In E-Commerce there is no doubt that the negotiators of TPP did agree to provisions that strongly advance liberalization of Internet trade flows and the enhancement of commerce and investment through the medium of cyberspace

See What it Means for the Digital Economy by Claude Barfield Former Consultant, Office of the U.S. Trade Representative. He is a Resident Scholar at the American Enterprise Institute.

"There has been a good deal of hype touting the recently concluded Trans-Pacific Partnership (TPP) agreement as the first “21^st Century” trade pact.   Whether it lives up to this high accolade is currently under debate, both in the United States and among the 11 other TPP member states.  But in one area—E-Commerce—there is no doubt that the negotiators did agree to provisions that strongly advance liberalization of Internet trade flows and the enhancement of commerce and investment through the medium of cyberspace.     

The E-Commerce chapter consists of the following new rules and mandates (among others):

• Cross-Border Data Transfers—Article 14.11 requires TPP governments to allow the cross-border transfer of information, including personal information, for the conduct of business.  The only exception to this obligation is in the pursuit of a “legitimate public policy objective.”  The exception, however, cannot be undertaken in a manner that constitutes arbitrary or unjustifiable discrimination.
• Forced Localization—Article 14.13 no TPP may require a business to locate computing facilities (including servers and storage devices) within its territory, with the same public necessity provision described above.  US officials state that this provision is the first in a free trade agreement;
• Transfer of Source Code—Article 14.17 prohibits the requirement to transfer software source codes as a condition of doing business or investing in a TPP country. There is an exclusion from this rule for “critical infrastructure” (undefined).
• Customs Duties on Internet Traffic—Article 14.3 prohibits the imposition of customs duties on cross electronic transmissions.  This prohibition, however, does not preclude TPP countries from imposing internal taxes or fees on content transmitted electronically.
• Privacy and Consumer Protection—In addition, other sections of the chapter contain consumer protection requirements, as well as mandates to provide domestic users with full information concerning their privacy rights.

The entire E-Commerce chapter comes under the full scope of the TPP dispute settlement system.

If the TPP is ratified by the TPP members states and comes into force, it will have far-reaching strategic implications for both the world trading system and the future of the Internet.   Even before expected expansion to other Asian and non-Asian nations (Korea, Thailand, Indonesia, Colombia, as examples), the TPP already covers one quarter of world trade and about 40 percent of world GDP.  As such, future rules for Internet-related trade and investment will be greatly influenced and directed by established TPP rules.  This is particularly true in that international rules and norms for the Internet are just in their infancy, and thus the timing of the TPP is crucially important.

Finally, the next few years will see a huge growth in Internet traffic and utilization for key commercial goals.  In 2005, there were an estimated one billion Internet users; that number doubled by 2010.  It reached three billion in 2014, and is expected to growth to over five billion by 2020.  President Obama has warned, correctly, that if the U.S. and its TPP trading partners don’t write the “rules of the road” for the Internet, others (read: China) will.  Should the fractured U.S. political situation result in a failed TPP, the country will pay a heavy price, both economically and strategically."

A Two-Millennia Relationship Between Climate and Economic Data

By Craig D. Idso of Cato.

"Introducing their intriguing work, Wei et al. (2015) write that “investigating climate-society relationships has long been a hot topic,” noting that “many studies have demonstrated the important roles of climate change in facilitating the rise or fall of ancient communities.” However, they report that “intense arguments regarding the economic effects of global warming” remain to be clarified in such investigations.

Against this backdrop, Wei et al. set out to investigate the long-term relationship between the climate and economy of China. More specifically, they derived a 2,130-year long record of the Chinese economy based on 1,091 records extracted from 25 books on Chinese history and economic history, spanning the period 220 BC to 1910 AD. This new proxy was then statistically analyzed in conjunction with historical proxies of Chinese temperature and precipitation previously compiled by Ge et al. (2013) and Zheng et al. (2006), respectively. And what did that analysis reveal?

The three Chinese researchers found that warm and wet climate periods coincided with more prosperous and robust economic phases (above-average mean economic level, higher ratio of economic prosperity, and less intense variations), whereas opposite economic conditions ensued during cold and dry periods (where the possibility of economic crisis was “greatly increased”) (see Figure 1 below). They also report that temperature was “more influential than precipitation in explaining the long-term economic fluctuations, whereas precipitation displayed more significant effects on the short-term macro-economic cycle.”

In concluding their paper Wei et al. write that, “from a deep time perspective, our study may provide new insight into the current intense arguments regarding the economic effects of global warming.” Indeed it does; and that insight reveals a warmer (and wetter) climate favors economic prosperity. Given this data-derived relationship, why are the leaders of so many nations hell-bent on halting any future rise in global temperature, especially when two millennia of climate and economic data suggest such a rise would benefit the economy? As the late Casey Stengel would have said, “doesn’t anybody know how to play this game?”

Figure 1. Series comparison between economic fluctuations and climate changes in China from BC 220 to AD 1910. Panel a: Decadal temperature anomaly for all of China during the period AD 1–1910 (Ge et al. 2013); the red curve is the low-pass filtered series. Panel b: Decadal precipitation over eastern China during the period 101–1910 (Zheng et al. 2006); the blue curve is the low-pass filtered series. Panel c: Winter half-year temperature anomaly series for eastern China during the period BC 210–AD 1920 with a 30-year resolution (Ge 2011). Panel d: Decadal macro-economic series during the period BC 220–AD 1910 in China; the black curve is the low-pass filtered series. The red and blue bars indicate typical episodes of prosperity and crisis periods (respectively). The gray and white areas delineate cold and warm phases, respectively. Figure from Wei et al. (2015)."

It is incorrect to assume that (X-M) < 0 necessarily “is dragging down GDP”

See Trade Deficits and C+I+G+(X-M) by Don Boudreaux of Cafe Hayek.

"This letter is to a businessman who heard an interview that I did yesterday on Ross Kaminsky’s show on KOA Radio out of Denver.

Mr. Kevin K_____:
Dear Mr. K_____:

Thanks for listening.

In response to my attempt to calm the fears of those who worry about the U.S. trade deficit, you correctly note that “imports minus exports is part of the GDP equation” and that “if it [imports minus exports] is always negative, then it is dragging down GDP.”  You then understandably ask “How can this be considered ‘good’ in any way?”

You refer, of course, to this identity: GDP = C [consumption spending] + I [investment spending] + G [government spending] + (X [exports] – M [imports]).  Ignore here the many problems that infect the simplistic Keynesian notion of describing the size or health of an economy exclusively by aggregate spending. Instead realize that, contrary to the impression conveyed by the GDP=C+I+G+(X-M) identity, the size of C, of I, and of G are not independent of the size of (X-M).  That is, for a variety of reasons, an increase in the size of the absolute value of (X-M), when X

Consider, for example, investment spending.  When foreigners shift the spending of their dollars such that they buy fewer American exports in order to enable themselves to invest more in America – say, by starting or expanding foreign-owned companies in the U.S. – the resulting rise in the U.S. trade deficit is accompanied by an increase in investment spending (I) in the U.S.  Or consider government spending. When foreigners lend more of their dollars to Uncle Sam or to the State of Colorado, not only does the U.S. trade deficit rise, government spending (G) in the U.S. also rises – and it does so without the corresponding fall in consumption (C) or investment spending (I) that would occur had those loans been made exclusively by Americans or had this government spending been funded with hikes in Americans’ current taxes.

The bottom line is that it is incorrect to assume that (X-M) < 0 – again, loosely speaking, a trade deficit – necessarily “is dragging down GDP.”

Sincerely,

Donald J. Boudreaux
Professor of Economics
and
Martha and Nelson Getchell Chair for the Study of Free Market Capitalism at the Mercatus Center
George Mason University
Fairfax, VA 22030

UPDATE: Pierre Lemieux reminds me that the matter is even simpler than I explain in the above letter.  See Pierre’s excellent explanation in the Fall 2015 issue of Regulation."

By Bernanke's criteria monetary policy became very tight in the second half of 2008

See Beckworth and Ponnuru on 2008 by Scott Sumner.

"David Beckworth and Ramesh Ponnuru have produced some excellent pieces on the mistakes made by the Fed in 2008. Here's an excerpt from their latest:

Krugman thinks the behavior of long-term real interest rates contradicts our thesis. They rose in the middle of 2008, but not, he says, catastrophically, as they should have if the Fed were really running a much-too-tight policy. Krugman is incorrect about the implications of our account. We would expect the Fed's contractionary mistakes to have led to an increase in the risk premium. It did. We would also expect it to reduce the prospects of economic growth and thus lead to a decline in long-term real interest rates adjusted for the risk premium. Again, that's what happened.

Read the whole article, it's great.

 I find it very odd that Krugman would claim that real interest rates are a good indicator of whether Fed policy is effectively getting tighter. After all, real interest rates soared right after Lehman failed, to over 4%. And yet that dramatic increase is strangely missing from the Krugman post they link to:

I'd just add that if there were anything to this story, we should have seen a sharp increase in long-term real interest rates, as investors saw the Fed getting behind the disinflationary curve. Here's the real 10-year rate in the months leading up to Lehman:

Why did Krugman leave off that surge in real interest rates? Perhaps because it would imply that money got really tight in late 2008 and, AFAIK, none of the mainstream Keynesians were saying that money was really tight at that time. Although I was not yet blogging, I was complaining about Fed policy to people I met, like Greg Mankiw and Robert Barro.

The second reason I found Krugman's claim to be odd is that he had previously criticized Friedman's frequent assertion that the Fed caused the Great Contraction of 1929-33 with a tight money policy. Krugman insisted that Friedman was being "intellectually dishonest" because, (according to Krugman) the Fed did not cause the downturn, they failed to prevent it.

As people like Nick Rowe frequently point out, the distinction between causing and failing to prevent is meaningless unless one can agree one what it means for the central bank to be "doing something". But economists do not agree, indeed Paul Krugman doesn't even agree with himself. When dismissing Friedman's argument he pointed out that the monetary base increased between 1929 and 1933. So in that case Krugman saw the monetary base, not real interest rates, as the proper metric of Fed action, or inaction. I suppose this is not surprising, because given the rapid deflation of 1929-33, many experts believe real interest rates shot up to very high levels. So if Krugman's current criticism of Beckworth and Ponnuru is correct, then his earlier criticism of Friedman is discredited.

 But it gets even worse. Real interest rates are not a reliable indictor of the stance of monetary policy, as Beckworth and Ponnuru explain. And this is not just a market monetarist view, it's also Ben Bernanke's view:

The imperfect reliability of money growth as an indicator of monetary policy is unfortunate, because we don't really have anything satisfactory to replace it. As emphasized by Friedman (in his eleventh proposition) and by Allan Meltzer, nominal interest rates are not good indicators of the stance of policy, as a high nominal interest rate can indicate either monetary tightness or ease, depending on the state of inflation expectations. Indeed, confusing low nominal interest rates with monetary ease was the source of major problems in the 1930s, and it has perhaps been a problem in Japan in recent years as well. The real short-term interest rate, another candidate measure of policy stance, is also imperfect, because it mixes monetary and real influences, such as the rate of productivity growth. In addition, the value of specific policy indicators can be affected by the nature of the operating regime employed by the central bank, as shown for example in empirical work of mine with Ilian Mihov.

In the same speech, Bernanke suggested a better indicator of the stance of policy:

Ultimately, it appears, one can check to see if an economy has a stable monetary background only by looking at macroeconomic indicators such as nominal GDP growth and inflation. On this criterion it appears that modern central bankers have taken Milton Friedman's advice to heart.

But wait a minute, didn't NGDP and the price level fall in the second half of 2008? Yes they did, and so by Bernanke's criteria monetary policy became very tight. 

 

Of course Bernanke later became Fed chair, and obviously isn't going to blame the Fed for the recession, but that's certainly the implication of his academic work before becoming chair. Keep in mind that we were not at the zero bound during this period, so "conventional" models apply. And conventional New Keynesian models say that falling NGDP and prices is a good indication that money is too tight. Even Bernanke admits (in his memoir) that the Fed erred in not cutting rates after Lehman failed. I suspect that privately he now wishes the Fed had been more expansionary during the entire April to September period.

Our critics seem to suggest that market monetarists are pursuing wacky theories that are out of the mainstream. Exactly the opposite is true. MMs are upholding the mainstream consensus circa 2007. It is our critics who have forgotten what we used to teach our students from the number one monetary textbook, back in 2007 (written by Frederic Mishkin):

1. It is dangerous always to associate the easing or the tightening of monetary policy with a fall or a rise in short-term nominal interest rates. 2. Other asset prices besides those on short-term debt instruments contain important information about the stance of monetary policy because they are important elements in various monetary policy transmission mechanisms.
3. Monetary policy can be highly effective in reviving a weak economy even if short term rates are already near zero.

(Note that virtually all of the "other asset prices" implied sharply tightening money during the second half of 2008.)

Market monetarists are like those Irish monks that upheld classical learning during the long dark ages. In this case the long dark age of macroeconomics."

Why Americans don't live as long as Europeans

Three causes of death (drug poisonings, gun injuries and motor vehicle crashes) were responsible for 48% of the gap in men's life expectancy between the United States and similar countries.
 
By Carina Storrs, Special to CNN.

"Americans die younger than people in other high-income countries, and drug poisonings, gun injuries and motor vehicle crashes are largely to blame, a study finds.

To see how the United States measures up in terms of life expectancy, researchers at the Centers for Disease Control and Prevention compared its death rates in 2012 with those of a dozen other countries with similar economies, including the United Kingdom, Japan, Germany and other European countries. 

The researchers found that men and women in the United States lived 2.2 fewer years than residents in similar countries. American men and women could only look forward to a life expectancy of 76.4 and 81.2 years, respectively, compared with the 78.6 and 83.4 years of their peers abroad. 

"The idea that Americans live several years shorter than we would expect them to, given the level of development, is sort of already known, but every time I come across that number it seems staggering that we get two fewer years of life just for living here," said Andrew Fenelon, a senior service fellow at the CDC's National Center for Health Statistics and senior author of the study, which was published on Tuesday in the Journal of the American Medical Association.

The current study didn't look at which U.S. age groups were at the greatest disadvantage in terms of life expectancy, "but from my experience the largest gaps are between 25 and 65, so this prime middle-age adulthood," Fenelon said. However, other age groups in the United States, including infants, have also been known to face higher death rates, he added.

Fenelon and his colleagues took their investigation one step further and asked what is killing Americans. They focused on injuries, which are the leading cause of death for Americans between 1 and 44 years of age. Among injuries, those that are responsible for the greatest number of deaths are drug poisonings, gun injuries and motor vehicle crashes. 

They found that these three causes of death were responsible for 48% of the gap in men's life expectancy between the United States and similar countries, and took about a year off their lives in the United States. For women, they accounted for 19% of the discrepancy, costing them about half a year of life."

Hillary and Bernie both complain about excessive CEO pay, but the average CEO makes less than Hillary’s speaking fee

From Mark Perry.

"In the campaign ad above for Hillary Clinton, the narrator tells us that “On average, it takes three hundred Americans working for a solid year to make as much money as one top CEO. It’s called the wage gap.” In a Tweet last month, Bernie Sanders lamented that “CEOs make 300 times what their workers make. That is simply immoral and must be dealt with.”



How accurate are those claims that CEOs in the US make 300 times more than an average full-time American worker? Even if true, so what, is that a problem to be “dealt with”? I’ve blogged about this before on CD, see posts here, here, here and here. Here are a few additional thoughts and observations:

1. If we want an accurate “apples-to-apples” comparison, then shouldn’t we really compare the average CEO in the US to the average American worker? In 2014, there were 21,550 Chief Executives working full-time “managing a company or enterprise” and those CEOs earned an average annual salary of $216,100 according to the BLS. That’s about the same annual salary of $201,030 for the average orthodontist.

The average private full-time American worker in 2014 earned $48,920 (based on an average hourly wage of $24.46). That would give us an “Average CEO-to-Average-Worker Pay“ ratio of only 4.4-to-1 in 2014. That ratio has been been stable over the last 8 years at an average of 4.4-to-1 between 2007 and 2014 (see chart above).

To re-state Hillary Clinton’s claim above: “On average, it takes only 4.4 average Americans working for a solid year to make as much money as one average CEO. It’s called the wage gap.”

2. But Hillary and Sanders, along with the AFL-CIO, like to compare the total compensation of a very small sample of only about 350-475 of the highest-paid CEOs in the US to the average annual pay for about 100 million hourly workers employed at private companies (small, medium and large companies), and some of those workers are part-time. Note that Hillary qualifies her claim of a 300-to-1 CEO-to-worker pay ratio by referring to “top CEOs.” It’s hard to know the exact number for sure, but many of those 100 million hourly workers don’t even work for one of the 350-475 companies headed by a “top CEO.” For example, think of an American working at a small hardware store in Kansas, a family-run restaurant in Montana or a small family-owned grocery store in Kentucky. What sense does it make to compare Apple CEO Tim Cook’s $10m salary to the annual pay of workers who work for those small companies?

Of course, when the average person hears from Hillary or Sanders that there’s a 300-to-1 “wage gap,” and thinks about 300 Americans working all year to equal the salary of one top CEO, many of them are understandably upset. So upset that they can easily be persuaded that something must be done, by Hillary and Bernie of course, to address the “problem” of “excessive CEO pay,” using the heavy hand of government force if they’re elected president.

But when you have a total workforce of 150 million Americans, and you look at 300-400 of the highest paid executives in the US at the head of large, multi-national corporations, and compare their average compensation to the annual income of the “average hourly worker,” including many at small and medium sized firms, why wouldn’t we expect a large “wage gap”? Just like you’d expect to find a pretty big “wage gap” if you compared the average annual income of America’s 100-200 highest paid athletes, or the average salary of the country’s 100-200 highest paid entertainers, musicians or celebrities to the $48,920 annual income of the average hourly worker. And yet we rarely hear complaints about “excessive athlete, musician, or celebrity pay.”

3. Then there’s the inevitable lamenting about how the “CEO-to-worker pay ratio” has increased so much over time. It was about 20-to-1 in 1965, and has grown over time to the current 300-to-1 ratio that Hillary and Bernie complain about. But why wouldn’t we expect the ratio to increase over time? The size of the US workforce has doubled since the 1960s from about 75 million to 150 million workers, so the top 350-500 CEOs have become a smaller and smaller minority of all workers as total payrolls keep increasing. And adjusted for inflation, the S&P500 Index has increased three-fold since the 1960s, meaning that the CEOs of today’s S&P 500 companies are managing firms that are many times larger than S&P500 firms in the past and therefore deserve greater compensation relative to the average worker. For example, the value provided by an average hourly worker at Target or McDonald’s hasn’t changed much in the last 25 years. But the CEOs of Target and McDonald’s today are managing retail and fast food giants that are many times larger than the Target and McDonald’s in the early 1990s.

4. To put the size of the largest of today’s S&P500 companies into perspective, I posted last week on CD about how the market value of Apple’s stock at $521 billion is greater than entire stock market of Brazil ($490 billion). Further, the combined market cap of Apple, Google, Microsoft, ExxonMobil and GE exceeds $2 trillion and those five companies as a separate country would be the world’s 6th largest stock market. It’s not surprising that the CEOs of S&P 500 companies whose value is comparable to the market caps of the entire stock markets of other countries are highly compensated.
Bottom Line: It might be a little disingenuous and hypocritical for Hillary Clinton to complain about excessive CEO pay when her minimum speaking fee, reportedly $225,000 for a one-hour talk, is more than the $216,000 average annual CEO salary in 2014. We could say how unfair it is that the average CEO in America has to work a full year, 50 weeks full-time, to earn the same income that Mrs. Clinton earns in about 50 minutes giving a speech! How unfair! How immoral! Something must be done!

And if Bernie Sanders compares the pay for an average CEO to the average worker — i.e. compares “apples to apples” — and understands that the Average CEO-to-Average-Worker Pay ratio was only 4.4-to-1 in 2014, I’m not sure how he can call that an “immoral” outcome that must be “dealt with.” If Sanders wants to deal with some excessive pay that’s “immoral” maybe he should start with Mrs. Clinton’s excessive speaking fees before dealing with CEO pay. Or he might deal with the “immorality” that there are currently more than 60 NBA players who will earn $12 million or more this season, which is more than the average CEO of an S&P500 company earns!

The claim of a 300-to-1 ratio for CEO-to-worker pay made by Hillary, Bernie and the AFL-CIO gets my “Biggest Blindly Accepted Statistical Legerdemain Award.” Well no it’s actually a tie with the gender wage gap myth mentioned in the Hillary ad above and the perpetual and incessantly repeated “77 cents on the dollar” statistical falsehood."

To bring attention to the 23% “gender commute time gap” I introduce the new “Equal Commute Day” on April 14

From Mark Perry.

"The OECD Family Database (available here) has some fascinating statistics on average commute times by gender, and a summary of some of those data are displayed in the two tables above (click to enlarge). I was first made aware of these OECD commute times data from a blog post by Jim Rose (“The reverse gender gap in commuting times across the OECD”) where Jim suggests that “Commuting times need to be incorporated into calculations of the gender wage gap because they represent a serious fixed cost of working that is higher for men than for women.” Good point.




The graph that Jim displays on his blog is based on data from this OECD Excel file that contains the average commute times (minutes per day) for all adult men and women, including “self-employed who work at home and working age survey-respondents who do not participate in the labor market.” The OECD goes on to say that “Obviously, estimates on average commuting times for all respondents are lower than when such estimates are based on responses by workers only.”

The top table above displays average commute times for 17 OECD countries from this OECD source (see Table LMF2.6.A) that considers only “paid workers.” Some observations:

1. For all 17 OECD countries in the top table, men spend more time on average commuting to and from work each day, and the “gender commute time gap” ranges from as little as one extra minute of commuting time each day in Norway to as high as 18 minutes each day in the U.S. Interestingly, the difference in average commute times in the US by gender – 61 minutes for women vs. 79 minutes for men – represents a 23% “gender commute time gap” in favor of women that is exactly equal to the 23% “gender pay gap” that we hear about from President Obama:

Today, the average full-time working woman earns just 77 cents for every dollar a man earns…in 2014, that’s an embarrassment. It is wrong.

Let me re-phrase Obama’s statement to highlight the “gender commute time gap”:

Today, the average full-time working woman commutes only 77 minutes for every 100 minutes a man commutes to work…in 2014, that’s an embarrassment. It is wrong.

2. Following my introduction in 2010 of the “Equal Occupational Fatality Day” to highlight the “gender occupational fatality gap” in favor of women, let me now introduce the “Equal Commute Day” to highlight the significant “gender commute time gap” in favor of women. As displayed in the top table above, “Equal Commute Day” in the U.S. will fall on April 14* (see update below) this year and represents how far into the current year women will be able to commute to work before they have spent as much time commuting to work as men did in 2015. Interestingly, that will be a few days after the next “Equal Pay Day” on April 12. “Equal Commute Days” for other OECD countries are also displayed in the top table above.

[*Update: To calculate the “Equal Commute Day” for the US, I took the daily “gender commute gap” of 18 minutes and multiplied that by 250 days (5 work days per week X 50 weeks of work per year), to get 4,500 (18 X 250) extra commute minutes per year for men. Then I divided 4,500 extra minutes per year by the average daily commute time for women (61 minutes) to determine the number of extra days women would have to commute this year to equal the amount of time men spent commuting to work last year: 4,500 / 18 = 73.8 days.]

The bottom chart above displays some really interesting data on the average amount of time spent commuting by paid workers by gender and by the presence (and ages) of children in the household (also from Table LMF2.6.A). Note that:

3. Having children is actually associated with a slight increase in commuting times on average for men in the 16 OECD countries in the bottom table (U.S. data weren’t available for this part of the OECD study). In the UK, the average commute time increases by 2 minutes per day for men with young children (under 7 years old) and by 6 minutes per day for men with school aged children (7 to 17 years old).

4. In contrast to men with children, the average commute times in the OECD countries for women with children does change significantly – there is an average reduction of 4.6 minutes commuting time per day (1,150 minutes per year, or more than 19 hours) for women with young children (from 55.6 minutes to 51 minutes) and an average reduction of 3.9 minutes per day (975 minutes per year, or 16.25 hours) for women with school aged children (from 55.6 to 51.7 minutes).

5. In summary, the average “gender commute time gaps” for paid workers are as follows: a) 10.2% less commuting time per day for women vs. men in households without children (55.6 minutes for women vs. 61.9 minutes for men), b) 18% less commuting time per day for women vs. men in households with young children (51 vs. 62.1 minutes) and c) 17% less commuting time per day for women vs. men in households with children between 7 and 17 years of age.

Bottom Line: Behind the drive for closing the “gender pay gap” – presumably to zero – is often the mistaken assumption that men and women are, or should be, completely interchangeable in their roles in the labor market and in the family. Those assumptions defy innate biological differences and the forces of Mother Nature. It’s an empirically supported fact that men have a much greater tolerance for (and attraction to) risk than women. For example, 91% of motorcycle deaths in 2013 were male, 92% of workplace fatalities in 2014 were men, 93.4% of the current federal prison population is male, and almost 90% of climbers attempting to reach the peak of Mount Everest between 1990 and 2005 were men. That higher male tolerance for risk helps explain some of the gender differences in pay – dangerous, higher risk jobs that are more physically demanding in harsh outdoor work conditions pay more on average than safer, lower risk jobs that are less physically demanding and are in pleasant, air-conditioned indoor offices. It’s also a biological reality that men can’t get pregnant and can’t breast feed, which means that men and women will always play different family roles in childbirth and breastfeeding, and other nurturing child care responsibilities.

We learn about other gender differences for workplace preferences and for family roles from the OECD “gender commute time gaps.” In 17 OECD countries, and especially in the U.S., men are disproportionately more tolerant of longer commute times than women, who on average prefer to work closer to home at job locations with a shorter commute. To the extent that longer commute times are associated with a greater selection of higher-paying jobs, longer average commute times for men would be another factor that would explain some of the aggregate gender differences in pay favoring men. Further, while having children has no effect on men’s average commute times (and in fact increases their commute times slightly), having children does seems to affect women’s preferences for even shorter commute times compared to when they were childless. This might suggest that women want more flexibility and shorter commute times after they have children so that they can more effectively provide family and child care services. In conclusion, the OECD data suggest that women on average place a premium on shorter commute times to work, and therefore may be willing to voluntarily accept fewer job options and lower pay for being able to work close to home, especially after they have children.

Q: To close the “gender pay gap” women might have to be willing to spend a lot more time commuting to higher paying jobs and close the 23% “gender commute time gap,” which is currently 4,500 minutes annually in the U.S., or 75 hours per year and more than nine 8-hour work days per year in additional commute time for men. Would that increased commute time really be worth it to most women? Based on their current “revealed preferences” for shorter commute times than men according to the OECD survey, I think the answer is obviously “No.”"