A very nice talk by Robert Litan on the contributions of economists and economic ideas to the internet economy:
A very nice talk by Robert Litan on the contributions of economists and economic ideas to the internet economy:
One major advance in knowledge over the last twenty-five years of research in industrial organization is just how important — and how possible — market segmentation agreements and institutions may be. Is this another example?:
…this summer the service provider T-Mobile began offering its customers an alternative. Under a free feature on some plans, T-Mobile users can now stream music services like Pandora, iTunes Radio, Rhapsody, and Spotify all day long without having to worry about sapping their data caches.
T-Mobile calls it “Music Freedom,” and it’s part of a quiet but powerful global trend.
Apps and Web sites that don’t count against the users’ data plan are popping up both in the United States and abroad, often under names like Wikipedia Zero or Facebook Zero. “[W]e hope that even more people will discover the mobile Internet with Facebook,” the company blogged in announcing Facebook Zero in 2010. (The names are a riff on “zero-rated,” an economics term for products exempt from taxation.) But set against the ongoing dispute over so-called net neutrality, those apps are beginning to spark a debate about the future of an open, equal, and vibrant Internet in the United States and abroad.
And there is a trade off for consumers. In return for low-cost service, users are, in some cases, being corralled into a limited view of the Internet. Rather than wandering freely from site to site, they have gained gatekeepers who have power over what they see.
That is from Nancy Scola.
A new study which found that readers using a Kindle were “significantly” worse than paperback readers at recalling when events occurred in a mystery story is part of major new Europe-wide research looking at the impact of digitisation on the reading experience.
The study, presented in Italy at a conference last month and set to be published as a paper, gave 50 readers the same short story by Elizabeth George to read. Half read the 28-page story on a Kindle, and half in a paperback, with readers then tested on aspects of the story including objects, characters and settings.
Anne Mangen of Norway’s Stavanger University, a lead researcher on the study, thought academics might “find differences in the immersion facilitated by the device, in emotional responses” to the story. Her predictions were based on an earlier study comparing reading an upsetting short story on paper and on iPad. “In this study, we found that paper readers did report higher on measures having to do with empathy and transportation and immersion, and narrative coherence, than iPad readers,” said Mangen.
But instead, the performance was largely similar, except when it came to the timing of events in the story. “The Kindle readers performed significantly worse on the plot reconstruction measure, ie, when they were asked to place 14 events in the correct order.”
The researchers suggest that “the haptic and tactile feedback of a Kindle does not provide the same support for mental reconstruction of a story as a print pocket book does”.
That is speculative, but consistent with my own intuition, and my own tendency to (sometimes) organize information by remembering physically where it was in the book.
Daimler employees can head to the beach this summer without worrying about checking emails, sparing their partners and children the frustration of work-related matters intruding on the family vacation.
The Stuttgart-based car and truckmaker said about 100,000 German employees can now choose to have all their incoming emails automatically deleted when they are on holiday so they do not return to a bulging in-box.
For that matter they will not feel any pressure to check work email while they are away. From the FT there is more here.
You will notice this is related to some ideas from optimal queuing theory. The sender is notified that the email will be obliterated, and if it is important, he or she can send again and rejoin the queue once the recipient is back from vacation. In other words, when a long queue of email might otherwise form, potential queue creators are told they have to wait and restart later on, but at the back of the line, so to speak.
Some part of me finds this deeply wrong, but perhaps as a blogger/infovore I am not the person to ask. And there is this, which I don’t believe can be the long-term equilibrium:
It is up to Daimler employees to decide whether they wish to use the system, but Daimler assured staff it would not record who had done so.
There is a legal/regulatory angle too:
Germany’s labour ministry told managers to stop emailing or calling staff out-of-hours except in an emergency.
The Economist ran a long feature story, full of data on the world’s oldest profession. Here is one bit of interest (WWBCS?):
A degree appears to raise earnings in the sex industry just as it does in the wider labour market. A study by Scott Cunningham of Baylor University and Todd Kendall of Compass Lexecon, a consultancy, shows that among prostitutes who worked during a given week, graduates earned on average 31% more than non-graduates. More lucrative working patterns rather than higher hourly rates explained the difference. Although sex workers with degrees are less likely to work than others in any given week (suggesting that they are more likely to regard prostitution as a sideline), when they do work they see more clients and for longer. Their clients tend to be older men who seek longer sessions and intimacy, rather than a brief encounter.
Are there general lessons here for the rate of return to education? Here is another bit, when it comes to disintermediation one sex worker complains:
Moving online means prostitutes need no longer rely on the usual intermediaries—brothels and agencies; pimps and madams—to drum up business or provide a venue. Some will decide to go it alone. That means more independence, says Ana, a Spanish-American erotic masseuse who works in America and Britain. It also means more time, effort and expertise put into marketing. “You need a good website, lots of great pictures, you need to learn search-engine optimisation…it’s exhausting at times,” she says.
The full story is here.
Here is the latest, very consistent with what I argued in the book:
Automation and technology are replacing or reducing the menial tasks once associated with typical entry-level roles – those jobs that act as the first rung on a career ladder – so employers are raising the skills bar for their newest hires. Companies want those employees to arrive with sophisticated interpersonal skills, able to collaborate skillfully with colleagues and immediately interact with clients.
Weinberger examined later-life earnings of two groups of white men who completed high school and entered the workforce 20 years apart, one group in 1972 and the other in 1992. As a measurement of social skills, she looked at the men’s participation in high school sports, especially leadership roles on schools teams.
By examining wages seven years after high school graduation – in 1979 and 1999, respectively – and then looking at more recent Census and Department of Labor data to understand current labor-market outcomes, Weinberger found that later grads with impressive social skills as well as cognitive prowess experienced a seven percentage-point wage premium over those from the earlier group.
The paperback edition of Average is Over is out soon on August 26, you can order it here.
1. The law of comparative advantage has not been repealed. Machines take away some jobs and create others, while producing more output overall.
2. That said, some particular kinds of machines increase the relative return to skilled labor. If the new jobs require working with computers, and working with computers effectively is hard, reemploying lower-skilled workers at good wages may be difficult.
3. Smart software, factor price equalization, and better measurement of value have all boosted income inequality. Returns to working for low-skilled workers have fallen or stagnated in many regions (not North Dakota). Returns for many higher skilled workers have risen, but most of them were working and working hard already.
4. Lower returns to unskilled labor mean (on average) that low-skilled laborers will work less. This effect may interact with government benefits but sometimes people decide to work less or search less hard for a job for reasons unrelated to benefits. These decisions may produce feedback which weakens pro-work norms in the broader culture.
5. The employment to population ratio will be lower than it otherwise would have been, because of “robots” but not only robots. The natural rate of unemployment will be higher too.
6. Many of the new service sectors jobs will be better suited to women rather than the most unruly men. Physical strength will matter less, conscientiousness and teamwork will matter more, and much of the burden of these adjustments will fall on lesser educated men.
7. Facebook makes it easier to get sex and keep friends without having a job.
8. There is good evidence for each of these propositions, although it may be questioned how great is their combined import. In the meantime, yes robots may lower employment, although the catchphrase “robots are destroying jobs” is misleading rather than illuminating.
The working paper (pdf) describes it in this way:
Filecoin is a distributed electronic currency similar to Bitcoin. Unlike Bitcoin’s computation-only proof-of-work, Filecoin’s proof-of-work function includes a proof-of-retrievability component, which requires nodes to prove they store a particular file. The Filecoin network forms an entirely distributed file storage system, whose nodes are incentivized to store as much of the entire network’s data as they can. The currency is awarded for storing files, and is transferred in transactions, as in Bitcoin. Files are added to the network by spending currency. This produces strong monetary incentives for individuals to join and work for the network. In the course of ordinary operation of the Filecoin network, nodes contribute useful work in the form of storage and distribution of valuable data.
The mother site is here. File under…arbitrage.
For the pointer I thank J.
The Finnish capital has announced plans to transform its existing public transport network into a comprehensive, point-to-point “mobility on demand” system by 2025 – one that, in theory, would be so good nobody would have any reason to own a car.
Helsinki aims to transcend conventional public transport by allowing people to purchase mobility in real time, straight from their smartphones. The hope is to furnish riders with an array of options so cheap, flexible and well-coordinated that it becomes competitive with private car ownership not merely on cost, but on convenience and ease of use.
Subscribers would specify an origin and a destination, and perhaps a few preferences. The app would then function as both journey planner and universal payment platform, knitting everything from driverless cars and nimble little buses to shared bikes and ferries into a single, supple mesh of mobility. Imagine the popular transit planner Citymapper fused to a cycle hire service and a taxi app such as Uber, with only one payment required, and the whole thing run as a public utility, and you begin to understand the scale of ambition here.
This is from a New York Craigslist post, from a restaurant owner who apparently viewed tapes of customers from 2004 and 2014, here is part of his account of the more recent behavior:
Customers walk in.
Customers get seated and is given menus, out of 45 customers 18 requested to be seated elsewhere.
Before even opening the menu they take their phones out, some are taking photos while others are simply doing something else on their phone (sorry we have no clue what they are doing and do not monitor customer WIFI activity).
7 out of the 45 customers had waiters come over right away, they showed them something on their phone and spent an average of 5 minutes of the waiter’s time. Given this is recent footage, we asked the waiters about this and they explained those customers had a problem connecting to the WIFI and demanded the waiters try to help them.
Finally the waiters are walking over to the table to see what the customers would like to order. The majority have not even opened the menu and ask the waiter to wait a bit.
Customer opens the menu, places their hands holding their phones on top of it and continue doing whatever on their phone.
This is for call center operators:
The results are surprising. Some are quirky: employees who are members of one or two social networks were found to stay in their job for longer than those who belonged to four or more social networks (Xerox recruitment drives at gaming conventions were subsequently cancelled). Some findings, however, were much more fundamental: prior work experience in a similar role was not found to be a predictor of success.
“It actually opens up doors for people who would never have gotten to interview based on their CV,” says Ms Morse. Some managers initially questioned why new recruits were appearing without any prior relevant experience. As time went on, attrition rates in some call centres fell by 20 per cent and managers no longer quibbled. “I don’t know why this works,” admits Ms Morse, “I just know it works.”
The rest of the Tim Smedley FT story is here, via Peter Sahui.
There is a new NBER working paper with that title, by S. Borağan Aruoba and Jesus Fernandez-Villaverde. Here is the abstract:
We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++11, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration with grid search, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and comment on the strength and weakness of each language.
Here are their results:
1. C++ and Fortran are still considerably faster than any other alternative, although one needs to be careful with the choice of compiler.
2. C++ compilers have advanced enough that, contrary to the situation in the 1990s and some folk wisdom, C++ code runs slightly faster (5-7 percent) than Fortran code.
3. Julia, with its just-in-time compiler, delivers outstanding per formance. Execution speed is only between 2.64 and 2.70 times the execution speed of the best C++ compiler.
4. Baseline Python was slow. Using the Pypy implementation, it runs around 44 times slower than in C++. Using the default CPython interpreter, the code runs between 155 and 269 times slower than in C++.
5. However, a relatively small rewriting of the code and the use of Numba (a just-in-time compiler for Python that uses decorators) dramatically improves Python ’s performance: the decorated code runs only between 1.57 and 1.62 times slower than the best C++ executable.
6.Matlab is between 9 to 11 times slower than the best C++ executable. When combined with Mex files, though, the difference is only 1.24 to 1.64 times.
7. R runs between 500 to 700 times slower than C++ . If the code is compiled, the code is between 240 to 340 times slower.
8. Mathematica can deliver excellent speed, about four times slower than C++, but only after a considerable rewriting of the code to take advantage of the peculiarities of the language. The baseline version our algorithm in Mathematica is much slower, even after taking advantage of Mathematica compilation.
There are ungated copies and some discussion here.
It is excellent throughout, here is one good sentence:
The funny thing about Piketty is that he has a lot more faith in returns on invested capital than any professional investor I’ve ever met.
Here is another:
The result of all that is the effective death of the IPO. The number of public companies in the US has dropped dramatically. And then correspondingly, growth companies go public much later. Microsoft went out at under $1 billion, Facebook went out at $80 billion. Gains from the growth accrue to the private investor, not the public investor…
Most American retirement savings is invested in the public stock market. Most Americans can’t invest in private companies and most Americans can’t invest in venture capital and private equity funds. They’re actually prohibited from doing so by the SEC. If you both prohibit them from investing in private growth and wire the market so they can’t get into public growth, then you can’t be invested in growth. That raises the societal question of how are we going to pay for retirements. That’s the question that needs to be asked that nobody asks because it’s too scary.
The full interview is here.
This trend is accelerating:
When Jim Sullivan began working as a waiter at a Dallas restaurant a few years ago, he was being watched — not by the prying eyes of a human boss, but by intelligent software.
The digital sentinel, he was told, tracked every waiter, every ticket, and every dish and drink, looking for patterns that might suggest employee theft. But that torrent of detailed information, parsed another way, cast a computer-generated spotlight on the most productive workers.
Mr. Sullivan’s data shone brightly. And when his employer opened a fourth restaurant in the Dallas area in 2012, Mr. Sullivan was named the manager — a winner in the increasingly quantified world of work.
Here is some of what goes on behind the scenes:
Ben Waber is chief executive of Sociometric Solutions, a start-up that grew out of his doctoral research at M.I.T.’s Human Dynamics Laboratory, which conducts research in the new technologies. Sociometric Solutions advises companies using sensor-rich ID badges worn by employees. These sociometric badges, equipped with two microphones, a location sensor and an accelerometer, monitor the communications behavior of individuals — tone of voice, posture and body language, as well as who spoke to whom for how long.
Sociometric Solutions is already working with 20 companies in the banking, technology, pharmaceutical and health care industries, involving thousands of employees. The workers must opt in to have their data collected. Mr. Waber’s company signs a contract with each one guaranteeing that no individual data is given to the employer (only aggregate statistics) and that no conversations are recorded.
The article by Steve Lohr is here.