O blog TechCrunch traz hoje uma matéria sobre este luta (ver http://www.techcrunch.com/2008/07/18/fighting-for-its-life-yahoo-uses-its-homepage-to-battle-carl-icahn/)

Conclúo dizendo que também votei na petição (voto 63349)! 

Pela Liberdade (ponto.) (full stop)

Link da petição: http://www.petitiononline.com/veto2008/

==========

"Este blog [e centenas de outros] já comentaram o atentado que o congresso está prestes a cometer contra a internet brasileira [veja nosso texto sobre o assunto aqui]. se a atual da proposta de legislação for aprovada, o brasil vai entrar no seleto clube dos países que vigiam, de muito perto, tudo o que se faz na rede. ninguém está defendendo o caos total na internet, mas não se pode usar o argumento que há crimes, na rede, para tornar todos os seus usuários suspeitos e vigiados.

é hora de agir. mais de 62 mil pessoas já assinaram uma petição que estará sendo encaminhada à câmara de deputados, defendendo as liberdades e a privacidade dos usuários da internet no brasil. parte do texto da petição diz que… defendemos a liberdade, a inteligência e a troca livre e responsável. Não defendemos o plágio, a cópia indevida ou o roubo de obras. Defendemos a necessidade de garantir a liberdade de troca, o crescimento da criatividade e a expansão do conhecimento no Brasil. Experiências com Software Livres e Creative Commons já demonstraram que isso é possível. Devemos estimular a colaboração e enriquecimento cultural, não o plágio, o roubo e a cópia improdutiva e estagnante. E a Internet é um importante instrumento nesse sentido. Mas esse projeto coloca tudo no mesmo saco. Uso criativo, com respeito ao outro, passa, na Internet, a ser considerado crime. Projetos como esses prestam um desserviço à sociedade e à cultura brasileiras, travam o desenvolvimento humano e colocam o país definitivamente para debaixo do tapete da história da sociedade da informação no século XXI.

eu já assinei. assine você também. se este projeto for aprovado -e se a lei pegar- nós vamos sentir muita falta da liberdade que temos hoje. melhor não arriscar."

Pois é: a blogesfera está começando a ficar séria aqui no Brasil!

=============

As inovações e a nova política industrial

Naércio Menezes Filho professor de economia do IBMEC-SP, da FEA-USP e diretor de pesquisas do Instituto Futuro Brasil, escreve mensalmente às sextas-feiras.

Deste modo Yahoo demonstra que está vivo e inovando.  Isso talvez possa despertar ainda mais interesse da Microsoft!

E a diferença está na capacidade que Google tem de monetizar seu espaço virtual com propaganda!

Este mundo foi inicialmente "povoado" pelo Second Life, que ganhou massa crítica.  Second Life se tornou popular, ganhou mais buzz do que provavelmente merecia, e encontrou seus entraves em tempo record.  A IBM começou a experimentar com seu próprio engenho de mundo virtual,  projetado para uso corporativo, oferecendo conversação segura e objetivando fomentar inovação.

Vamos ver no que Lively vai dar! Se corresponder à trajetória da própria Google, tem tudo para ser um sucesso!

===============================

What the Internet is doing to our brains

by Nicholas Carr

Is Google Making Us Stupid?

brain. “Dave, my mind is going,” HAL says, forlornly. “I can feel it. I can feel it.”

I can feel it, too. Over the past few years I’ve had an uncomfortable sense that someone, or something, has been tinkering with my brain, remapping the neural circuitry, reprogramming the memory. My mind isn’t going—so far as I can tell—but it’s changing. I’m not thinking the way I used to think. I can feel it most strongly when I’m reading. Immersing myself in a book or a lengthy article used to be easy. My mind would get caught up in the narrative or the turns of the argument, and I’d spend hours strolling through long stretches of prose. That’s rarely the case anymore. Now my concentration often starts to drift after two or three pages. I get fidgety, lose the thread, begin looking for something else to do. I feel as if I’m always dragging my wayward brain back to the text. The deep reading that used to come naturally has become a struggle.

I think I know what’s going on. For more than a decade now, I’ve been spending a lot of time online, searching and surfing and sometimes adding to the great databases of the Internet. The Web has been a godsend to me as a writer. Research that once required days in the stacks or periodical rooms of libraries can now be done in minutes. A few Google searches, some quick clicks on hyperlinks, and I’ve got the telltale fact or pithy quote I was after. Even when I’m not working, I’m as likely as not to be foraging in the Web’s info-thickets—reading and writing e-mails, scanning headlines and blog posts, watching videos and listening to podcasts, or just tripping from link to link to link. (Unlike footnotes, to which they’re sometimes likened, hyperlinks don’t merely point to related works; they propel you toward them.)

For me, as for others, the Net is becoming a universal medium, the conduit for most of the information that flows through my eyes and ears and into my mind. The advantages of having immediate access to such an incredibly rich store of information are many, and they’ve been widely described and duly applauded. “The perfect recall of silicon memory,” Wired’s Clive Thompson has written, “can be an enormous boon to thinking.” But that boon comes at a price. As the media theorist Marshall McLuhan pointed out in the 1960s, media are not just passive channels of information. They supply the stuff of thought, but they also shape the process of thought. And what the Net seems to be doing is chipping away my capacity for concentration and contemplation. My mind now expects to take in information the way the Net distributes it: in a swiftly moving stream of particles. Once I was a scuba diver in the sea of words. Now I zip along the surface like a guy on a Jet Ski.

I’m not the only one. When I mention my troubles with reading to friends and acquaintances—literary types, most of them—many say they’re having similar experiences. The more they use the Web, the more they have to fight to stay focused on long pieces of writing. Some of the bloggers I follow have also begun mentioning the phenomenon. Scott Karp, who writes a blog about online media, recently confessed that he has stopped reading books altogether. “I was a lit major in college, and used to be [a] voracious book reader,” he wrote. “What happened?” He speculates on the answer: “What if I do all my reading on the web not so much because the way I read has changed, i.e. I’m just seeking convenience, but because the way I THINK has changed?”

Bruce Friedman, who blogs regularly about the use of computers in medicine, also has described how the Internet has altered his mental habits. “I now have almost totally lost the ability to read and absorb a longish article on the web or in print,” he wrote earlier this year. A pathologist who has long been on the faculty of the University of Michigan Medical School, Friedman elaborated on his comment in a telephone conversation with me. His thinking, he said, has taken on a “staccato” quality, reflecting the way he quickly scans short passages of text from many sources online. “I can’t read War and Peace anymore,” he admitted. “I’ve lost the ability to do that. Even a blog post of more than three or four paragraphs is too much to absorb. I skim it.”

Anecdotes alone don’t prove much. And we still await the long-term neurological and psychological experiments that will provide a definitive picture of how Internet use affects cognition. But a recently published study of online research habits, conducted by scholars from University College London, suggests that we may well be in the midst of a sea change in the way we read and think. As part of the five-year research program, the scholars examined computer logs documenting the behavior of visitors to two popular research sites, one operated by the British Library and one by a U.K. educational consortium, that provide access to journal articles, e-books, and other sources of written information. They found that people using the sites exhibited “a form of skimming activity,” hopping from one source to another and rarely returning to any source they’d already visited. They typically read no more than one or two pages of an article or book before they would “bounce” out to another site. Sometimes they’d save a long article, but there’s no evidence that they ever went back and actually read it. The authors of the study report:

It is clear that users are not reading online in the traditional sense; indeed there are signs that new forms of “reading” are emerging as users “power browse” horizontally through titles, contents pages and abstracts going for quick wins. It almost seems that they go online to avoid reading in the traditional sense.

Thanks to the ubiquity of text on the Internet, not to mention the popularity of text-messaging on cell phones, we may well be reading more today than we did in the 1970s or 1980s, when television was our medium of choice. But it’s a different kind of reading, and behind it lies a different kind of thinking—perhaps even a new sense of the self. “We are not only what we read,” says Maryanne Wolf, a developmental psychologist at Tufts University and the author of Proust and the Squid: The Story and Science of the Reading Brain. “We are how we read.” Wolf worries that the style of reading promoted by the Net, a style that puts “efficiency” and “immediacy” above all else, may be weakening our capacity for the kind of deep reading that emerged when an earlier technology, the printing press, made long and complex works of prose commonplace. When we read online, she says, we tend to become “mere decoders of information.” Our ability to interpret text, to make the rich mental connections that form when we read deeply and without distraction, remains largely disengaged.

Reading, explains Wolf, is not an instinctive skill for human beings. It’s not etched into our genes the way speech is. We have to teach our minds how to translate the symbolic characters we see into the language we understand. And the media or other technologies we use in learning and practicing the craft of reading play an important part in shaping the neural circuits inside our brains. Experiments demonstrate that readers of ideograms, such as the Chinese, develop a mental circuitry for reading that is very different from the circuitry found in those of us whose written language employs an alphabet. The variations extend across many regions of the brain, including those that govern such essential cognitive functions as memory and the interpretation of visual and auditory stimuli. We can expect as well that the circuits woven by our use of the Net will be different from those woven by our reading of books and other printed works.

Sometime in 1882, Friedrich Nietzsche bought a typewriter—a Malling-Hansen Writing Ball, to be precise. His vision was failing, and keeping his eyes focused on a page had become exhausting and painful, often bringing on crushing headaches. He had been forced to curtail his writing, and he feared that he would soon have to give it up. The typewriter rescued him, at least for a time. Once he had mastered touch-typing, he was able to write with his eyes closed, using only the tips of his fingers. Words could once again flow from his mind to the page.

But the machine had a subtler effect on his work. One of Nietzsche’s friends, a composer, noticed a change in the style of his writing. His already terse prose had become even tighter, more telegraphic. “Perhaps you will through this instrument even take to a new idiom,” the friend wrote in a letter, noting that, in his own work, his “‘thoughts’ in music and language often depend on the quality of pen and paper.”

“You are right,” Nietzsche replied, “our writing equipment takes part in the forming of our thoughts.” Under the sway of the machine, writes the German media scholar Friedrich A. Kittler, Nietzsche’s prose “changed from arguments to aphorisms, from thoughts to puns, from rhetoric to telegram style.”

The human brain is almost infinitely malleable. People used to think that our mental meshwork, the dense connections formed among the 100 billion or so neurons inside our skulls, was largely fixed by the time we reached adulthood. But brain researchers have discovered that that’s not the case. James Olds, a professor of neuroscience who directs the Krasnow Institute for Advanced Study at George Mason University, says that even the adult mind “is very plastic.” Nerve cells routinely break old connections and form new ones. “The brain,” according to Olds, “has the ability to reprogram itself on the fly, altering the way it functions.”

As we use what the sociologist Daniel Bell has called our “intellectual technologies”—the tools that extend our mental rather than our physical capacities—we inevitably begin to take on the qualities of those technologies. The mechanical clock, which came into common use in the 14th century, provides a compelling example. In Technics and Civilization, the historian and cultural critic Lewis Mumford described how the clock “disassociated time from human events and helped create the belief in an independent world of mathematically measurable sequences.” The “abstract framework of divided time” became “the point of reference for both action and thought.”

The clock’s methodical ticking helped bring into being the scientific mind and the scientific man. But it also took something away. As the late MIT computer scientist Joseph Weizenbaum observed in his 1976 book, Computer Power and Human Reason: From Judgment to Calculation, the conception of the world that emerged from the widespread use of timekeeping instruments “remains an impoverished version of the older one, for it rests on a rejection of those direct experiences that formed the basis for, and indeed constituted, the old reality.” In deciding when to eat, to work, to sleep, to rise, we stopped listening to our senses and started obeying the clock.

The process of adapting to new intellectual technologies is reflected in the changing metaphors we use to explain ourselves to ourselves. When the mechanical clock arrived, people began thinking of their brains as operating “like clockwork.” Today, in the age of software, we have come to think of them as operating “like computers.” But the changes, neuroscience tells us, go much deeper than metaphor. Thanks to our brain’s plasticity, the adaptation occurs also at a biological level.

The Internet promises to have particularly far-reaching effects on cognition. In a paper published in 1936, the British mathematician Alan Turing proved that a digital computer, which at the time existed only as a theoretical machine, could be programmed to perform the function of any other information-processing device. And that’s what we’re seeing today. The Internet, an immeasurably powerful computing system, is subsuming most of our other intellectual technologies. It’s becoming our map and our clock, our printing press and our typewriter, our calculator and our telephone, and our radio and TV.

When the Net absorbs a medium, that medium is re-created in the Net’s image. It injects the medium’s content with hyperlinks, blinking ads, and other digital gewgaws, and it surrounds the content with the content of all the other media it has absorbed. A new e-mail message, for instance, may announce its arrival as we’re glancing over the latest headlines at a newspaper’s site. The result is to scatter our attention and diffuse our concentration.

The Net’s influence doesn’t end at the edges of a computer screen, either. As people’s minds become attuned to the crazy quilt of Internet media, traditional media have to adapt to the audience’s new expectations. Television programs add text crawls and pop-up ads, and magazines and newspapers shorten their articles, introduce capsule summaries, and crowd their pages with easy-to-browse info-snippets. When, in March of this year, TheNew York Times decided to devote the second and third pages of every edition to article abstracts, its design director, Tom Bodkin, explained that the “shortcuts” would give harried readers a quick “taste” of the day’s news, sparing them the “less efficient” method of actually turning the pages and reading the articles. Old media have little choice but to play by the new-media rules.

Never has a communications system played so many roles in our lives—or exerted such broad influence over our thoughts—as the Internet does today. Yet, for all that’s been written about the Net, there’s been little consideration of how, exactly, it’s reprogramming us. The Net’s intellectual ethic remains obscure.

About the same time that Nietzsche started using his typewriter, an earnest young man named Frederick Winslow Taylor carried a stopwatch into the Midvale Steel plant in Philadelphia and began a historic series of experiments aimed at improving the efficiency of the plant’s machinists. With the approval of Midvale’s owners, he recruited a group of factory hands, set them to work on various metalworking machines, and recorded and timed their every movement as well as the operations of the machines. By breaking down every job into a sequence of small, discrete steps and then testing different ways of performing each one, Taylor created a set of precise instructions—an “algorithm,” we might say today—for how each worker should work. Midvale’s employees grumbled about the strict new regime, claiming that it turned them into little more than automatons, but the factory’s productivity soared.

More than a hundred years after the invention of the steam engine, the Industrial Revolution had at last found its philosophy and its philosopher. Taylor’s tight industrial choreography—his “system,” as he liked to call it—was embraced by manufacturers throughout the country and, in time, around the world. Seeking maximum speed, maximum efficiency, and maximum output, factory owners used time-and-motion studies to organize their work and configure the jobs of their workers. The goal, as Taylor defined it in his celebrated 1911 treatise, The Principles of Scientific Management, was to identify and adopt, for every job, the “one best method” of work and thereby to effect “the gradual substitution of science for rule of thumb throughout the mechanic arts.” Once his system was applied to all acts of manual labor, Taylor assured his followers, it would bring about a restructuring not only of industry but of society, creating a utopia of perfect efficiency. “In the past the man has been first,” he declared; “in the future the system must be first.”

Taylor’s system is still very much with us; it remains the ethic of industrial manufacturing. And now, thanks to the growing power that computer engineers and software coders wield over our intellectual lives, Taylor’s ethic is beginning to govern the realm of the mind as well. The Internet is a machine designed for the efficient and automated collection, transmission, and manipulation of information, and its legions of programmers are intent on finding the “one best method”—the perfect algorithm—to carry out every mental movement of what we’ve come to describe as “knowledge work.”

Google’s headquarters, in Mountain View, California—the Googleplex—is the Internet’s high church, and the religion practiced inside its walls is Taylorism. Google, says its chief executive, Eric Schmidt, is “a company that’s founded around the science of measurement,” and it is striving to “systematize everything” it does. Drawing on the terabytes of behavioral data it collects through its search engine and other sites, it carries out thousands of experiments a day, according to the Harvard Business Review, and it uses the results to refine the algorithms that increasingly control how people find information and extract meaning from it. What Taylor did for the work of the hand, Google is doing for the work of the mind.

The company has declared that its mission is “to organize the world’s information and make it universally accessible and useful.” It seeks to develop “the perfect search engine,” which it defines as something that “understands exactly what you mean and gives you back exactly what you want.” In Google’s view, information is a kind of commodity, a utilitarian resource that can be mined and processed with industrial efficiency. The more pieces of information we can “access” and the faster we can extract their gist, the more productive we become as thinkers.

Where does it end? Sergey Brin and Larry Page, the gifted young men who founded Google while pursuing doctoral degrees in computer science at Stanford, speak frequently of their desire to turn their search engine into an artificial intelligence, a HAL-like machine that might be connected directly to our brains. “The ultimate search engine is something as smart as people—or smarter,” Page said in a speech a few years back. “For us, working on search is a way to work on artificial intelligence.” In a 2004 interview with Newsweek, Brin said, “Certainly if you had all the world’s information directly attached to your brain, or an artificial brain that was smarter than your brain, you’d be better off.” Last year, Page told a convention of scientists that Google is “really trying to build artificial intelligence and to do it on a large scale.”

Such an ambition is a natural one, even an admirable one, for a pair of math whizzes with vast quantities of cash at their disposal and a small army of computer scientists in their employ. A fundamentally scientific enterprise, Google is motivated by a desire to use technology, in Eric Schmidt’s words, “to solve problems that have never been solved before,” and artificial intelligence is the hardest problem out there. Why wouldn’t Brin and Page want to be the ones to crack it?

Still, their easy assumption that we’d all “be better off” if our brains were supplemented, or even replaced, by an artificial intelligence is unsettling. It suggests a belief that intelligence is the output of a mechanical process, a series of discrete steps that can be isolated, measured, and optimized. In Google’s world, the world we enter when we go online, there’s little place for the fuzziness of contemplation. Ambiguity is not an opening for insight but a bug to be fixed. The human brain is just an outdated computer that needs a faster processor and a bigger hard drive.

The idea that our minds should operate as high-speed data-processing machines is not only built into the workings of the Internet, it is the network’s reigning business model as well. The faster we surf across the Web—the more links we click and pages we view—the more opportunities Google and other companies gain to collect information about us and to feed us advertisements. Most of the proprietors of the commercial Internet have a financial stake in collecting the crumbs of data we leave behind as we flit from link to link—the more crumbs, the better. The last thing these companies want is to encourage leisurely reading or slow, concentrated thought. It’s in their economic interest to drive us to distraction.

Maybe I’m just a worrywart. Just as there’s a tendency to glorify technological progress, there’s a countertendency to expect the worst of every new tool or machine. In Plato’s Phaedrus, Socrates bemoaned the development of writing. He feared that, as people came to rely on the written word as a substitute for the knowledge they used to carry inside their heads, they would, in the words of one of the dialogue’s characters, “cease to exercise their memory and become forgetful.” And because they would be able to “receive a quantity of information without proper instruction,” they would “be thought very knowledgeable when they are for the most part quite ignorant.” They would be “filled with the conceit of wisdom instead of real wisdom.” Socrates wasn’t wrong—the new technology did often have the effects he feared—but he was shortsighted. He couldn’t foresee the many ways that writing and reading would serve to spread information, spur fresh ideas, and expand human knowledge (if not wisdom).

The arrival of Gutenberg’s printing press, in the 15th century, set off another round of teeth gnashing. The Italian humanist Hieronimo Squarciafico worried that the easy availability of books would lead to intellectual laziness, making men “less studious” and weakening their minds. Others argued that cheaply printed books and broadsheets would undermine religious authority, demean the work of scholars and scribes, and spread sedition and debauchery. As New York University professor Clay Shirky notes, “Most of the arguments made against the printing press were correct, even prescient.” But, again, the doomsayers were unable to imagine the myriad blessings that the printed word would deliver.

So, yes, you should be skeptical of my skepticism. Perhaps those who dismiss critics of the Internet as Luddites or nostalgists will be proved correct, and from our hyperactive, data-stoked minds will spring a golden age of intellectual discovery and universal wisdom. Then again, the Net isn’t the alphabet, and although it may replace the printing press, it produces something altogether different. The kind of deep reading that a sequence of printed pages promotes is valuable not just for the knowledge we acquire from the author’s words but for the intellectual vibrations those words set off within our own minds. In the quiet spaces opened up by the sustained, undistracted reading of a book, or by any other act of contemplation, for that matter, we make our own associations, draw our own inferences and analogies, foster our own ideas. Deep reading, as Maryanne Wolf argues, is indistinguishable from deep thinking.

If we lose those quiet spaces, or fill them up with “content,” we will sacrifice something important not only in our selves but in our culture. In a recent essay, the playwright Richard Foreman eloquently described what’s at stake:

I come from a tradition of Western culture, in which the ideal (my ideal) was the complex, dense and “cathedral-like” structure of the highly educated and articulate personality—a man or woman who carried inside themselves a personally constructed and unique version of the entire heritage of the West. [But now] I see within us all (myself included) the replacement of complex inner density with a new kind of self—evolving under the pressure of information overload and the technology of the “instantly available.”

As we are drained of our “inner repertory of dense cultural inheritance,” Foreman concluded, we risk turning into “‘pancake people’—spread wide and thin as we connect with that vast network of information accessed by the mere touch of a button.”

I’m haunted by that scene in 2001. What makes it so poignant, and so weird, is the computer’s emotional response to the disassembly of its mind: its despair as one circuit after another goes dark, its childlike pleading with the astronaut—“I can feel it. I can feel it. I’m afraid”—and its final reversion to what can only be called a state of innocence. HAL’s outpouring of feeling contrasts with the emotionlessness that characterizes the human figures in the film, who go about their business with an almost robotic efficiency. Their thoughts and actions feel scripted, as if they’re following the steps of an algorithm. In the world of 2001, people have become so machinelike that the most human character turns out to be a machine. That’s the essence of Kubrick’s dark prophecy: as we come to rely on computers to mediate our understanding of the world, it is our own intelligence that flattens into artificial intelligence.

===========

Living With a Computer

(July 1982)
"The process works this way. When I sit down to write a letter or start the first draft of an article, I simply type on the keyboard and the words appear on the screen..." By James Fallows

... está publicando (a partir de 2009) quatro novas revistas: Applied Economics; Economic Policy; Macroeconomics, e Microeconomics.

Em meus mais de 20 anos de consulta aos journals da AEA esta é uma das grandes surpresas que ela traz ao mundo econômico da academia. Parabéns AEA!

O artigo abaixo é de Jason Hiner, da TechRepublic!

=======================
"Five things we have learned from Bill Gates"

Whether or not you are a fan of Bill Gates, it is impossible to deny the impact he has made on the spread of computer technology across the planet during the past three decades. Since Friday was Gates’ last day as a full-time Microsoft employee, this is the perfect time to look back at five of the most important lessons we’ve learned from the meteoric, tumultuous, and lucrative career of the world’s most famous software engineer.

5. Geeks can be businessmen, too

Before Bill Gates, computer programmers were mostly considered to be a necessary evil for businesses. They were stereotyped as misanthropic weirdos that you stick in dark corners in the back office. However, Gates, became the most successful businessman on earth — if you judge business success by profits — and almost singlehandedly transformed the term “geek” from an insult to a badge of honor in the process.

4. You don’t have to be first to win

Gates and Microsoft rarely got to the party first with new technologies and innovations, but they were simply better at bringing technology products to the masses than anyone else in the industry. Internet Explorer is the most famous example, but Microsoft Windows, Microsoft Word, and Microsoft Excel are also great examples. Microsoft was merely better at executing. It didn’t hurt that Microsoft often had the most resources, but Gates and Co. showed over and over again that they knew how to best take advantage of those resources.

3. Computing will spread everywhere

In the 1980s when the computer was still mostly a novelty, Gates expressed his vision that there would one day be “a computer on every desk and in every home.” That vision has nearly become a reality in the U.S. and it’s in the process of coming to fruition across the globe. Plus, Gates’ vision of the computing experience has continued to inspire the industry in general as well as Microsoft’s product plans — from the smartphone to the Tablet PC to speech recognition to the touch-based interface.

2. Arrogance breeds failure

In the movie Pirates of Silicon Valley, the Bill Gates character says to Steve Ballmer, “Success is a menace. It fools smart people into thinking that they can’t lose.” He was referring to IBM and the fact that it let Microsoft sneak in and steal the thunder in the launch of the PC. A decade later, Microsoft’s own success and arrogance led to its anti-trust defeat to the U.S. government. But Microsoft also remained humble and paranoid enough to always be on the lookout for the next small company that might do to it what it had done to IBM. Some of the most popular targets in its cross hairs: Apple, Netscape, Linux, and Google.

1. Software matters

The one message that Bill Gates spent his career reiterating was that software matters. Gates and Microsoft always believed in the magic of software to create amazing digital experiences. When “Micros-Soft” (as it was originally known) first launched in the 1970s, the computer business was all about the hardware. It was Gates and his vision of what people could do with computers that moved software to the center of the computing experience.

É para isso que serve modelagem econômica! Logo, não se deixe influenciar por achismos ou tentativas de opiniões de muitos (principalmente na imprensa) que não têm fundamentação econômica. 

Conselho: simplesmente modele o fenômeno! As ferramentas são simples: leis da demanda e da oferta!

====================

An Increase in Worldwide Demand for Oil

Mas pouco percebemos isto quando se trata de associar a educação às efetivas oportunidade de emprego (ou das oportunidades perdidas com o desemprego).  O gráfico abaixo (de hoje do blog do Prof. Mark Perry) mostra, para o caso dos EUA, a evidência da dinâmica do mercado de trabalho americano em função da escolaridade!

O gráfico é mais um indicativo do que se denomina hoje de "skilled biased technical change" (mudança tecnológica voltada para os mais capacitados).  Ou seja, quem está mais capacitado sofre menos as variações do desemprego (principalmente no mercado de trabalho mais flexível do mundo, como é o dos EUA).  Ele mostra como o desemprego vinha caindo nos EUA até o estouro da bolha das empresas ponto.com e aumentou logo em seguida, e como ele está subindo novamente desde 2007, em função do estouro da bolha do mercado imobiliário de lá!.

=====================

Chart of the Day: Finish High School, Finish College

Hoje percebi que algumas pessoas identificaram no próprio Bill Gates a transição para esta outra era.  Elas perceberam que Gates pavimentou o caminho desta transição ao fazer um discurso no início deste ano no World Economic Forum em Davos, na Suíça.  E o que foi destaque, além do discurso, foi o fato dele ter cunhado a expressão "Capitalismo Criativo".

Pois bem! Alguns autores pegaram esta idéia e estão propondo um livro com uma série de artigos sobre este assunto. Se você estiver interessado é só entar no seguinte blog: http://www.creativecapitalismblog.com/creative_capitalism/what-is-creative.html.

Mas o mais interessante do lançamento foi o reforço que Nicholas Carr, autor de “Does IT Matter” e “The Big Switch,” deu com uma breve mensagem sobre a mudança para cloud computing e porque nós precisamos pensar sobre ética da infraestrutura. Ele também apontou que a Structure08 conference estava acontecendo na semana que Bill Gates se aposenta da Microsoft. Carr vê este fato  como o fim de uma era da computação e o início de outra.  A mensagem está no vídeo abaixo:

A nova revista The Economist traz Bill Gates na capa.  E o sub-título da matéria é interessante: "À medida que seu reino termina, também termina a era que ele dominou!

Começou uma fuga de talentos do Yahoo.  É o que trata uma interessante matéria da Businessweek!

Se isto é um resultado da não desejada oferta da Microsoft, ou se é fruto dos comentários do investidor Carl Icahn, só o tempo pode dizer! 

========================

11 Billion videos served - Profits ???

Eis aqui uma boa entrevista com o economista James Poterba, que foi escolhido como o novo Presidente do NBER-National Bureau of Economic Research, um dos mais renomados think tanks de Economia do mundo.  A entrevista foi concedida ao Federal Reserve Bank of Minneapolis, USA.

===========

Interview with James Poterba  

Interview conducted April 1, 2008.

It's often said that economists agree on little, but there was no divergence of opinion when the National Bureau of Economic Research, the nation's premier body of research economists, announced it had selected James Poterba as its new president and CEO as of July 1. Economists of all stripes were unanimous in their praise.

Left-of-center columnist Paul Krugman deemed Poterba “a great choice.” Republican Martin Feldstein, NBER president for 30 years, declared Poterba “an excellent fit.” Freakonomics co-author Steven Levitt summed it up: “The choice was so obvious that I can't say I'm surprised. Nonetheless, I couldn't be more delighted, both for Poterba and for the profession. This is wonderful news.”

Poterba—a summa cum laude graduate of Harvard College, a Marshall scholar at Oxford University, a fellow of the American Academy of Arts and Sciences and the Econometric Society—personifies the highest standards of scholarship in economics. His work on the impact of taxation on household and firm behavior is fundamental in the profession, and his recent exploration of how taxes affect savings and portfolio decisions, and tax-deferred retirement plans in particular, has been pathbreaking.

But skills honed as head of the top-rated economics department at the Massachusetts Institute of Technology, as editor of the Journal of Public Economics, as director of the NBER's program on public economics and on countless policy committees over the years will be central to his future leadership of NBER. Colleagues refer often to his impartiality and his ability to bring fractious debate to cohesive conclusion. In the contentious world of research (and allocation of resources within), such skills will be invaluable.

In the following interview, that same respect for evidence and thoughtful consideration of alternatives is evident, but Poterba also promises to respond “nimbly” to the pressing economic challenges of our time. “One of the NBER's great strengths,” he notes, “is its ability to bring a whole range of economic researchers to bear on important questions as they emerge.”

TAX REFORM

Region: Let me throw you in the deep end. With the presidential election drawing near, tax policy is sure to become a topic of increasing debate. As a tax scholar and a member of the 2005 President's Advisory Panel on Tax Reform, what kind of advice would you offer to an incoming president on tax policy?

Poterba: We are approaching a period when tax reform will likely move out of academic discussion and attract serious attention from Washington policymakers, for two reasons.

One is the Alternative Minimum Tax, a feature of the tax code that was originally designed to affect very-high-income taxpayers but has over time come to affect a larger and larger fraction of the U.S. tax-paying population because the relevant provisions were not indexed for inflation. Congress has been fixing the AMT one year at a time by raising the thresholds at which it affects taxpayers. But the one-year fix strategy is becoming increasingly expensive because the compounding of inflation keeps lowering the levels at which statutory thresholds kick in. It's likely that Congress will have to do something to fix the AMT in a more permanent way—after the next election would be a natural time.

The other factor that will draw tax reform into the middle of the political debate is the scheduled expiration of the tax changes that were enacted in 2001 and 2003. The expiring provisions include reductions in marginal tax rates as well as the tax rate relief on dividends and capital gains. The estate tax will also revert to its pre-2001 form if Congress does not act in 2009 or 2010.

It's difficult to predict where tax reform is likely to go. When the president's tax panel looked at the AMT and other issues in 2005, we recognized that there was no easy solution to the challenge of tax reform. Fixing the AMT is a very expensive proposition. It costs more than a trillion dollars over a medium-term budget window to repeal the AMT, and if you're going to do that in a revenue-neutral way, you have to either change income tax rates or broaden the income tax base. The tax panel pushed toward the base-broadening approach, which I think has a great deal to recommend it.

Of course, supporting base-broadening is hardly novel. It's almost a reflexive action for most public finance economics. Marginal distortions associated with the tax code tend to rise with the square of the tax rate, so that as the tax rate gets into higher and higher territory, the marginal dead-weight losses tend to grow rapidly. Going from a 30 percent to a 40 percent marginal tax rate, for example, doesn't increase the marginal efficiency cost of taxation by a factor of 1.33, but by the ratio of 16 over 9—close to 75 percent.

Region: Thus the appeal of broadening the base.

Poterba: Exactly. Broadening the tax base reduces the need to impose high marginal dead-weight burdens associated with high marginal tax rates. The challenge of broadening the base—which I fear the tax panel members learned the hard way by proposing a lot of base-broadening and then seeing the proposals go nowhere in the political system—is that most of the things that erode the current income tax base are political sacred cows. These include the home mortgage interest deduction, the exclusion of employer-provided health insurance from the tax base for individuals, the deduction for state and local property taxes, and the relief we provide on medical expenditures of various kinds. They all have constituencies that find them very important and very attractive. There isn't a strong constituency at the moment, and probably never will be, for the efficiency gains associated with broadening the tax base and lowering rates.

So you're faced with one of the classic political economy problems of imposing burdens on an identifiable group that can tell they're going to have their oxes gored by the particular reform you've proposed, while generating broadly diffused benefits for the population at large in the form of a more efficient structure for raising revenue.

Region: Is there any hope that the political system can embrace broad-based tax reform?

Poterba: It's not impossible, and it's happened before.  In 1986, the tax system was reformed in a way that broadened the base and lowered marginal rates across the board. What that took was a combination of the political stars lining up in just the right way and the policymakers and policy advisers—the academic economists and the economists in the policy process—making a strong and articulate case for the benefits of an efficiency-improving tax reform.

In 1986, we'd been through a period with high inflation which had wrought havoc on the effective tax burdens on many investments. Inflation tends to raise the effective tax burden on bonds because the inflation premium in nominal bonds is taxed. The United States had higher tax marginal rates than many of our international competitors at that point. Policymakers recognized that these were serious concerns, and they managed, quite remarkably, to draw together in support of a major tax reform. I don't think it's impossible to do it again.

Region: The advisory panel also suggested a simpler code; is that a feasible goal?

Poterba: Absolutely. Simplification may be the easiest dimension of reform. If you look, for example, at the way we currently provide incentives for saving to finance retirement, education, medical expenditures—we have a dizzying array of programs: 401(k)s, IRAs, Roth IRAs, 403(b)s, 457s—all of these are basically ways of offering households what public finance economists call “consumption tax treatment” on their savings. By investing in these special forms, investors can earn the pretax return on their investments. But each of these account types has its own complicated set of rules, and many households don't know what they're eligible for and don't take full advantage of the opportunities that these programs present. Some simplification could surely be achieved by rolling some of those programs into a smaller number of more broadly available saving vehicles.

There probably are other opportunities for moving in the direction of a return-free system for a substantial number of low-income taxpayers who have relatively simple tax returns. If a taxpayer's only income source is wage income or that plus some very easily identifiable capital income, perhaps from a bank, the IRS could easily compute the household's tax liability and send out a bill.

The problem with simplicity is that while almost everybody thinks that a simpler tax code is an attractive ideal, in many cases the tax code is not simple because it's trying to deal with the complexity of economic life. You could make the tax code simpler, for example, by having one tax schedule for everybody and just saying that married couples and single individuals would file on the same schedule; no need to look up different rates or anything else. But of course that would offend some people's sense of fairness. They would say that a two-person household with a given income should not necessarily face the same tax burden as a five-person household with the same income, or as a single individual with that income. So you say, “Okay, we'll have different tax codes for married couples; we'll allow for some dependency deductions.” Soon you're on the path to making the tax system more complicated. The same thing happens to an even greater degree when you're trying to track the income from investment property. A lot of the complexity really comes from the fact that people do complicated things, and we need to track them appropriately.

While it would be straightforward to simplify the tax code for quite a large number of taxpayers, some of the inherent complexity of the tax code that's associated with the measurement of capital income, with the tracking of business receipts and things like that, would be very difficult to get rid of without ending up with a tax system that many people would find objectionable.

TAX EXPENDITURES

Region: Going back to the issue of a broader tax base, I believe you've just hosted a conference on “tax expenditures.” Can you tell us about it?

Poterba: Sure. I organized the conference to address some questions that arose during the tax panel's discussions. Those discussions, incidentally, were great. Serving on the panel was a remarkably interesting and educational experience. The other members brought a variety of interesting and insightful backgrounds to bear on the questions of tax reform, and they worked incredibly hard on the issues we faced. We also had a fabulous professional staff of both lawyers and economists who tackled a lot of the difficult issues that tax reform raises.

As I worked with that very distinguished group, I realized that a key issue that is likely to emerge next time we have a big tax reform discussion concerns how to broaden the income tax base. This will require good estimates of the economic effects of various current tax code provisions that narrow the base. The research projects that were presented at the recent conference focused on this issue. Under the auspices of the National Bureau of Economic Research, I brought together 11 research teams working on various features of the current tax code that cause deviations from a broad-based income tax and lead to revenue reductions.

Region: Revenues forgone by the government as a result of tax exemptions, credits or exclusions?

Poterba: Exactly. Over time there's been an increasing use of the tax code for social engineering through various kinds of deductions and credits, most of which would fall into the tax expenditure category. For example, we now encourage various kinds of energy activities with tax credits or tax deductions. We encourage the construction of low-income housing with tax credits. These incentives are joining the more traditional and bigger ticket items like the tax exemption for employer-provided health insurance and for property taxes, the home mortgage interest deduction, and the exemption for state and local interest payments on tax-exempt bonds.

I organized the research project that was summarized at the conference to focus on a set of tax expenditures that would be regarded as narrowing the tax base both by those who support an income tax and by those who support an expenditure tax, a tax based on consumption rather than income. An income tax taxes the return to capital income; a consumption tax does not.

The research presented at the conference did not consider the tax expenditures for private pensions, 401(k)s, IRAs and other types of tax-deferred savings. These provisions of the tax code reduce revenues if the benchmark is an income tax, but not if it is a consumption tax. The conference brought new empirical work to bear on these issues and also provided detailed information based on tax returns and household surveys on the distribution of benefits associated with the current tax expenditures. Some of the researchers also looked at the behavioral consequences of tax expenditures.

To give you one example, my work with Todd Sinai at the Wharton School at the University of Pennsylvania focused on the tax treatment of owner-occupied housing. Not all homeowners have mortgages; the elderly often have fully paid-up houses, so they don't take advantage of the mortgage interest deduction. By contrast, younger households, particularly high-income younger households, have a lot of mortgage debt. Also, because house prices vary a lot from place to place—they're much higher in Boston than in Minneapolis and higher still in San Francisco—the geographical diversity of the benefits of the home mortgage interest deduction is substantial. Another source of variation is that not all households with mortgages itemize on their tax returns. Those who do not cannot claim a mortgage interest deduction.

Todd and I found that the mortgage interest deduction is a benefit skewed toward young households in high-income areas on the East and West coasts. It is also more beneficial to higher-income taxpayers because the benefit is proportional to the taxpayer's marginal tax rate. So somebody who's at a 35 percent bracket saves more than somebody who's in a 25 or 15 percent bracket. That's an important feature of many tax expenditures—their value is increasing with marginal tax rates. It is not obvious that one would design a tax subsidy so that its value increases with a household's income or marginal tax rate.

Region: You've also been looking at the nontaxation of imputed rent of owner-occupied housing, I believe.

Poterba: Yes. As a homeowner, you are buying a long-lived durable asset and then renting it to yourself each period. Think of it as two transactions: In one, you're a consumer who pays the landlord, while in the other, you're the landlord who's collecting the rent. It just happens that the landlord and the tenant are the same person.

The income tax doesn't tax the implicit rental income that a homeowner receives in the landlord capacity. If the same taxpayer owned a rental building and collected rent from a tenant, that income would be taxed. The nontaxation of implicit rent means that owner-occupied housing is taxed less heavily than many other assets in the economy. The result is that we have much more owner-occupied housing in the U.S. economy than we would otherwise. The distortion is likely to be larger for high-income taxpayers who are in higher tax brackets.

This is a standard example of how the tax code distorts the economy, which in turn leads to a more efficient allocation of capital than in a no-tax world. In many general equilibrium models built to study taxes and other issues, when there are different tax burdens on different kinds of assets, the level of output is substantially lower than in an economy in which all assets are taxed the same way.

HOUSING AND THE WEALTH EFFECT

Region: Let me ask about another issue related to housing. In 2000, in a paper reviewing evidence on the wealth effect, you concluded that the “rising stock market has surely contributed to rising consumer spending in the 1990s” but that there is “at best a weak link between house price changes and nonhousing consumption.”

Since that time, of course, both equity and housing markets have undergone significant boom and collapse cycles. What is your sense right now of the impact of the housing market collapse on consumer spending?

Poterba: Great question. Much of the discussion of the wealth effect seems to assume that there's a question of whether it exists. I think that's a misapprehension. The simple logic of budget constraints for multiperiod consumers and households tells you that if you reduce the value of the assets that households own at a given point in time, the present discounted value of their consumption stream must be reduced correspondingly. So the real question is simply, How does a household, or the household sector in aggregate, spread the loss of wealth from a drop in equity values or house values over various consumption in various future periods?

Region: So it's not whether, but when and how big.

Poterba: Right, and once we say that, we are drawn to the question of how precisely we can measure these effects. This is a particular challenge since in the aggregate data, if asset prices have changed precipitously over some time period, it's typically not the case that the only shock buffeting the economy is the movement in asset prices. If we see a significant move in stock prices, for example, it's possible that consumers might also have changed their future expectations of interest rates or other discount factors; risk premia may have changed in the economy; the expected wage path the consumer thinks he or she may be able to achieve by supplying labor in the future may also have changed at about the same time.

All of those variables potentially can affect the level of consumer spending, so teasing out the part that can be identified with the wealth effect of movements in the stock market becomes very difficult. The same is true when you pose the question with respect to housing, particularly in the context of a large house price movement like the one we've seen in the last couple of years. When we look back at the current period, it may be hard to identify the effect of house price movements as distinct from changes in lending practices and other aspects of the financial environment.

Region: But scholars have made the effort nonetheless. What have you found?

Poterba: Yes, there have been some attempts to look at cross-sectional differences in the exposure of households to different kinds of wealth. For example, some households hold more stock than others and consequently would be more exposed to a revaluation of stock market equities, so one can study those households to see if they are particularly sensitive to stock price fluctuations.

Equity ownership is concentrated in the United States. Households in the top 1 percent of the wealth distribution own more than half of the corporate stock which is held outside of retirement accounts. Even if you include retirement account wealth, the concentration is still very high. With housing equity, by the way, there's a more egalitarian distribution. The top 1 percent owns about 15 percent of housing. In the portfolios of the richest households, housing equity is less important than other sources of financial wealth.

One thing that researchers have tried is to see if there is evidence that households with lots of equity exposure tend to cut their consumption back more when the stock market tends to decline. Unfortunately, we don't have very good measures of consumer spending at the household level linked up with high-quality data on the household balance sheet, especially for the best-off households.

The Federal Reserve System sets the gold standard for household balance sheet information with the Survey of Consumer Finances. This survey is administered every three years. The most recent version was 2007, and we should have the data from that survey later this year.

Region: But there are definite limitations to SCF data, including a small sample of upper-income families, right?

Poterba: It's true that the SCF doesn't have a very large sample of the upper-wealth households, but it is still by far the best source of information about this group. But the real problem for studying wealth effects is that the SCF doesn't have any data on consumer spending. This is not because the consumption data would not be of great value—it is just because there is a trade-off between getting respondents to answer the survey and the length of the survey, and adding questions about consumption might lengthen the questionnaire and depress the response rate. Also, the SCF is a snapshot. It's a one-time cross section each time it's administered, so researchers cannot study a given household and see how its wealth changed over time.

The data sets that do have a lot of information on consumer spending either have very little information on assets or have very little information on the high-wealth households who are likely to be the key holders of corporate stock.

It may be possible, using other data sets, to get a better fix on the wealth effect of house price movements. But there is another complication. Movements in house values in regional and local economies are tied up with employment prospects and many other factors. In some of the boom housing markets of the last decade—Southern California, Las Vegas, South Florida, for example—construction became a very important part of the economy. When house prices decline and the construction sector contracts, the effect on consumer spending cannot be attributed only to a simple wealth effect. It is very hard to design empirical tests which can distinguish wealth effects from other associated shocks.

These serious concerns notwithstanding, when one looks at the historical correlations between aggregate wealth movements and aggregate consumer spending, controlling as well as possible for other shocks to the economy, one finds something between 4 cents on the dollar, 6 cents on the dollar, of change in consumer spending within about 12 months of a stock market revaluation. That's not very different from the estimate of the consumption effect you would develop if instead of looking at data, you used a standard life-cycle model with plausible parameter values and worked through the potential effects of a wealth shock on consumer spending.

With regard to measuring the housing wealth effect, I worry that historical correlation patterns between price changes and consumer spending may be misleading because the financial services environment has changed in ways that may alter the underlying behavior we're interested in. The changes in lending practices that took place between 1990 and 2002 made it easier for households to tap into their home equity and provided home equity loans on a broader scale than in the past. Related changes altered the loan-to-value ratios of first-time home buyers in a way that could change the link between house prices and consumer spending. I suspect that the innovations in the financial services area increased the linkages between changes in house prices and changes in consumer spending. We saw those on the upside in a period of rising house prices, as households withdrew equity from their homes. The current discussions of foreclosures and trying to find ways to keep people in their homes suggest that we're just in the early stages of finding out what those dynamics are going to be on the downside.

SAVING FOR RETIREMENT

Region: With Joshua Rauh, Steven Venti and David Wise, you've conducted a great deal of research on the shift from defined-benefit to defined-contribution retirement plans, one of the major changes in the private pension landscape. Can you tell us about that transformation?

Poterba: Over the last two decades, we have seen a radical change in the role of the individual in taking responsibility for retirement in the U.S. economy.

Twenty-five or 30 years ago, the predominant form of employer-provided retirement benefit was a defined-benefit pension plan. A defined-benefit, or DB, pension plan is a liability of the employer which gives the worker an annuity when he or she retires. In most cases DB plans provided a guaranteed nominal income stream for as long as the worker, or the worker and the worker's spouse, remained alive. The worker never had to think much during the working phase about the way DB plan assets were invested by the firm. Most workers just knew that there was a formula, often complicated, which related their benefits after retirement to their last wage, years of service at the firm and the age at which they retired.

In the late 1960s and early 1970s, several large firms went bankrupt and their workers were left with empty pension promises. Their DB plans had not been funded, and this exposed a set of risks associated with the DB paradigm. In 1974, Congress passed ERISA, the Employee Retirement Income Security Act. It regulated DB plans along a number of dimensions and provided federal insurance for retiree benefits. The regulatory structure for DB plans was more stringent than that for defined-contribution plans, to which firms and employers contributed but with no benefit promise at retirement. Subsequent legislative changes raised the regulatory burden, particularly on firms with DB plans.

Firms responded to the changing regulatory environment, and to growing worker interest in defined-contribution plans in the 1990s, by shifting away from the historical DB model and toward DC plans. Very few new defined-benefit plans have been started in the last decade. There has been very rapid growth in defined-contribution plans, primarily the 401(k) type of plans. With these plans, the individual takes responsibility for deciding how much to contribute, how to invest the assets, what to do with the assets at retirement. The retirement options include leaving the assets in the plan, annuitizing them or taking them out as a lump-sum distribution. Those choices are important ones, and they all involve difficult decisions.

Financial economists will recognize that the planning problem for a household thinking about financial accumulation over the life cycle in a world with uncertain labor income, uncertain asset returns and uncertain mortality is difficult—even for someone with sophisticated analytical tools. Ordinary households confront a pretty daunting task in trying to make these decisions. The DC-based retirement system to which we have shifted offers households the opportunity to save more than they typically could in the defined-benefit world and to make different choices for retirement depending in part on their preferences and attributes. The DC system allows an individual who is in poor health to choose a lump-sum payout rather than an annuity, but it also allows an uninformed but healthy individual who does not recognize the chance of a very long retirement to inadvertently endanger his late-life resources by making the same choice.

Region: What does this mean for the future of retirement? Are 401(k)s likely to provide greater financial security for retirees than defined-benefit plans did?

Poterba: We are not quite far enough into the 401(k) experience yet to see how people do in the drawdown phase. Even though many retirees today are reaching retirement with some assets in a 401(k) plan, most of those people joined 401(k) plans relatively late in their working career.

The retirees who will hit retirement in 2025 or 2030 will have worked for most of their life under a 401(k) regime. They will have accumulated a lot more assets in that part of the retirement system, and the decisions they make will be much more consequential for how their retirement plays out than the decisions of today's retirees because many of today's 401(k) retirees also have a DB pension. A lot of 401(k) wealth is invested in equities. As we move forward, the future retirement accumulations for people in the 401(k) sector are going to be quite dependent on the equity return path.

If equities on average deliver returns like their historical returns since the 1920s, then there's every reason to think that accumulations in 401(k) plans will be larger by a substantial margin than the wealth values that were built up in traditional defined-benefit plans. On the other hand, there is a chance that equity markets will perform less well in the future than in the past—and a small chance of a much weaker performance. If they perform dramatically less well than they have historically, we are likely to end up with households with significantly lower levels of retirement wealth than previous generations of retirees. Of course, it is hard to know how a more traditional defined-benefit system would perform if equity markets generated weak returns for a prolonged period, since this would place heavy demands for plan contributions on the sponsoring firms.

One of the challenges that the shift toward the 401(k) model places on households is the need to become more educated about the financial decisions that they face. It places a responsibility on both public policymakers and firms' human resource departments to find relatively straightforward heuristics that will help people who in most cases don't really want to know the details of financial engineering.

Region: What kinds of heuristics would be useful in this context?

Poterba: Brigitte Madrian, David Laibson and their collaborators have done research on behavioral economics in the context of retirement and have found that many of the investment decisions people make are influenced by factors in the workplace. One of the best documented facts is what happens when a firm shifts from having a voluntary participation 401(k) plan where, when a worker is hired, he or she has to check a box and say, “Yes, I'd like to join the 401(k) plan and contribute X percent of my salary to this plan” to an “opt-out” plan in which the firm's hiring forms say, “We have a 401(k) plan. You will be automatically enrolled, and the firm will contribute 5 percent of your salary to your account.”

Region: Unless you opt out.

Poterba: Right. You have to check a box to say “no contribution.” Neoclassical economists would say the voluntary participation and the opt-out settings are identical. The budget sets, the returns, everything else is identical in these two problems, so we would expect households to make the same choices. In fact, however, participation in “opt-out” 401(k) plans is sometimes 40 percentage points higher than participation in voluntary participation plans.

Region: That much!?

Poterba: It's a huge difference. The effect tends to slowly damp out over time. The effects are largest in the first year or so when people are hired. Even in a voluntary program, people who have been with the firm longer do tend to migrate into the 401(k) plan over time, but even five years after workers are hired, there are still some effects of the automatic enrollment.

What the evidence suggests is that there are ways to affect participation in defined-contribution plans. I don't think the ways necessarily have to come from behavioral economics. Standard price-based approaches, such as matching contributions to plans, also work in increasing 401(k) participation and contribution rates.

Region: You've looked at life-cycle allocation strategies too.

Poterba: We've looked at how people might allocate their 401(k) savings over the course of their lives. The rise of life-cycle funds is a good example of how the financial services sector and retirement planners are trying to find ways of making this simpler for households and giving them ways to basically put the retirement saving process on autopilot. The designers of these funds are trying to recognize that many households do not want to think about financial decisions and are offering them ways to reduce the potential costs of financial inertia.

INSURANCE PRICING

Region: You've developed a significant body of work on asymmetric information in insurance markets, much of it with Amy Finklestein. In a recent paper with Amy and Casey Rothschild, “Redistribution by Insurance Market Regulation,” you estimate the efficiency costs and distributive impact of regulations that prohibit insurers from looking at buyer characteristics in determining prices. Are the cost and impact quantitatively significant? In an age when genetic testing is growing ever more sophisticated, what is the policy import of such findings?

Poterba: I am fascinated by insurance markets and the contracts that are available to individuals. This strikes me as an important and somewhat understudied area. My work with Amy and Casey tries to understand what happens when regulations preclude insurance companies from using some information to set insurance prices.

There are many examples of such regulations. Many states limit the data that firms can use to price automobile insurance. We consider the market for retirement annuities. In the United States, a firm cannot offer different pension payouts to men and women with the same salary history and years of service, retiring at the same age, even though life expectancy for women is several years longer than that for men at typical retirement ages.

In most settings, a ban on using some information to price insurance transfers resources toward those whom this information would show to be high-risk insurance buyers. In the market for annuities, someone who is expected to live a long time is more expensive to insure than someone who is unhealthy and has a high mortality risk. An insurance company could offer to pay higher monthly benefits to those who are ill or infirm if it could identify them. Sometimes insurance regulations make this difficult or impossible and therefore represent a transfer from one mortality risk group to another.

One of the intriguing questions is the extent to which insurance companies can induce policy buyers to reveal something about their underlying mortality type through the creative design of insurance policies. In Britain, insurers offer both inflation-indexed and nominal annuities. The households who buy the inflation-indexed products, which deliver more of their value at advanced ages than nominal products, tend to live longer than those who buy nominal annuities.  This enables insurers to partly distinguish their client base. The extent to which such distinctions can be made is likely to vary across markets and settings.

NBER

Region: Let me ask you a last question, if I may, about the NBER. You're about to become president and CEO, stepping into the shoes of Martin Feldstein, who held the position for 30 years. Can you tell us your thoughts about directions that economic research should take in coming decades and where you plan to steer the Bureau?

Poterba: Let me start by saying it is an incredible honor and a humbling opportunity to be asked to lead an organization which has had such an enormous impact on the course of empirical research within the economics profession. It's an exciting opportunity and one I'm looking forward to.

The NBER under Marty has been a great place for economists from different universities, sometimes from different subfields within the field of economics, to come together for discussion and collaboration. The topics have ranged widely, and they have been of broad interest to economic policy analysts whether they're in academe, government or business. I hope that the NBER will continue to deliver top-quality research that will be of general interest and that we'll manage to respond nimbly to the interesting economic developments of the day. One of the NBER's great strengths is its ability to bring a whole range of economic researchers to bear on important questions as they emerge.

I hope to follow an opportunistic strategy in directing research. Sometimes this involves looking into the crystal ball and identifying issues and questions that are likely to become more important going forward. But other times it involves looking in the rearview mirror and saying, “What's just happened that's really interesting? Should we look more deeply into this?”

I would expect, for example, in the very near term I will encourage research on the role of risk in financial markets, the interplay between regulatory structure and risk-bearing by financial institutions, and the interplay between the financial services sector and the broader real economy. The economics profession needs to devote significant effort to understanding what happened during the financial market gyrations of late 2007 and 2008, to modeling the linkages between different parts of the financial sector and to explaining why contagion spread from one market to another in the way it did.

Part of what's important here is to make sure that policy analysts and researchers in universities are brought up to speed and learn what was happening in the financial markets so they're able to think cogently about the episode we've been through and focus their research on the right issues.

Once we've got that knowledge base, I think the next question is “what are the lessons?” as we try to think about the potential consequences of different regulatory structures. The NBER does not make policy recommendations. It tries to identify the consequences of policies, to think through “if you do this, then this might happen” without saying whether a particular policy is a good or a bad idea.

Region: Thanks so much for your time.

—Douglas Clement
Interview conducted April 1, 2008.

Eis abaixo o que foi noticiado no http://www.allfacebook.com/2008/06/facebook-has-115-million-people/.

============
Facebook Has 115 Million People?
Posted by Nick O'Neill on June 13th, 2008 1:08 AM

Mike Arrington has published Comscore’s most recent numbers for Facebook’s traffic and last month Facebook attracted 115 million visitors. MySpace attracted the same amount. At least that’s what Comscore and Techcrunch are now reporting. How many users does Facebook say they have? Over 80 million. That means 35 million visitors to Facebook last month do not have accounts.

If you take a look at Alexa’s chart of Facebook versus MySpace traffic (as pictured below), Facebook had already surpassed MySpace in traffic. So what’s the real story behind these conflicting numbers? Well, one rationale is that Facebook is purposely understating their user statistics which would make a lot of sense.

Currently Facebook claims that they have around 80 million “active users” which means that they “returned to the site in the last 30 days.” The wording of that phrase could be misleading though. Theoretically there could be 80 million that returned and 35 million that registered last month alone. That seems a little ridiculous though. Given that Facebook is attracting at least 250,000 new users a day we know that at least 7.5 million people registered for the site last month alone.

That would leave another 27.5 million visiting the site via links around the web. This is definitely possible but if it’s true, that means that Facebook has a 21 percent conversion rate of new visitors into new users which is an impressive number. It also means that Facebook is now beginning to rely increasingly on search traffic to generate new users registrations. Whatever the case, Facebook continues to grow extremely fast and may now be the largest social network in the world.

===================

June 05, 2008

Bits, Bands and Books

By Paul Krugman
 
Published: June 6, 2008

Do you remember what it was like back in the old days when we had a New Economy? In the 1990s, jobs were abundant, oil was cheap and information technology was about to change everything.

Then the technology bubble popped. Many highly touted New Economy companies, it turned out, were better at promoting their images than at making money — although some of them did pioneer new forms of accounting fraud. After that came the oil shock and the food shock, grim reminders that we’re still living in a material world.

So much, then, for the digital revolution? Not so fast. The predictions of ’90s technology gurus are coming t