowl myth. Snopes concludes:

The ensuing weeks and months saw a fair amount of backpedalling by those who had propagated the Super Bowl Sunday violence myth, but — as usual — the retractions and corrections received far less attention than the sensational-but-false stories everyone wanted to believe, and the bogus Super Bowl statistic remains a widely-cited and believed piece of misinformation. As Sommers concluded, "How a belief in that misandrist canard can make the world a better place for women is not explained."

Do laws against texting while driving reduce or increase car crashes?

You might think: of course those laws make the roads safer. But that's far from obvious (via):

Researchers at the Highway Loss Data Institute compared rates of collision insurance claims in four states — California, Louisiana, Minnesota and Washington — before and after they enacted texting bans. Crash rates rose in three of the states after bans were enacted.

The Highway Loss group theorizes that drivers try to evade police by lowering their phones when texting, increasing the risk by taking their eyes even further from the road and for a longer time.

The findings "call into question the way policymakers are trying to address the problem of distracted-driving crashes," Lund says, calling for a strategy that goes beyond cellphones to hit other behaviors such as eating and putting on makeup. "They're focusing on a single manifestation of distracted driving and banning it," he says.

But I'm skeptical of these conclusions as the article presents them. Look again at that sentence: "Crash rates rose in three of the states after bans were enacted." It doesn't tell us how much the rates rose. When journalists report on research that shows an increase or decrease in anything, I wish they'd tell us how big the increase or decrease was.

I've been noticing this a lot lately. For instance, this article tells us that religious people give "more" donations to charity and do "more" volunteer work; this one says religious people have "higher levels of 'life satisfaction.'" But they don't tell us how much more (or higher). If anything, I'd guess that the difference was fairly small; otherwise, the reporter probably would have wanted to quantify it in order to impress us with the finding.


Short URL for this post: goo.gl/Vm0m

Scientific happiness studies are missing the point.

"The fundamental error of the science - and the reason why so many of its recommendations sound trivial or just confused - is the assumption that happiness is the same as positive emotion. Researchers are continuously drawn back to this idea since it makes happiness measurable."

So says Mark Vernon (who also writes the excellent "Philosophy and Life Blog"), channeling Robert Schoch's book The Secrets of Happiness: Three Thousand Years of Searching for the Good Life.

The whole article is well worth reading and worth keeping in mind the next time someone tries to tell you that researchers have discovered that people who do such-and-such are "happier" than people who do so-and-so.

Does music describe things?

The blog Cognitive Daily has conducted an experiment to find out something that musicians and composers have always known: music is ineffectual at describing things in the external world.

Of course, a lot of music is meant to accompany extra-musical images or stories. There are tone poems, movie soundtracks, the Fantasia movies, Peter and the Wolf, and for that matter, song lyrics in general.

But you need to be explicitly shown or told what the music is supposed to evoke -- which means the music on its own doesn't evoke specific things.

Here's how Cognitive Daily did the experiment: they conducted a survey of their blog readers, in which they embedded audio clips from supposedly descriptive pieces of music and asked the readers to say what the music described. For instance, the survey included

a selection from Claude Debussy's La Mer, from the movement intended to represent the wind and the sea. Only 36 of 357 respondents answered correctly. Even when I gave half-credit for mentioning either the wind, or a storm, or waves, or a boat, only an additional 90 got it. Most respondents -- over 200, in fact, got it completely wrong.

I picked seven different clips like this, from seven different works that were all intended by their composers to represent specific things, not just emotions or adjectives. I tried to pick pieces that seemed relatively obvious, based on the composer's initial intentions. I scored each response on a scale of 0 to 2, with 2 being perfect, and 1 meaning some portion of the response was correct. The average score was a mere 0.38, and 72 percent of the time people got the answer completely wrong.

Respondents with musical training did better than those without it, but "not much better."

I'm reminded of an anecdote about a critic who was writing a review of Mendelssohn's Symphony No. 3, the "Scottish" Symphony (sometimes awkwardly called the "Scotch" Symphony) when it first came out. The critic exulted that Mendelssohn had perfectly captured the essence of Scotland. He had inadvertently listened to Mendelssohn's Fourth, the "Italian" Symphony, which, as you might have guessed, was supposed to evoke Italy, not Scotland.

I do think music is meaningful and important, but for other reasons (which I'll go into in a future blog post). It's not important because it "describes" or "depicts" nature, or a city, or a person. Music doesn't "describe" or "depict" anything.

The famous composer Aaron Copland wrote, in his book What to Listen for in Music (1939):

My own belief is that all music has an expressive power, some more and some less, but that all music has a certain meaning behind the notes and that the meaning behind the notes constitutes, after all, what the piece is saying, what the piece is about.

This whole problem can be stated quite simply by asking, "Is there a meaning to music?" My answer to that would be, "Yes." And "Can you state in so many words what the meaning is?" My answer to that would be, "No."

Therein lies the difficulty. Simple-minded souls will never be satisfied with the answer to the second of these questions.

They always want music to have a meaning, and the more concrete it is the better they like it. The more the music reminds them of a train, a storm, a funeral, or any other familiar conception the more expressive it appears to them.

This popular idea of music's meaning -- stimulated and abetted by the usual run of musical commentator -- should be discouraged wherever and whenever it is met.

One timid lady once confessed to me that she suspected something seriously lacking in her appreciation of music because of her inability to connect it with anything definite. That is getting the whole thing backward, of course.*

Copland said more about this question, based on intuition and experience, than any scientific experiment could.



(That's the movement from Debussy's La Mer that the Cognitive Daily survey had readers listen to, "Dialogue du vent et de la mer," conducted by Herbert von Karajan.)

* Line breaks added for readability.

Do women earn less money than men for equal work?

Economics professor Nancy Folbre says they do, in this blog post that the New York Times' website published yesterday. At the top of her post, she claims:

Tuesday is the day on which women’s wages catch up to men’s wages from the preceding week. On average, female workers have to put in more than six days of paid work to earn what men earn in five.

Among those who usually worked full time during the first quarter of 2009, women’s median weekly earnings were 79 percent those of men. That implies that the catch-up clock for them rings at about 10:38 a.m. on Tuesdays (assuming a standard five-day week and eight-hour day starting at 8 a.m.).

Some women earn less than men because they choose less lucrative occupations or take more time out from employment. But a 2003 Government Accountability Office study controlling statistically for these factors showed that women’s average pay between 1983 and 2000 flat-lined at about 80 percent of men’s over the entire period.

You'll notice that her link on the word "study" goes to this PDF of the 2003 U.S. government report. Well, if you actually click the link and read the report, you'll find that her summary is literally correct but misleading. The authors conceded that while they tried to control for confounding factors, they might have failed to adequately consider others:

[W]omen have fewer years of work experience, work fewer hours per year, are less likely to work a full-time schedule, and leave the labor force for longer periods of time than men. Other factors that account for earnings differences include industry, occupation, race, marital status, and job tenure....

Even after accounting for key factors that affect earnings, our model could not explain all of the difference in earnings between men and women. Due to inherent limitations in the survey data and in statistical analysis, we cannot determine whether this remaining difference is due to discrimination or other factors that may affect earnings. For example, some experts said that some women trade off career advancement or higher earnings for a job that offers flexibility to manage work and family responsibilities.

In conclusion, while we were able to account for much of the difference in earnings between men and women, we were not able to explain the remaining earnings difference. It is difficult to evaluate this remaining portion without a full understanding of what contributes to this difference. Specifically, an earnings difference that results from individuals’ decisions about how to manage work and family responsibilities may not necessarily indicate a problem unless these decisions are not freely made. On the other hand, an earnings difference may result from discrimination in the workplace or subtler discrimination about what types of career or job choices women can make. Nonetheless, it is difficult, and in some cases, may be impossible, to precisely measure and quantify individual decisions and possible discrimination. Because these factors are not readily measurable, interpreting any remaining earnings difference is problematic.

Now, maybe you think 80% is such a huge discrepancy that it couldn't plausibly be explained by unmeasured factors.

But that's an old report -- it only looked at data up to 2000. The GAO released a new report yesterday that looks at data from as recently as 2007 and suggests that we should be much more optimistic:

GAO used data from the Office of Personnel Management's (OPM) Central Personnel Data File (CPDF)--a database that contains salary and employment data for the majority of employees in the executive branch. GAO used these data to analyze (1) "snapshots" of the workforce as a whole at three points in time (1988, 1998, and 2007) to show changes over a 20-year period, and (2) the group, or cohort, of employees who began their federal careers in 1988 to track their pay over a 20-year period and examine the effects of breaks in service and use of unpaid leave....

The gender pay gap--the difference between men's and women's average salaries--declined significantly in the federal workforce between 1988 and 2007. Specifically, the gap declined from 28 cents on the dollar in 1988 to 19 cents in 1998 and further to 11 cents in 2007. For the 3 years we examined, all but about 7 cents of the gap can be explained by differences in measurable factors such as the occupations of men and women and, to a lesser extent, other factors such as education levels and years of federal experience. The pay gap narrowed as men and women in the federal workforce increasingly shared similar characteristics in terms of the jobs they held, their educational attainment, and their levels of experience. For example, the professional, administrative, and clerical occupations--which accounted for 68 percent of all federal jobs in 2007--have become more integrated by gender since 1988. Some or all of the remaining 7 cent gap might be explained by factors for which we lacked data or are difficult to measure, such as work experience outside the federal government. Finally, it is important to note that this analysis neither confirms nor refutes the presence of discriminatory practices.

GAO's case study analysis of workers who entered the workforce in 1988 found that the pay gap between men and women in this group grew overall from 22 to 25 cents on the dollar between 1988 and 2007. As with the overall federal workforce, differences between men and women that can affect pay explained a significant portion of the pay gap over the 20-year period. In particular, differences in occupations explained from 11 to 19 cents of the gap over this period.

Prof. Folbre acknowledges this study and blandly recites a few of its findings, but she buries it under her sweeping, sensationalistic announcement that women need to work till "10:38 a.m." on Tuesday of a second week to catch up to what men make in one week.

She also asserts that "the pay gap is narrower among federal employees than in the work force as a whole." Her theory for why this is the case: "Job descriptions are more standardized in government employment, and salaries are a matter of public record."

But is that what's really going on? Is federal government hiring more enlightened than hiring in America as a whole?

Or is it simply easier to effectively control for variables when you're looking at a narrower slice of the whole job market?

A commenter on her post ("Milton Recht") gives some specific reasons to think so:

[T]he reason that non-government job studies show a greater gender wage difference that the government sector is that the statistics on private sector wages do not include the employer cost of benefits as part of the wage. All government jobs provide about equal benefits.

Studies are published that show women on average will choose a job with better benefits over higher salary and men on average choose jobs with higher salaries over better benefits. The same studies show that men on average will choose a job without health benefits for higher salaries and women on average will not.

When private sector benefits are adjusted to include employer cost of benefits, the private sector difference shrinks to about the same seven percent difference as government wages....

[T]here are probably valid non-observed, non-discriminatory variables for the pay gap. Otherwise, any employer would be foolish not to hire the cheaper labor if it were comparable in every other aspect except gender.

I realize he's referring to "studies" without mentioning or linking to them, so I'm skeptical of his specific claims. But his theory seems more plausible to me than Prof. Folbre's conclusions, even though she links to several empirical studies.

[UPDATE: Since I wrote that, Milton Recht dropped by in the comments of this post and added details: "A January 2009 Department of Labor study (link below) that studies of gender wage discrimination do not include total compensation." He quotes from the study:

Specifically, CONSAD’s model and much of the literature, including the Bureau of Labor Statistics Highlights of Women’s Earnings, focus on wages rather than total compensation. Research indicates that women may value non-wage benefits more than men do, and as a result prefer to take a greater portion of their compensation in the form of health insurance and other fringe benefits.]

More citations, links, and figures don't necessarily add up to a better analysis. For instance, Prof. Folbre's link to support her claim that women overall catch up on Tuesday at 10:38 a.m. doesn't seem to make any attempt to control for confounding factors. The report she links to simply says:

Women who usually worked full time had median earnings of $649 per week, or 78.9 percent of the $823 median for men.

That's essentially meaningless if we don't know a lot more details about what kinds of jobs they had, what their credentials were, and how much they worked. (Perhaps the study secretly controlled for these factors, but if so, it's not apparent from the link.) Of course, Prof. Folbre emphasizes these findings over the GAO reports.

It's nice to link to multiple studies and invoke the principle of controlling for variables. But if you ultimately cherry-pick the gloomiest-sounding figures you can find, and -- whoops! -- by the way, forget about those pesky variables, context, and alternate explanations based on factors other than sexism ... then you've given up any pretense to empirical validity.


UPDATE: Comments over here.

What's the most energy-efficient state in the US?

Apparently the answer is my state, New York.

You can see the info for all states in this interactive map.

(Via the Freakonomics blog. If you're interested in the full report by the Rocky Mountain Institute, here's the PDF.)

Could this be some of the fruits of "elevator environmentalism" in NYC?

Maybe that's part of it, but there seems to be a problem with how the report measures energy efficiency. They did it "by dividing each state’s G.D.P. by the kilowatt hours of electricity it consumed." As a commenter on the Freakonomics blog says:

This study assumes all kinds of weird relationships between energy and GDP that just don’t seem to be accurate. You know why New York is so high on that list? Because banking takes a lot less energy than farming does to produce money. You know why Mississippi and Kentucky are at the bottom? Because farming and coal mining are energy intensive and produce inexpensive products.

So what’s the answer then? Stop farming and make every state convert to a white collar economy? Doesn’t seem feasible to me.

Tellingly, the blog post does ask readers for feedback, but only feedback on "how to close the gap" among the different states, not suggestions for more useful ways to frame the problem or measure the gap.

In fairness, the authors of the study show up in the comments section to defend their conclusions. Do you think their defense is very convincing? They claim to control for a lot of variables. But even taking them at their word, there seems to be a deeper problem, which is that a lot of the energy-intensive activity (farming, etc.) that's done by the lower-ranked states makes it possible for, say, New Yorkers to enjoy the array of modern conveniences that make it so comfortable to live the lifestyle of, say, a reasonably affluent office worker in the Northeast. (I don't want to overstate this as if it were some kind of clear-cut dichotomy: the report ranks California, which produces enormous amounts of food among other goods, as one of the most energy-efficient states.)

In other words, the suggestion that the supposedly less efficient states should simply conform to the more efficient ones may be a nice thought -- but it's easy to wish for the world we're living in to be better. We're able to look at it first-hand, up close, and vividly see its many flaws. It's a lot harder to see how all the interconnected parts of the hulking, complicated machinery of society might be thrown out of whack if we made the proposed sweeping reforms -- even on the overly optimistic assumption that they'd be implemented brilliantly and in good faith. (By the way, for those readers who might think of me as a liberal, I'm try to invoke a conservative principle here.)

And of course,

New York being #1 in GDP/kWh just shows what you can do by fabricating earnings on Wall Street. They will not be #1 on that list for long.

Another commenter has a similar point but, I think, takes it too far:

Look at the list of the most efficient by kWh. 7 of the 10 have little in the way of "real" wealth creation industries - by which I mean either farming/extraction or manufacturing. If you want to create real wealth that doesn’t involve repackaging money or ideas a dozen times, then I think a different metric is required.

I don't know how you can distinguish "real" wealth from non-"real" wealth. Why are farming and manufacturing the only things that are "real"?

Why isn't work that gets done in New York "real"?

This calls for some My Dinner with Andre, specifically Wally's rant:

I mean, is Mount Everest more "real" than New York? I mean, isn't New York "real"? I mean, you see, I think if you could become fully aware of what existed in the cigar store next door to this restaurant, I think it would just blow your brains out! I mean...I mean, isn't there just as much "reality" to be perceived in the cigar store as there is on Mount Everest? I mean, what do you think? You see, I think that not only is there nothing more real about Mount Everest, I think there's nothing that different, in a certain way. I mean, because reality is uniform, in a way....