Slashdot Mirror

An anonymous reader quotes NPR: In recent months, a slew of studies has debunked predictions that we're witnessing the dawn of a new "gig economy." The U.S. Bureau of Labor Statistics (BLS) found that there was actually a decline in the categories of jobs associated with the gig economy between 2005 and 2017. Larry Katz and the late Alan Krueger then revised their influential study that had originally found gig work was exploding. Instead, they found it had only grown modestly. Other economists ended up finding the same -- and now writers are declaring the gig economy is "a big nothingburger."

Arun Sundararajan, a professor at the NYU Stern School of Business and the author of The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism, remains a true believer in the gig revolution.... When asked about the onslaught of data contradicting his thesis, Sundararajan said the Bureau of Labor Statistics continues "to underestimate the size of the gig economy and in particular of the platform-based gig economy." The best BLS estimate of the number of gig workers employed through digital platforms -- whether full-time, part-time or occasionally -- is one percent of the total U.S. workforce, or about 1.6 million workers, as of mid-2017. Sundararajan argues that the survey questions the BLS used to gather this data were clunky and don't quite capture what's going on.... He believes work done through gig platforms can be more efficient than work done in a traditional company -- and that will spell the company's doom...

The dawn of a new gig economy has seemed plausible because the Internet has been dramatically reducing transaction costs. Search engines have made it incredibly cheap to find goods and services, compare prices, and get bargains. Social media and peer reviews have made it easier to determine if people are trustworthy. E-commerce has made it easier process payments. You can click a button on a mobile phone and instantaneously have GPS guide drivers right to you. But as big as these efficiency gains have been, a new economy based on crowds of people doing gigs through digital platforms -- as exciting or scary as that might sound -- still doesn't compare to one based on the efficiencies and stability of the good old-fashioned company.

An anonymous reader quotes NPR: In recent months, a slew of studies has debunked predictions that we're witnessing the dawn of a new "gig economy." The U.S. Bureau of Labor Statistics (BLS) found that there was actually a decline in the categories of jobs associated with the gig economy between 2005 and 2017. Larry Katz and the late Alan Krueger then revised their influential study that had originally found gig work was exploding. Instead, they found it had only grown modestly. Other economists ended up finding the same -- and now writers are declaring the gig economy is "a big nothingburger."

Arun Sundararajan, a professor at the NYU Stern School of Business and the author of The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism, remains a true believer in the gig revolution.... When asked about the onslaught of data contradicting his thesis, Sundararajan said the Bureau of Labor Statistics continues "to underestimate the size of the gig economy and in particular of the platform-based gig economy." The best BLS estimate of the number of gig workers employed through digital platforms -- whether full-time, part-time or occasionally -- is one percent of the total U.S. workforce, or about 1.6 million workers, as of mid-2017. Sundararajan argues that the survey questions the BLS used to gather this data were clunky and don't quite capture what's going on.... He believes work done through gig platforms can be more efficient than work done in a traditional company -- and that will spell the company's doom...

The dawn of a new gig economy has seemed plausible because the Internet has been dramatically reducing transaction costs. Search engines have made it incredibly cheap to find goods and services, compare prices, and get bargains. Social media and peer reviews have made it easier to determine if people are trustworthy. E-commerce has made it easier process payments. You can click a button on a mobile phone and instantaneously have GPS guide drivers right to you. But as big as these efficiency gains have been, a new economy based on crowds of people doing gigs through digital platforms -- as exciting or scary as that might sound -- still doesn't compare to one based on the efficiencies and stability of the good old-fashioned company.

An anonymous reader quotes a report from Bloomberg: Thirty years ago in December, the modern exchange of scholars between the U.S. and China began. Since then, Chinese academics have become the most prolific global contributors to publications in physical sciences, engineering and math. Recent attempts by the U.S. to curtail academic collaboration are unlikely to change this trend. Qingnan Xie of Nanjing University of Science & Technology and Richard Freeman of Harvard University have studied China's contribution to global scientific output. They document a rapid expansion between 2000 and 2016, as the Chinese share of global publications in physical sciences, engineering and math quadrupled. By 2016, the Chinese share exceeded that of the U.S. Furthermore, the authors argue that these metrics -- which are based on the addresses of the authors -- understate China's impact. The data don't count papers written by Chinese researchers located in other countries with addresses outside China and exclude most papers written in Chinese publications. The researchers adjusted for both factors and conclude that Chinese academics now account for more than one-third of global publications in these scientific fields.

An anonymous reader shares a report: In the United States, if you have an Apple iPhone or iPad, it's a strong sign that you make a lot of money. That's one of the takeaways from a new National Bureau of Economic Research working paper from University of Chicago economists Marianne Bertrand and Emir Kamenica. "Across all years in our data, no individual brand is as predictive of being high-income as owning an Apple iPhone in 2016," the researchers wrote. There are details and caveats to the research, but the economists found that owning an iPhone gave them a 69% chance to correctly infer that the owner was "high-income," which they defined as being in the top quartile of income for households of that type -- like single adult or couple with dependents, for example.

Abstract of a paper [PDF] which was originally published last month: Artificial intelligence may greatly increase the efficiency of the existing economy. But it may have an even larger impact by serving as a new general-purpose "method of invention" that can reshape the nature of the innovation process and the organization of R&D. We distinguish between automation-oriented applications such as robotics and the potential for recent developments in "deep learning" to serve as a general-purpose method of invention, finding strong evidence of a "shift" in the importance of application-oriented learning research since 2009.

We suggest that this is likely to lead to a significant substitution away from more routinized labor-intensive research towards research that takes advantage of the interplay between passively generated large datasets and enhanced prediction algorithms. At the same time, the potential commercial rewards from mastering this mode of research are likely to usher in a period of racing, driven by powerful incentives for individual companies to acquire and control critical large datasets and application-specific algorithms. We suggest that policies which encourage transparency and sharing of core datasets across both public and private actors may be critical tools for stimulating research productivity and innovation-oriented competition going forward.

Andrew Van Dam, writing for the Washington Post: Where did all the jobs go? Well, we're finally starting to find some satisfactory answers to the granddaddy of all economic questions. The share of Americans with jobs dropped 4.5 percentage points from 1999 to 2016 -- amounting to about 11.4 million fewer workers in 2016. At least half of that decline probably was due to an aging population. Explaining the remainder has been the inspiration for much of the economic research published after the Great Recession.

According to a new working paper from the National Bureau of Economics, the number of American firms listed publicly in the U.S. has dropped more than half. In 1997, more than 7,500 American firms were listed publicly in the U.S. Nearly two decades later, in 2016, the number had dropped to 3,618 firms. Quartz reports: The crux of the issue is that U.S. startups are increasingly shunning stock market boards. That could have worrying implications for America's long-term economic prospects. One big reason young companies are shying away from IPOs is that public listings don't offer much benefit to promising startups, say the paper's authors, economists Craig Doidge, Kathleen Kahle, Andrew Karolyi, and Rene Stulz. In fact, going public can hurt them. The upside of public listing is that it lets companies raise huge sums of capital, issue more shares, issue debt with relative ease, and use equity to fund acquisitions. But because of the ways the American economy has evolved, those advantages are less important than they once were.

When industry powered U.S. growth, companies grew by spending on capital investments like factories and machinery. Back in 1975, firms once spent six times more on capital investments than they did on research and development. But as the U.S. shifted toward a services and knowledge-based economy, intangible investments became increasingly important. In 2002, R&D expenditures for the average firm surpassed capital expenditures for the first time. It's stayed that way since; nowadays, average R&D spending is roughly twice that of capital expenditures. The problem is, two features of public listings -- disclosure and accounting standards -- make things tough on companies with more intangible assets. U.S. securities law requires companies to disclose their activities in detail. But startups are wary of sharing information that might benefit their competitors.

"Robot-assisted surgery costs more time and money than traditional methods, but isn't more effective, for certain types of operations," reports the Register, in an article shared by schwit1: In a study of almost 24,000 laparoscopic surgeries just published in The Journal of American Medicine, researchers from Stanford University School of Medicine analyzed data from 416 hospitals around the U.S. from 2003 to 2015. Robotic assistance provides 3D-visualization, a broader range of motion for instruments, and better ergonomics for physicians, according to the study. While it has advantages in scenarios where a high-degree of precision is required or where improved outcomes have been demonstrated (like radical prostatectomy), it appears to be a waste of resources for the two operations examined... But the patient outcomes were more or less the same.

A thematically-related economic study presented by the National Bureau for Economic Research on Monday suggests that while AI and machine learning have received substantial investment over the past five years and have been widely touted as a transformative technologies, "there is little sign that they have yet affected aggregate productivity statistics... The simplest possibility is that the optimism about the potential technologies is misplaced and unfounded," muse Erik Brynjolfsson and Daniel Rock (MIT), Chad Syverson (University of Chicago) in the paper.
But instead the paper's author suggest that fully realizing the benefits of AI "will require effort and entrepreneurship to develop the needed complements, and adaptability at the individual, organizational, and societal levels to undertake the associated restructuring."

A new paper released on Monday via the National Bureau of Economic Research claims that retaining search log data doesn't do much for search quality. "Data retention has implications in the debate over Europe's right to be forgotten, the authors suggest, because retained data undermines that right," reports The Register. "It's also relevant to U.S. policy discussions about privacy regulations." From the report: To determine whether retention policies affected the accuracy of search results, Chiou and Tucker used data from metrics biz Hitwise to assess web traffic being driven by search sites. They looked at Microsoft Bing and Yahoo! Search during a period when Bing changed its search data retention period from 18 months to 6 months and when Yahoo! changed its retention period from 13 months to 3 months, as well as when Yahoo! had second thoughts and shifted to an 18-month retention period. According to Chiou and Tucker, data retention periods didn't affect the flow of traffic from search engines to downstream websites. "Our findings suggest that long periods of data storage do not confer advantages in search quality, which is an often-cited benefit of data retention by companies," their paper states. Chiou and Tucker observe that the supposed cost of privacy laws to consumers and to companies may be lower than perceived. They also contend that their findings weaken the claim that data retention affects search market dominance, which could make data retention less relevant in antitrust discussions of Google.

Innovation, fetishized by Silicon Valley companies and celebrated by business boosters, no longer provides the economic jolt it once did. From a report: In order to maintain Moore's Law -- by which transistor density doubles every two years or so -- it now takes 18 times as many scientists as it did in the 1970s. That means each researcher's output today is 18 times less effective in terms of generating economic value than it was several decades ago. On an annual basis, research productivity is declining at a rate of about 6.8 percent per year in the semiconductor industry. In other words, we're running out of ideas. That's the conclusion of economic researchers from Stanford University and the Massachusetts Institute of Technology. In a paper published this week through the National Bureau of Economic Research, "Are Ideas Getting Harder to Find?", economics professors Nicholas Bloom, Charles Jones, and John Van Reenen, and PhD candidate Michael Webb, defy Betteridge's Law of Headlines by concluding that an idea drought has indeed taken hold. "Across a broad range of case studies ... we find that ideas -- and in particular the exponential growth they imply -- are getting harder and harder to find," the authors declare in their paper.

An anonymous reader shares a report via email: As of the start of the year, 19 U.S. states had raised minimum wages, dramatizing a long simmering debate: Do minimum wages kill jobs, and make the working class worse off in the end? Or do they simply make them a little richer, with little or no loss to overall employment? In a new paper, economists Grace Lordan of the London School of Economics and David Neumark of UC Irvine parse 35 years of census data and come down on the worse-off side: For lower-skill jobs like bookkeepers and assembly-line workers, they say, higher minimum wages encourage employers to automate -- according to their calculations, a $1 increase can cost tens of thousands of jobs nationally.

Who is winning the race for jobs between robots and humans? Last year, two leading economists described a future in which humans come out ahead. But now they've declared a different winner: the robots. From a report on the New York Times: The industry most affected by automation is manufacturing. For every robot per thousand workers, up to six workers lost their jobs and wages fell by as much as three-fourths of a percent, according to a new paper by the economists, Daron Acemoglu of M.I.T. and Pascual Restrepo of Boston University. It appears to be the first study to quantify large, direct, negative effects of robots. The paper is all the more significant because the researchers, whose work is highly regarded in their field, had been more sanguine about the effect of technology on jobs. In a paper last year, they said it was likely that increased automation would create new, better jobs, so employment and wages would eventually return to their previous levels. Just as cranes replaced dockworkers but created related jobs for engineers and financiers, the theory goes, new technology has created new jobs for software developers and data analysts. From a report on The Verge, which looks at another finding in the study: They found that each new robot added to the workforce meant the loss of between 3 and 5.6 jobs in the local commuting area. Meanwhile, for each new robot added per 1,000 workers, wages in the surrounding area would fall between 0.25 and 0.5 percent.

An anonymous reader quotes a report from MarketWatch: There would have been up to 11% more computer science jobs at wages up to 5% higher were it not for the immigration program that brings in foreign high-skilled employees, a new study finds. The paper -- by John Bound and Nicolas Morales of the University of Michigan and Gaurav Khanna of the University of California, San Diego -- was conducted by studying the economy between 1994 and 2001, during the internet boom. It was also a period where the recruitment of so-called H-1B labor was at or close to the cap and largely before the onset of the vibrant IT sector in India. In 2001, the number of U.S. computer scientists was between 6.1%-10.8% lower and wages were between 2.6% and 5.1% lower. Of course, there also were beneficiaries -- namely consumers and employers. Immigration lowered prices by between 1.9% and 2.4%, and profits increased as did the total number of IT firms.

Registered Coward v2 writes: Vault, in a blog post, discusses whether colleges should base tuition on the actual cost of providing the education rather than on a one-price-for-all-credits basis. Their argument is based on a Quartz article that shows engineering and science degrees cost schools a lot more than liberal arts degrees for a variety of reasons, including higher professor salaries and equipment/infrastructure costs. As a result, those majors are subsidized by the cheaper ones even though they also have the highest earnings in aggregate. The new paper on the topic estimates that it typically costs the universities more than $62,000 to educate an engineer (including professor salaries, facilities fees, and administrative costs), while an English or business major costs nearly half that. Quartz has a chart embedded in its report that shows the cost of education by major at the University of Florida. There's also another chart that shows the earnings of past graduates, up to age 45, minus the cost of each degree. According to the paper, even though it costs more for an engineering degree, it pays off.

An anonymous reader writes: A few articles came out Thursday talking about the recently released report from the National Bureau of Economic Research on the environmental benefits of electric cars. The general consensus is kind of obvious -- that it depends on the ratio of coal vs. clean electrical generation that is used to charge your car. What is interesting is the extent to which it makes a difference, and that when viewed on a regional basis, there are cases where the EV doesn't do so well. And when it comes to policy decisions, it seems the central focus needs to be on the replacement of large-scale coal generation, and the rest will fall in to place. Here is one cover story from Ars Technica. Google others for varying perspectives.

theodp (442580) writes "Citing a new study published by the National Bureau of Economic Research (free to Federal employees), the NY Times reports on how elementary school teachers' pro-boy biases can discourage girls from math and science. "The pipeline for women to enter math and science occupations narrows at many points between kindergarten and a career choice," writes Claire Cain Miller, "but elementary school seems to be a critical juncture. Reversing bias among teachers could increase the number of women who enter fields like computer science and engineering, which are some of the fastest growing and highest paying. 'It goes a long way to showing it's not the students or the home, but the classroom teacher's behavior that explains part of the differences over time between boys and girls,' said Victor Lavy, an economist at University of Warwick in England and a co-author of the paper." Although the study took place in Israel, Lavy said that similar research had been conducted in several European countries and that he expected the results were applicable in the United States."

Bennett Haselton writes: A editorial with 24,000 Facebook shares highlights the differences in public reaction to two nearly identical breastfeeding photos, one showing a black woman and one showing a white woman, each breastfeeding an infant. The editorial decries the outrage provoked by the black woman's photo compared to the mild reaction elicited by the white woman's photo, and attributes the difference to racism. I tried an experiment using Amazon's Mechanical Turk to test that theory. Read on to see the kind of results Bennett found.

You can see the side-by-side pictures in the November 10 editorial by Ruby Hamad. My first thought, upon seeing the pictures, was that this is not a controlled experiment -- the woman on the left is breastfeeding in public, while the woman on the right is breastfeeding against a blank wall inside a presumably private room. While I think breastfeeding in public should be completely normalized, it's not the same thing as breastfeeding in private, and so that might have accounted for the difference in reactions, if there was any.

My second thought was that the data on people's reactions was not collected in a systematic way. According to the editorial, the black photo of the black mother, Karlesha Thurman, was posted on the Facebook page Black Women Do Breastfeed, and "[w]hile Karlesha received many supportive comments, the backlash was so severe, she eventually deleted the photo." The photo of the Australian woman, Jacci Sharkey, was posted by the University of the Sunshine Coast on their Facebook page, where it received 275,000 Facebook "likes", but also, according to the editorial, "more than a few detractors, proving that breastfeeding in public is (still!) a contentious issue for women of all races." There's no apples-to-apples comparison gauging people's reactions to the two photos under similar conditions.

But just because the methodology was imprecise, doesn't mean that the underlying phenomenon might not be real. Maybe Internet users really do have different gut reactions to pictures of black women and white women breastfeeding.

One quick way to get a rough answer is Amazon's Mechanical Turk service, where you can pay legions of workers some small amount of money per person to complete some menial task that can't be automated by a computer. I've used it dozens of times for surveys (such as gauging whether people would strongly prefer slideout keyboard phones) and for amateur psychological experiments (including one experiment which suggested that people who answered a math problem correctly were more likely to disagree with an attorney general's dubious legal argument). So I created a poll on Mechanical Turk, limited to U.S. users and with a payout of 25 cents for each person who answered. The poll asked:

Our academic department has asked everyone to submit a "fun" photo of themselves, so that our photos can be displayed together on the department home page. One of our employees submitted a photo that has caused some internal debate about whether the photo is inappropriate. I wanted to do a poll to get the opinion of a random sample of Internet users of different backgrounds.

Do you think this is an appropriate picture to be used in a photo collection on our academic department home page?

Since the original photos had been published in different contexts anyway, I tried to find a middle ground for the wording of the survey question, to emphasize that the photos were going to be published in a "fun" setting, but still integrated into the women's professional environments. The survey-takers were then (randomly) shown either the black woman's photo or the white woman's photo, and answered "Yes, the image is fine" or "No, the image is inappropriate". Then respondents were asked to fill in their age, gender, ethnicity, and education level.

(One thing that I've found with all of my previous surveys on Mechanical Turk, is that there is strong evidence that survey-takers are not answering randomly. Strong correlations often occur where you would expect them to -- for example, in a survey about what are the greatest causes of global strife, the same people tend to select "Energy shortages" and "Environmental damage" above other options, whereas another subgroup will tend to select both "Atheism" and "Decline of traditional values". And any survey where I've added a textbox for users to enter "more thoughts", most users enter something reasonably thoughtful which corresponds to the multiple-choice answers they've selected. Formal research by the psychologist Samuel Gosling has similarly found that Internet surveys can be useful for psychological research and are not plagued with bot-responders or random answers. So I'm working under that assumption.)

The results: Out of 47 respondents who saw the black girl's picture, 36 said the image was inappropriate (77%). Out of 54 respondents who saw the white girl's picture, 38 said the image was inappropriate (70%). For such a small sample, that's not enough to definitively say whether the small difference is due to random chance, or due to small differences in opinion in the population being surveyed. What it does show, even with such a small sample, is that in the underlying population there's almost certainly no huge gap between people's opinions of black women vs. white women breastfeeding in photos.

In both surveys, both male and female respondents voted the photos "inappropriate" with about the same frequency. For the black woman's photo, 22 out of 26 men (86%) and 14 out of 21 women (67%) voted the photo inappropriate; for the white woman's photo, 19 out of 30 men (63%) and 19 out of 24 women (79%) voted it inappropriate. There also didn't appear to be any correlation between the age of the respondents and their responses. (You can view the breakdown of answers in terms of respondent demographics here for the black woman's picture and here for the white woman's picture; the crummy layout is because I just copied-and-pasted the output from my own custom-written survey-taking tool, where I usually just view the results for myself.) As for the gap between black and white survey-takers, in the case of the black woman's photo, 24 out of 34 white survey-takers (70%) and 5 out of 6 black survey-takers (83%) voted it inappropriate, while for the white woman's photo, 25 out of 36 white survey-takers (69%) and 4 out of 4 (100%) of black survey-takers voted it inappropriate -- but those discrepancies probably don't mean much, since the population of self-identified black respondents was too small in both cases to draw any conclusions.

Even with small samples, though, I would argue that this is a better way to answer the question of latent racism than to draw fuzzy conclusions based on the trolling comments posted on a Facebook photo. My guess is that even if there was an underlying difference in the frequency of negative comments posted to the two photos, part of it could have been due to the photo being posted in a Facebook group titled "Black Women Do Breastfeed", a group name that is practically begging for trolls to wait for a chance to try and provoke an outraged response. The white woman's photo, on the other hand, was posted on the University of the Sunshine Coast Facebook page, which is not the kind of place that maladjusted nitwits hang out trying to start a flame war. And for the trolls who did post on the white woman's photo, their natural inclination would be to make some immature comment about b00bs; whereas for the trolls posting on the black woman's photo, the easiest cheap shot would be to make it about race. But that doesn't mean that there is actually a racially motivated difference in people's reactions to the photos.

Besides, if you want to use Facebook to raise awareness of racism, there are properly controlled scientific experiments that have demonstrated the extent of prejudice, such as the infamous 2003 resume callback experiment which showed that resumes with white-sounding names on them received about 50% more callbacks than resumes with black-sounding names. A viral story with 24,000 Facebook shares, about two isolated incidents under different circumstances, is not necessarily evidence of racism. It might be. But you have to do some kind of controlled experiment to check first.

First time accepted submitter SillyBoy123 writes What is the impact of file sharing releases on the movie industry? Ask the studios and they will say billions. An economist named Koleman Strumph is presenting a paper at the National Bureau of Economics this week that tries to estimate the crowd out from these releases. His conclusion: "I find that file sharing has only a modest impact on box office revenue." In fact, Strumph finds that file sharing before the official release of a movie can actually be beneficial to revenues: "One consistent result is that file sharing arrivals shortly before the theatrical opening have a modest positive effect on box office revenue. One explanation is that such releases create greater awareness of the film. This is also the period of heaviest advertising. In conjunction with the main estimates, this suggests that free and potentially degraded goods such as the lower quality movies available on file sharing networks can have some beneficial effects on intellectual property."

cold fjord writes "I wish it was always this easy. Business Insider reports, 'Iodized salt is so ubiquitous that we barely notice it. Few people know why it even exists. Iodine deficiency remains the world's leading cause of preventable mental retardation. According to a new study (abstract), its introduction in America in 1924 had an effect so profound that it raised the country's IQ. A new NBER working paper from James Feyrer, Dimitra Politi, and David N. Weil finds that the population in iodine-deficient areas saw IQs rise by a full standard deviation, which is 15 points, after iodized salt was introduced.... The mental impacts were unknown, the program was started to fight goiter, so these effects were an extremely fortunate, unintended side effect.'"

First time accepted submitter HonorPoncaCityDotCom writes "Khadeeja Safdar reports in the WSJ that researchers who surveyed 655 incoming college students found that while math and science majors drew the most interest initially, not many students finished with degrees in those subjects. Students who dropped out didn't do so because they discovered an unexpected amount of the work and because they were dissatisfied with their grades. "Students knew science was hard to begin with, but for a lot of them it turned out to be much worse than what they expected," says Todd R. Stinebrickner, one of the paper's authors. "What they didn't expect is that even if they work hard, they still won't do well." The authors add that the substantial overoptimism about completing a degree in science can be attributed largely to students beginning school with misperceptions about their ability to perform well academically in science. ""If more science graduates are desired, the findings suggest the importance of policies at younger ages that lead students to enter college better prepared (PDF) to study science.""

New submitter Stirling Newberry writes "You may have heard of The Great Moderation (PDF), which argues that business cycles have become less volatile over time, and the Green Revolution, a set of initiatives that led to increased global food production. These, it has been argued, have led to a marked decrease in war across the world. But not so fast, says a study in Science. It may well be that periods of war, past and present, can be linked to changes in climate: 'The most direct way in which extreme climate shifts influence human society is through agriculture, Zhang says; a falling supply of crops will drive up the price of gold and cause inflation. Similarly, epidemics can be exacerbated by famine. And when people are miserable, they are likely to become angry with their governments and each other, resulting in war. But golden ages rise out of these dark periods, the team argues. For instance, a 100-year cold period beginning in 1560 caused shortened crop growing seasons. The researchers found a causal linkage with a decline in average human height by nearly an inch during this period, and the century was rife with disease and conflict. But the world began to warm in 1650; when Charles II was crowned king of England in 1660, the coronation sparked the Enlightenment era in Europe.'"

instantgames writes "According to a working paper of the National Bureau of Economic Research, rapid development of a science and technology base by populous Asian countries soon may threaten the economic position of the United States. Not only is the U.S. losing ground in high technology exports, but its very capacity to develop new technologies is declining rapidly with respect to the rest of the world. According to Richard Freeman, the paper's author, the sheer population of Asian countries may allow them to train more scientists and engineers than the U.S. while devoting a smaller share of their economy to science and technology." From the article: "The phenomenal growth of China's industrial base has been widely publicized, but Freeman focuses on what is perhaps the more important long-term indicator of a nation's prosperity - its re-investment in science and technology education. "

instantgames writes "According to a working paper of the National Bureau of Economic Research, rapid development of a science and technology base by populous Asian countries soon may threaten the economic position of the United States. Not only is the U.S. losing ground in high technology exports, but its very capacity to develop new technologies is declining rapidly with respect to the rest of the world. According to Richard Freeman, the paper's author, the sheer population of Asian countries may allow them to train more scientists and engineers than the U.S. while devoting a smaller share of their economy to science and technology." From the article: "The phenomenal growth of China's industrial base has been widely publicized, but Freeman focuses on what is perhaps the more important long-term indicator of a nation's prosperity - its re-investment in science and technology education. "

GrokSoup writes "A new study shows that great achievements in science are produced by older innovators today than they were a century ago. Using data on Nobel Prize winners and great inventors, the author shows that the age at which noted innovations are produced has increased by approximately 6 years over the 20th Century. This runs contrary to accepted wisdom in science, which says that most scientists peak in their 20s. It is also welcome news to those of us who have not yet, ahem, done our Nobel-winning work."

l2718 writes "Two economists have just posted a paper online, showing a small correlation between counties' use of paperless electronic voting systems and voting results in the recent presidential election (after controlling for other factors). They found no evidence for systematic fraud by testing several potential indicators. Rather, the voting method seems to affect the relative turnout of different voter demographies. Thanks to Election Law Blog for the pointer."

l2718 writes "Two economists have just posted a paper online, showing a small correlation between counties' use of paperless electronic voting systems and voting results in the recent presidential election (after controlling for other factors). They found no evidence for systematic fraud by testing several potential indicators. Rather, the voting method seems to affect the relative turnout of different voter demographies. Thanks to Election Law Blog for the pointer."

Jason Kau writes " is a working paper on the economics of open source software from the Nation Bureau of Economic Research entitled "The Simple Economics of Open Source". Focuses primarily on Apache, Perl, and Sendmail but mentions Linux, Debian, VA Linux, etc. It's a 40 page PDF document. Some background in Economics would probably be helpful."