viernes, 2 de agosto de 2013

Usando Blogs en Economía


Using Blogs in Economics

Contact: Paul Ayres, Intute Social Sciences, University of Bristol and Bhagesh Sachania, The Economics Network, University of Bristol
Updated version published February 2009, published in CHEER journal Volume 20, pages 32-37, ISSN 1358-5363

1. Introduction

" 'I certainly have not found a comparable way to get my ideas out. It allows me to have a voice I would not otherwise get,' Mr [Brad] Setser says. Blogs have enabled economists to turn their microphones into megaphones." -"The invisible hand on the keyboard", The Economist, 3 August 2006
So what is this thing called blogging and why is it important? While arguments may rage over the precise definition of blogging, a blog is in essence an online diary style website. Short articles are posted in chronological order, with the most recent one at the top of the page. Simple software enables writers to fill in a form, press a button and update their website, producing quick and easy publishing on the web without the need for technical skills. The Economist has become so taken by the concept, that it has a suite of blogs of its own.
What is the case for blogging among the economics community? One of the most famous blogging economists, Brad DeLong of the University of California at Berkeley, says that blogging gives him access to an "invisible college" of people who will react to his opinions, point him to more interesting things, help him to raise the level of debate on economic issues and bring it to a mass audience. He neatly sums up blogging as "turbo charging of the public sphere of information and debate", which he hopes will make him smarter and more productive.
Blogs do this by being interactive. This takes many forms including: providing links to other websites, papers or blogs; allowing readers to comment on articles; via acknowledgements to other bloggers for leads to interesting pieces of news; or by critiquing each others writing, producing a network of links, relationships and interactions across the web.
Blogs have been in existence since the late 1990s according to blog pioneer Rebecca Blood, but it took another few years for blogs to go mainstream, with the US Presidential election of 2004 seeing them start to be used as a major source of online news. The vast majority of blogs are written by girls in their teenage years or by males in their 20's, and they write about their daily lives and interests. Blogs behave in accordance with the "long tail" theory whereby a small number of blogs enjoy a large amount of influence, which has led to their increasing prominence in search engine results and readership.
How do you take the first steps into this brave new world of blogging? Hopefully, this guide will provide some useful pointers. It will start by taking you through the mechanics of blogging, choosing appropriate software and offer some advice on how to start writing, as well as highlighting, the potential pitfalls of sharing your thoughts with the world online. Finally we will focus on specific uses of blogs in economics and some case studies of how they are used in teaching, before looking at the future of blogs and blogging as a developing technology.

References

2. Software options

Once you have decided to start writing a blog, how do you go about it? You'll need access to some blogging software, so the key questions you need to ask yourself are:
  • Do you have technical support available to help you?
  • Do you want to decide how the blog looks yourself?
  • Do you have specific needs? For example, to support multiple authors, enable you to add categories or password protect the blog
There are three main options in terms of setting up a blog:

1. Hosted solutions

Hosted software is where a company has set up blogging software for you on the Internet, enabling you to sign up for an account, log in to the system, and start blogging straight away. There is a large range of hosted solutions out there, which vary greatly in terms of quality, features and whether you wish to pay for them.
The key advantage of a hosted solution is that you do not need any technical skills or intervention to start blogging. This means that you can get writing immediately and it is a good way to introduce yourself to how blogs work and the mechanics of posting articles and receiving comments.
You will be restricted in terms of the look and feel of the blog - usually in the form of templates provided by the company. You may also be restricted in terms of the functionality a particular blogging software package may provide - whether you can add multiple authors, assign categories to posts or set up more than one blog.
Three of the most popular hosted blogging solutions are:

Blogger

Blogger is free and owned by Google - all you need to get started is a valid email address and to register at their website.
Professor Greg Mankiw of Harvard University, uses Blogger for his website.

WordPress.com

A hosted version of the open source WordPress blogging software (see below), that is free to use, but some extra features like using your own design template or getting a personalised web address can be paid for.
The Everyday Economist uses WordPress.com

TypePad

TypePad is the hosted version of the Movable Type blogging software (see below) that is produced by the company Six Apart. It has a range of pay monthly cost options, with the cheapest offering one blog produced by a single author, ranging to a package offering multiple authors and an unlimited number of blogs.
The Cafe Hayek blog uses the Typepad blogging platform.

2. Installed software

This option will require that you have some blogging software, access to a web server on which to host it and the technical skills to manage the web server / blogging software or the time and skills of someone who does. The intricacies of web server maintenance and the various technical skills needed to run them are outside the scope of this article, but your best option is to consult within your institution as to what support is available from your department or information service.
The advantages of this option are that you have control over the look and feel of the blog, can add extra authors or blogs easily and can add extra features yourself. However, you may be limited by the license terms of the software you have downloaded, be dependent on the technical skills of someone else or be restrained by your institution as to the types of software you can install.
Two of the most popular blogging software packages are:

WordPress

WordPress is an open source blogging platform. It is freely available and has a dedicated community of developers working on new features that can be easily integrated into the software, via plugins or widgets that add extra functionality. The design of the blog can be changed at the click of the mouse, as WordPress keeps design and content elements separate, and it does this by using themes that can be downloaded from the Internet.
The Freakonomics blog of Steven D. Levitt and Stephen J. Dubner uses WordPress

Movable Type

Movable Type is a proprietary blogging platform developed by the company Six Apart. Originally freely available, Movable Type now has a range of low cost pricing options allowing you to download the software. While a free version is available for a single user in an educational setting, if you wish to create multiple blogs, allow multiple authors or provide the tool to your students, a license fee will be payable.

3. Institutional options

Your institution may already provide a blogging platform that you can have access to. If your institution has a Virtual Learning Environment (VLE) such as Blackboard, WebCT or Moodle, these VLEs can come with a blogging module already built in. This has the advantage of being integrated with an existing system which you and your students may already be familiar with, but the functionality offered within these systems is usually less than you would receive when using a piece of dedicated blogging software.
Another possibility is that your institution offers a dedicated blogging platform. This is not widespread in the UK at present, but the example of the University of Warwick has shown what can be possible. It may be worth asking your library, computing or information service whether they have a recommended blogging product they support or whether they have plans to implement one in the future.

Find out more

You can compare some of the options detailed above and a few more, using the Blog Software Comparison Chart provided by the Online Journalism Review.

3. Writing and managing content

Whichever software option you choose, most blogs will have a similar set of features. This part of the guide will tell you about the mechanics of blogging, i.e. how to blog, and some pointers on what you might like to write, i.e. what to blog.

How to Blog

Like many niche activities, blogging has its own terminology, which may seem off putting to those new to it. A typical blog will have some or all of the following characteristics:

Posts

Posts are the individual articles that make up the blog. They have a title and main body of text, which you produce simply by filling in a form in your blogging software and pressing a button to submit or publish the article on your blog.

Comments

Most blogging software allows readers to comment on posts. Readers can suggest corrections, clarify information or simply add their opinion on the post. Entries are normally time stamped and include the author's name and other details. Another useful feature is that they can also be threaded allowing readers to comment on comments.

Blogroll

A blogroll of links is another key aspect of blogs. It usually directs a reader to interesting links that relate to the theme of the blog; and link to fellow bloggers. This provides the reader with an opportunity to discover new and interesting sites. The blogroll usually appears down the side of the blog, on every page of the site and is managed using the blogging software.

Categories (tags/ subjects that the entry discusses)

Categories enable posts to be organised by subjects (or tags) and help readers to find information about a specific topic quickly and easily. Individual posts can be assigned into several categories, often just by ticking a box when writing them.

Archives

Archives are links to chronological collections of posts, enabling a reader to go back through time and see what has been posted on this blog in the past. They can be arranged by day, week or month, depending on how frequently the site is updated.

What to Blog

Blogging, like other forms of online communication (e.g. email) has its own set of social conventions. It's important to be aware of the following when writing or commenting on blogs:

Think about your audience

Potentially anything you post can read by a global audience. And a post might be archived or cached and therefore impossible to remove. Think carefully about posting contentious or provocative material, it may spark a rise in readership, but it could make you unpopular online.

Clear communication

Perfect prose isn't necessary but you should aim for clear, simple language. Try to avoid non-standard abbreviations and too much jargon.

Credit sources and respect copyright

Avoid quoting large extracts from a source without the consent of the copyright holder. Credit original authors appropriately, include a link, sometimes called a HatTip, to other bloggers if you are discussing their views.

Check the validity and accuracy of your information

Don't always take online information at face value, particularly if it deals with contentious issues. Check facts against more than one authoritative source.

Correct mistakes and post updates

Mistakes are inevitable. You might discover them yourself or readers may highlight them. Correcting them adds credibility to your blog and makes it look more professional. If possible leave the original entry intact and make corrections by adding extra material. Try to avoid rewriting or deleting posts, since others may rely on them via links.

Don't make 'spam' comments

Some people may regard simply posting a link or simple statement without any relevant information as spam. Make sure your comments are meaningful and relevant. Make sure you delete any spam comments on your own blog.

Identify yourself and be available

Try and ensure that your readers can contact you if necessary. If you do post comments on other blogs, it's good practice to identify yourself and provide information about how you can be contacted (usually an email address). Unattributed comments might be considered as spam (see above). If you don't want a comment to be attributed to you then you should consider whether you really want to make it.

References

4. Risks

Blogging as a form of academic publishing does come with its own risks, which you should consider fully before committing to writing online.

Effect on your job, or your next job

People have lost their job as a consequence of what they have written on their blogs, even if they have taken care not to refer directly to their employers and have blogged under pseudonyms. While in academia there is some conjecture that researchers in the United States have been refused tenure as a consequence of their blogging activity. You should bear in mind that your current or any prospective future employer may find your blog online and take it into account when assessing your employability.

Relationship with your institution

If your blog is set up within a Virtual Learning Environment or an institutional blog hosting service, it will be clear that you will be writing as a member of your university or college. This means that you will be subject to the relevant code of conduct or appropriate use of computing resources policy for your institution. While few institutions have a policy specifically to cover blogging, should you feel restricted by any limits these policies place upon your writing, you may wish to blog outside the confines of the IT systems provided for you by your institution.

Intellectual property

A blog may be a useful forum for floating new ideas, theories or areas of research. However, you will not have the same degree of control you have with a peer reviewed journal and will not be entitled to the same degree of credit a formal publication bestows upon you. Similarly, it is not clear whether ideas expressed or published on a blog, are covered by the same rules and regulations as a book, article or other output produced while you are an employee of an institution or being funded by a research council grant.

Blog ethics

Blogs come with their own set of social rules or blog etiquette. For example, Internet sources cited or quoted in your posts should be acknowledged with a reciprocal link to the websites in question. Retrospectively editing a blog entry is a tricky area, as this may make some of the comments users have posted to your initial article look out of place. Consider using strikeout formatting (like this) to show edits or make additions to the bottom of a post to show how your views may have evolved.

Comments

The default setting for most blogs is to allow comments from readers. While this can lead to fruitful interactions, debate and links to useful further resources, like any open form of conversation, it can lead to inappropriate or offensive comments and it can be exploited by Internet marketers as a way of spamming your blog. You may wish to investigate the security options in your blogging software to make readers register before posting a comment to your blog, or hold comments in a queue for your approval before they are published.

Other legal issues

The Electronic Frontier Foundation has produced a Legal Guide For Bloggers, which looks at some of the key legal issues that affect blogs. However, it should be remembered that this has been written from an American perspective and therefore some of the advice would not necessarily apply elsewhere. Also, this is an area of law that is developing all the time, so what may be true today could be changed by a new piece of legislation in the near future.

References

5. Uses for Economics

Henry Farrell is an Assistant Professor at the Department of Political Science and the Elliott School of International Affairs of George Washington University, and he is also one a group of scholars who contribute to the Crooked Timber blog. He has identified five uses of blogs within the classroom:
  • replacing standard class web pages
  • professor-written blogs which cover interesting developments that relate to the theme of the course
  • organization of in-class discussion
  • organization of intensive seminars where students have to provide weekly summaries of the readings
  • requiring students to write their own blogs as part of their grade
Stephen Downes, the Canadian learning technologist has expanded on these uses in an article for the EDUCAUSE Review.
But what is the potential for blogging in Economics teaching? Steve Greenlaw of the University of Mary Washington explores the broader role of technology in teaching via his blog Pedablogy: musings on art and craft of teaching.
A series of specific examples are presented below:

Replacing standard class web pages

Have you ever struggled to learn HTML and craft your own course website? It can be a valuable aid, enabling you to post suggested readings, set tasks / exercises / assignments or just remind students when they are expected to turn up for lectures. Using a blog can let you concentrate on adding the information, rather than having to learn additional IT skills.
This is something that Tim Kochanski at the University of Alaska Southeast successfully trialled. He created a blog as part of a four-week class on introductory economics. He was keen to investigate a low cost alternative to using his institutional course management system (Blackboard). He found that the journal format of a blog, as well as other features provided a valuable resource to help guide his students through a semester of economics. A detailed case study is available in the Reflections on Teaching section of the Economics Network website.

Professor-written blogs which cover interesting developments that relate to the theme of the course

You may already be familiar with the Internet and often come across websites that may be relevant to your teaching. Using a blog can enable you to bring these resources together, comment on them and organise them in a manner which may be helpful to your students. You may want to try and make the theoretical aspects of what you are teaching meaningful in a broader context, by relating them to items that are in the news or of topical interest.
The Tutor2u website is a good example of this. It offers a range of subject specific blogs. Geoff Riley (Head of Economics at Eton College) maintains the 'Economics in the News' Blog and provides a regular commentary on economics issues and trends. Although the primary target audience is secondary school students some of the resources could be useful in first year undergraduate courses on introductory economics.

Organization of in-class discussion or seminars

You may have experimented in the past with discussion boards and found that they can produce useful dialogues. Opening up this process with a group blog can enable students to post items, comment on them, get to know each other and even answer their own questions. You may get contributions from students who find face-to-face discussion difficult, but who find online communication more suited to their learning style.
Professor David Tufte manages an 'Economics Classes Blog' at Southern Utah University:
His students regularly post items of interest and ask thought provoking questions. Professor Tufte then invites his students to offer their feedback/analysis on that particular economics issue, by placing comments on the blog, where he occasionally offers comments of his own to relate the items to ideas he has mentioned in class.

6. Future of blogging

The rise of blogs has been meteoric over the past few years, but blogging is continuing to develop as a technology, as a way of communicating and as a way of interacting with others online. So what does the future hold for the world of blogs?

Different ways of blogging

Bloggers are finding different ways of passing on their thoughts to the rest of the world, other than just using text. Keen writers can send entries using their mobile phones, produce blogs that are made up solely of photographs or use a blog as a distribution method for audio (podcasts) or video (vlogging).
In economics, innovative sites such as VoxEU and Economics in Action, are already using the web to distribute audio interviews with researchers and to promote the study of economics to new audiences.
Research institutes, like the Library of Economics and Liberty are taking advantage of this opportunity to promote their work via a different medium, at their EconTalk website.

Keeping track of the blogosphere

The blogosphere is still growing, which makes it more and more difficult to keep track of good writing, new authors and interesting papers. Fortunately specialist search tools have emerged which allow you to focus just on blogs, so you can see what is being talked about as it happens.
Technorati is a search engine that has tracked over 130 million blogs worldwide and allows you to set up watchlists that search for new items on specified topics.
The main Internet search engines, also have services that monitor blogs such as Google Blog Search. Perhaps the easiest way of seeing what blogging economists are saying is to visit the Economics Roundtable, a site which aggregates over 120 of the leading economics commentators into one site. Palgrave EconBlog also collates posts from a range of Economics blogs.
These searching and alerting services rely on a technology called RSS or Really Simple Syndication, enabling users to subscribe for free to a blog or other information service, so that they are automatically updated when new material is published. Try a web based service like Bloglines or Google Reader, so that you can subscribe to your favourite blogs, get tables of contents from newly published journals and news stories from The Economist all in one place. It is spam and advert free, and it saves you time by delivering the information directly to you.

Here to stay

While some may be critical of blogging as a passing fad, it is here to stay, even if in the future blogs will be referred to in the same way as any other type of online source. Innovators such as Stephen Kinsella are already using blogs to support their courses with a full range of Web 2.0 add-ons such as videos, embeddable slideshows of lecture presentations and the latest links from social bookmarking websites. The fact that blogs offer quick and easy web publishing, with little or no need for technical skills, means that many people will continue to choose blogging as a key way of expressing themselves online.

References

7. Conclusion

"I'll publish, right or wrong" (Byron)
This article has outlined the possibilities that blogs offer in terms of teaching, personal and professional development and engaging with a global audience. The chance to take advantage of an "invisible college" of fellow scholars, informed readers and actively engaged students, means that blogs can provide a whole new dimension of interaction in helping people make sense of economic issues. Using blogs as part of the classroom experience can take the technical strain out of producing a website and allow you to concentrate on writing, discussing and teaching online.
We hope that this short guide has made you aware of the mechanics of blogging and some of the potential pitfalls, given you some ideas as to how you could use them for economics teaching and opened your eyes to some of the future possibilities that blogging as a technology can offer. If you successfully build blogging into your normal work routine, you may soon find that blogging starts to take over your life and that it is increasingly difficult to live without your virtual notebook.
The freedom that blogs bring to the voiceless in politically repressive regimes is a good example of how blogs enable anyone to publish anything online. The chance to hear from alternative viewpoints, to publish ideas that may not get an airing elsewhere, to sidestep the mainstream media and to experience quality writing freely and openly, means blogs can help produce a genuine free market in ideas.
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jueves, 1 de agosto de 2013

La política monetaria de Larry Summers

We Don't Know Where Larry Summers Stands On The Most Important Issue Facing The Fed





Monetary policy.
That's the massive issue on which we don't really know the views of Larry Summers, who is one of the leading candidates to replace Ben Bernanke as Chairman of the Federal Reserve. And since monetary policy is pretty much the Fed's whole thing, his lack of clear views are a pretty big deal.
This is a point that Matthew Yglesias got at yesterday, in arguing that it would probably be helpful for Summers to establish a position on some of the big monetary policy questions of the day to further his chances of being nominated by Obama.
Right now there's this idea that Yellen is "dovish" and that Summers is "hawkish" but this is really a gross oversimplification.
Pretty much the only thing we have to go on, with Summers, are comments about how he hasn't regarded QE to be particularly effective. But that doesn't necessarily imply dovishness. Even the Fed seems to be losing faith in the power of QE, as it shifts its stimulative efforts more towards guidance about keeping future rates low. If Summers is skeptical about QE, but, say, a fan of Evan's Rule (which promises to keep rates low until a certain unemployment threshold is hit) then perhaps Summers could be considered more dovish. We just don't really know.
As an aside, calling Janet Yellen "dovish" is also an oversimplification. For one thing, she's been correct in her assessment of the economy (predicting subdued inflation and weak growth), so the dovish stance hasn't necessarily been philosophical--just correct. It's also true that in the 90s she was battling with Alan Greenspan, warning about inflation risks, so she hasn't spent her whole career just obsessing about one side of the Fed's dual mandate.
The important thing about Janet Yellen isn't just that she believes in more Fed action, but that she's at the forefront of discussions about monetary policy technology — the new tools that monetary policy observers have been talking about and honing since the crisis. Back in January, Goldman Sachs argued that Yellen was basically a supporter of Nominal GDP targeting, which is one of the hottest ideas in monetary policy. Yellen hasn't addressed the idea in name, but she's a serious, leading edge monetary policy theorist.
A lot of the discussion about who will lead the Fed has either been about non-monetary policy questions (who's close with Obama, who's got the temerity for the job, etc.) and the part about monetary policy itself has been superficial.
But it seems clear that with Larry Summers, we really don't know that much about where he stands on the single most important aspect of the Fed's role.


Business Insider 





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¿Cuanto paga ser abogado en USA?

Is Law School a Good Deal After All?

A fascinating new paper argues that a J.D. is worth $1 million over the course of a career, and that the recession hasn't dampened its value. But don't go racing for your LSAT prep book just yet.
The Atlantic


Wikimedia Commons/Jordan Weissmann

Ever since the Great Recession sucked the air out of the legal industry, an extremely vocal group of writers -- myself included -- has been trying to warn pretty much any 20-something with an Internet connection to think twice about going to law school. The job market for recent grads has been murder. And there's an abiding sense that the business model which sustained many big corporate firms, the ones that offer those plum $160,000-a-year jobs of lore, isin danger of becoming obsolete, if it hasn't already. 
So it was with both great skepticism and a bit of personal trepidation that I cracked open "The Economic Value of a Law Degree," a new draft paper by Seton Hall Law Professor Michael Simkovic and Rutgers economist Frank McIntyre. The two researchers argue that over the course of a career, your average J.D.-holder will make almost $1 million more than a similar worker with just a bachelor's degree (or about $700,000 after taxes). Even law grads on the low end of the salary scale seem to fare better than their merely college-educated peers. Crucially, the paper finds no evidence that the earnings premium has declined since the economy crashed. 
"[O]ur results suggest that attending law school is generally a better financial decision than terminating one's education with a bachelor's degree," they write. Or to put it more bluntly, the law school haters are wrong.
So, are we? Is paying $60,000 a year to learn torts, tax, and civil procedure really a great deal after all? I don't think there's neat yes or no answer to that question. But I do think law school critics need to take Simkovic and McIntyre's conclusions seriously.
But before we get into precisely why, let's talk a bit about what went into this study. Using Census data dating back to 1996, the paper compares the earnings of law school graduates -- mind you, not just practicing lawyers, but anyone with a J.D. -- at all stages of their careers to the earnings of bachelor's degree holders, while accounting for factors like academic performance, race, socio-economic background, the chance of unemployment, and gender. The comparison comes out looking like this. 
Simkovic_Lawyer_Earnings_Curve.jpg
So on average, J.D.'s have traditionally earned about $53,000 more per year than similar college-educated workers. This should shock nobody. Using some standard accounting techniques, Simkovic and McIntyre estimate that pay bump is worth about $990,000 over a lifetime, far more than the cost of tuition at any law school. 
But the post-recession critique against law schools has never been about the fate of the average J.D. Rather, the concern is about the least successful grads, the ones who find themselves jobless after commencement, or toiling at legal temp work. But Simkovic and McIntyre don't just find that law grads fare better on average. Rather, they fare better all over the salary spectrum. The paper calculates that a law grad at the 25th percentile of earners with a J.D. makes about $17,000 more per year than a college graduate at the 25th percentile of earners with just a bachelor's. The median law grad earns $32,000-a-year more than the median B.A. 
That, in turn, would make a law degree a very good investment. Assuming tuition costs $60,000 a year (the average is closer to $30,000), you can think of a J.D. as a bond that pays off about 8 percent to 10 percent for the median earner. Stocks, by comparison, pay off about 6.8 percent a year, traditionally. (Important note: If a male lawyer at the 25th percentile of earnings pays average tuition, the paper says they're still beating stocks). 
Simkovic_Rate_of_Return_JD.png
Of course, everyone knows lawyers had a great run until the financial crash. What about today's young esquires? While legal salaries have tumbled and unemployment has risen, the paper argues, based on data from the class of 2008, that lawyers seem to have essentially maintained their advantage over their less educated peers. In fact, as the economy soured, their earnings premium seemed to rise. 
Simkovic_Young_Lawyers.jpg
The economy has been terrible for everyone. But it may have been better if you had a law degree to keep you afloat. 
As we all learned thanks to a certain Excel error, it's a bit foolish to put too much stock in a single academic paper, especially one that hasn't yet been subjected to a thorough vetting. That said, having scoured through it -- and having asked the Hamilton Project's Adam Looney, who has done similar work on college graduates, for a second opinion -- Simkovic and McIntyre's paper seems to be both based on a reasonable set of economic assumptions and a very by-the-book interpretation of their numbers.* 
That said, I'm not sure young political-science majors should take this study as a green light to go rushing back to their LSAT prep books. For ease of digestion, here are my reasons in bullet-point form: 
Reason 1: The Legal Job Market Continued Deteriorating Well Past 2008So far as law-school grads go, the class of 2008 did not get the worst of the recession. There's a reason lawyers sometimes refer to graduates from 2010 and 2011 as "the lost generation." Meanwhile, the job market only showed the barest signs of a rebound for the class of 2012. So the experience of lawyers who finished their degrees before Lehman collapsed may not fully reflect the challenges faced by recent J.D.'s. And while many of those young attorneys will have years to make up some of that lost salary, economists will tell you that early unemployment or low pay can have a lasting echo throughout a worker's career. 
The question is whether the problems law graduates have faced a temporary jobs drought thanks to the recession, or if something has fundamentally changed in the industry. 
Reason 2: The Boom Times Might Be Over for GoodAs Simkovic and McIntyre note, the predictions about the imminent ruin of the legal profession "date back at least to the invention of the typewriter." But at the risk of saying this time might be different, well, this time might be different. Even as corporate profits have come roaring back, particularly at banks, demand for high-end legal services has remained soft, and firms are facing unprecedented pressure to keep costs down. Many believe corporate law is entering a lean new world, which will only get leaner as software continues to automate and slim the margins on once-profitable activities. 
The legal academy tends to dismiss the troubles facing Big Law because the vast majority of attorneys don't actually spend their lives making millions representing banks and oil companies. But according to the Census, from 2002 through 2007, the 50 largest firms were responsible for about one-third of employment growth at all law offices (in the industry the top 200 firms by revenue are generally considered large). That jobs engine, for the time being, is dead. The entire U.S. economy has recovered almost three-quarters of the jobs lost thanks to the recession, but legal services has recovered just 16 percent of its losses. Many of those missing positions may have belonged to legal secretaries and paralegals. But the slow rebound nonetheless suggests something's amiss in law-firm land. Unless government hiring rebounds with a vengeance, or jobs open up en masse thanks to retiring boomers, it's hard to see the hiring picture dramatically improving for young J.D.'s. 
Reason 3: Students From Bottom of the Bottom Schools Are Still Suffering
Even if law-school graduates on the whole do reasonably well, the law-school boom of the last decade helped spur the growth of bottom-tier institutions that now post 20 percent or higher unemployment rates among their graduating classes. Those students may not be defaulting on their hefty debts en masse -- unlike the dropouts who are most likely to default on undergraduate debt, law grads are probably better at using programs like income-based repayment to protect themselves -- they're still suffering. I don't think there's anything about Simkovic and McIntyre's study that means something shouldn't be done to fix or restrain those schools.
Of course, the market is already doing that in its own way. Thanks to anenormous drop in law-school applicants, the class of 2016 may not have to face the nightmarish hiring environment that greeted grads from the last few years. Simkovic and McIntyre's paper is compelling. But I'm not yet comfortable saying that many young Americans are missing out by saying no to law school. 
___________________________
*If there's anything that makes me uneasy about the paper's mechanics, it's that it compares the bottom quarter of law-degree holders to the bottom quarter of bachelor's-degree holders. Their analysis suggests that had they not gone to law school, most J.D.'s would make only a small premium over the average B.A. (somewhere in the range of 0-5 percent). Intuitively, that strikes me as off. But I honestly don't have a good data based reason to reject their approach at the moment. (This footnote has been clarified from an earlier version that used some imprecise language). 
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miércoles, 31 de julio de 2013

Un aspecto filosófico del consumismo: La máquina deseante

La economía de las máquinas deseantes


Por Nicolás Litvinoff | Estudinero


El término "máquinas deseantes" fue introducido por Gilles Deleuze, un brillante filósofo francés contemporáneo que vivió entre 1925 y 1995. Desde 1960 hasta su muerte, escribió numerosas obras sobre la historia de la filosofía, la política, la literatura, el cine y la pintura.

En la presente columna me tomaré el atrevimiento de realizar un paralelo entre sus ideas y la realidad económica actual, haciendo hincapié en el dinero y las finanzas personales, con la esperanza de entender cómo funciona el consumismo en su conjunto y qué podemos hacer al respecto para trazar nuestro propio destino en este campo que es quizá uno de los más importantes para determinar nuestra felicidad relacionada a lo material.
Gilles Deleuze
Analizaremos para ello algunos de sus conceptos más relevantes en función de lo que sucede hoy en día en nuestro país, con un Estado que nos induce cada vez más a gastar dinero que no tenemos en cosas que no necesitamos para agradar a personas que no nos interesan.

LAS MÁQUINAS DESEANTES
Deleuze define el deseo como un devenir vital. Para él, el deseo es la tendencia del cuerpo a unirse a lo que aumenta su potencia de acción. Todo en el universo son encuentros: buenos o malos. Experimentamos alegría al encontrar un cuerpo que se compone con el nuestro y eleva nuestra potencia, y tristeza en el encuentro de un cuerpo que descompone el nuestro y nos quita potencia. El grado de potencia cambia según cuantas sean las pasiones tristes y las pasiones alegres que vivamos. Y en eso será determinante cuán malos o buenos hayan sido los encuentros.

Las pasiones tristes acarrean pasividad y fomentan el gusto por la esclavitud. De tal manera, en el sistema capitalista actual, aquel que no trabaja de lo que le gusta suele bromear con que es un esclavo de su jefe o de los dueños de la empresa para la cual trabaja. Para aquellos que no están conformes con su trabajo, el acto cotidiano de acudir al mismo representa una pasión triste.

En ese sentido es que el filósofo afirma que será esclavo quien se abandone a la ruleta de los hechos y sucumba sin cesar a los encuentros que no le son favorables.

¿Por qué algunas personas logran tener una vida intensa, trabajar de lo que les gusta y además de ello triunfar en el campo económico? Si todos somos máquinas deseantes, podría pensarse entonces que lo que nos diferencia tiene que ver con el grado de potencia que alcanza nuestro deseo.

Pero el deseo individual, la mayoría de las veces, suele chocar con los intereses del sistema, ya que la máquina deseante (es decir, todos nosotros) es un sistema de producir deseos mientras que la máquina social es un sistema económico-político de producción.

Deleuze habla sobre flujos de deseo, mientras que David Ricardo y Karl Marx descubrieron el flujo de producción, el flujo de dinero, el flujo de mercancías; todo ello como esencia de la economía capitalista.

SOBRE CÓMO LA SOCIEDAD DE CONSUMO ESTABLECE NUESTROS FLUJOS DE DESEO

Deleuze afirma que todo lo que vemos fue fabricado por flujos de deseo. Siguiendo esta hipótesis, una sociedad no es ni más ni menos que una forma particular de organizar los flujos de deseo. Dicho en otras palabras: el modo de producción capitalista es una forma de organización de la producción deseante, que busca lograr que las máquinas deseantes deseen lo que le conviene al sistema.

En la economía argentina, la presión consumista por parte del Estado es cada vez más asfixiante, y llega incluso al punto de limitar el ahorro mediante distintos mecanismos que no tienen que ver solamente con la prohibición de comprar dólares: las tasas de interés que se paga por los medios de ahorro más populares como los plazos fijos son negativas en términos reales (es decir, si tenemos en cuenta la inflación), con lo cual el consumo aparece como la única alternativa posible.

Pero la determinación externa de nuestro deseo no baja únicamente desde el Estado, sino que también se construye desde el sector privado la noción del éxito en función de lo material (un auto 0 km, una casa más grande, ropa de marca) valiéndose de un marketing cada vez más agresivo y subliminal frente al cual la mayoría sucumbe.

Así como están cosas, pareciera que no existe una salida posible. Sin embargo, en un tono esperanzador, Deleuze introduce dos conceptos fundamentales: el de rizoma y el de las "líneas de fuga", que ampliaremos a continuación.

RIZOMAS Y LÍNEA DE FUGA COMO ESCAPE A LA DOCTRINA DEL CONSUMISMO

En primer lugar, Deleuze introduce el concepto de rizoma, que es un modelo descriptivo en el que la organización de los elementos no sigue líneas de subordinación jerárquica, sino que cualquier elemento puede afectar o incidir en cualquier otro. La noción está adoptada de la estructura de algunas plantas, cuyos brotes pueden ramificarse en cualquier punto, así como engrosarse transformándose en un bulbo o tubérculo

Esta noción del conocimiento está motivada por la intención de mostrar que la estructura convencional de las disciplinas no refleja simplemente la estructura de la naturaleza, sino que es un resultado de la distribución de poder y autoridad en el cuerpo social.

Una organización rizomática del conocimiento es un método para ejercer la resistencia contra un modelo jerárquico o una estructura social opresiva.

Deleuze busca producir un quiebre al afirmar que un individuo debe negarse a utilizar las piezas que la sociedad le entrega para que arme la imagen que ella quiere mirar. Para ello, la línea de fuga tiene que ver con pensar, que no es ni más ni menos que ocupar la brecha que se abre entre lo que se dice y lo que se ve, pues nunca hay una coincidencia entre una cosa y otra.

Y pensar, a su vez, tiene que ver con cuestionar: ¿Quiero realmente pasarme la vida trabajando en proyectos ajenos, que disminuyen mi potencia, o es tiempo de encauzar mi deseo hacia mis propios intereses? ¿Un coche nuevo, una casa más grande o cualquier otro objeto material son realmente objetivos que yo deseo, o estoy siendo una pieza más del puzzle del consumismo global?

El filósofo afirma que las personas somos parte de este mundo en el cual experimentamos lo intolerable. La salida es creer no en otro mundo, sino en nuestro vínculo con el mundo: en la vida, el amor, el deseo..
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La fórmula que hizo un desastre en Wall Street

Recipe for Disaster: The Formula That Killed Wall Street
By Felix Salmon
Wired

In the mid-'80s, Wall Street turned to the quants—brainy financial engineers—to invent new ways to boost profits. Their methods for minting money worked brilliantly... until one of them devastated the global economy. Photo: Jim Krantz/Gallery Stock



Photo: Jim Krantz/Gallery Stock
Road Map for Financial Recovery: Radical Transparency Now!
A year ago, it was hardly unthinkable that a math wizard like David X. Li might someday earn a Nobel Prize. After all, financial economists—even Wall Street quants—have received the Nobel in economics before, and Li's work on measuring risk has had more impact, more quickly, than previous Nobel Prize-winning contributions to the field. Today, though, as dazed bankers, politicians, regulators, and investors survey the wreckage of the biggest financial meltdown since the Great Depression, Li is probably thankful he still has a job in finance at all. Not that his achievement should be dismissed. He took a notoriously tough nut—determining correlation, or how seemingly disparate events are related—and cracked it wide open with a simple and elegant mathematical formula, one that would become ubiquitous in finance worldwide.
For five years, Li's formula, known as a Gaussian copula function, looked like an unambiguously positive breakthrough, a piece of financial technology that allowed hugely complex risks to be modeled with more ease and accuracy than ever before. With his brilliant spark of mathematical legerdemain, Li made it possible for traders to sell vast quantities of new securities, expanding financial markets to unimaginable levels.
His method was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored.
Then the model fell apart. Cracks started appearing early on, when financial markets began behaving in ways that users of Li's formula hadn't expected. The cracks became full-fledged canyons in 2008—when ruptures in the financial system's foundation swallowed up trillions of dollars and put the survival of the global banking system in serious peril.
David X. Li, it's safe to say, won't be getting that Nobel anytime soon. One result of the collapse has been the end of financial economics as something to be celebrated rather than feared. And Li's Gaussian copula formula will go down in history as instrumental in causing the unfathomable losses that brought the world financial system to its knees.
How could one formula pack such a devastating punch? The answer lies in the bond market, the multitrillion-dollar system that allows pension funds, insurance companies, and hedge funds to lend trillions of dollars to companies, countries, and home buyers.
A bond, of course, is just an IOU, a promise to pay back money with interest by certain dates. If a company—say, IBM—borrows money by issuing a bond, investors will look very closely over its accounts to make sure it has the wherewithal to repay them. The higher the perceived risk—and there's always some risk—the higher the interest rate the bond must carry.
Bond investors are very comfortable with the concept of probability. If there's a 1 percent chance of default but they get an extra two percentage points in interest, they're ahead of the game overall—like a casino, which is happy to lose big sums every so often in return for profits most of the time.
Bond investors also invest in pools of hundreds or even thousands of mortgages. The potential sums involved are staggering: Americans now owe more than $11 trillion on their homes. But mortgage pools are messier than most bonds. There's no guaranteed interest rate, since the amount of money homeowners collectively pay back every month is a function of how many have refinanced and how many have defaulted. There's certainly no fixed maturity date: Money shows up in irregular chunks as people pay down their mortgages at unpredictable times—for instance, when they decide to sell their house. And most problematic, there's no easy way to assign a single probability to the chance of default.
Wall Street solved many of these problems through a process called tranching, which divides a pool and allows for the creation of safe bonds with a risk-free triple-A credit rating. Investors in the first tranche, or slice, are first in line to be paid off. Those next in line might get only a double-A credit rating on their tranche of bonds but will be able to charge a higher interest rate for bearing the slightly higher chance of default. And so on.

"...correlation is charlatanism"
Photo: AP photo/Richard Drew
The reason that ratings agencies and investors felt so safe with the triple-A tranches was that they believed there was no way hundreds of homeowners would all default on their loans at the same time. One person might lose his job, another might fall ill. But those are individual calamities that don't affect the mortgage pool much as a whole: Everybody else is still making their payments on time.
But not all calamities are individual, and tranching still hadn't solved all the problems of mortgage-pool risk. Some things, like falling house prices, affect a large number of people at once. If home values in your neighborhood decline and you lose some of your equity, there's a good chance your neighbors will lose theirs as well. If, as a result, you default on your mortgage, there's a higher probability they will default, too. That's called correlation—the degree to which one variable moves in line with another—and measuring it is an important part of determining how risky mortgage bonds are.
Investors like risk, as long as they can price it. What they hate is uncertainty—not knowing how big the risk is. As a result, bond investors and mortgage lenders desperately want to be able to measure, model, and price correlation. Before quantitative models came along, the only time investors were comfortable putting their money in mortgage pools was when there was no risk whatsoever—in other words, when the bonds were guaranteed implicitly by the federal government through Fannie Mae or Freddie Mac.
Yet during the '90s, as global markets expanded, there were trillions of new dollars waiting to be put to use lending to borrowers around the world—not just mortgage seekers but also corporations and car buyers and anybody running a balance on their credit card—if only investors could put a number on the correlations between them. The problem is excruciatingly hard, especially when you're talking about thousands of moving parts. Whoever solved it would earn the eternal gratitude of Wall Street and quite possibly the attention of the Nobel committee as well.
To understand the mathematics of correlation better, consider something simple, like a kid in an elementary school: Let's call her Alice. The probability that her parents will get divorced this year is about 5 percent, the risk of her getting head lice is about 5 percent, the chance of her seeing a teacher slip on a banana peel is about 5 percent, and the likelihood of her winning the class spelling bee is about 5 percent. If investors were trading securities based on the chances of those things happening only to Alice, they would all trade at more or less the same price.
But something important happens when we start looking at two kids rather than one—not just Alice but also the girl she sits next to, Britney. If Britney's parents get divorced, what are the chances that Alice's parents will get divorced, too? Still about 5 percent: The correlation there is close to zero. But if Britney gets head lice, the chance that Alice will get head lice is much higher, about 50 percent—which means the correlation is probably up in the 0.5 range. If Britney sees a teacher slip on a banana peel, what is the chance that Alice will see it, too? Very high indeed, since they sit next to each other: It could be as much as 95 percent, which means the correlation is close to 1. And if Britney wins the class spelling bee, the chance of Alice winning it is zero, which means the correlation is negative: -1.
If investors were trading securities based on the chances of these things happening to both Alice andBritney, the prices would be all over the place, because the correlations vary so much.
But it's a very inexact science. Just measuring those initial 5 percent probabilities involves collecting lots of disparate data points and subjecting them to all manner of statistical and error analysis. Trying to assess the conditional probabilities—the chance that Alice will get head lice if Britney gets head lice—is an order of magnitude harder, since those data points are much rarer. As a result of the scarcity of historical data, the errors there are likely to be much greater.
In the world of mortgages, it's harder still. What is the chance that any given home will decline in value? You can look at the past history of housing prices to give you an idea, but surely the nation's macroeconomic situation also plays an important role. And what is the chance that if a home in one state falls in value, a similar home in another state will fall in value as well?


Here's what killed your 401(k)   David X. Li's Gaussian copula function as first published in 2000. Investors exploited it as a quick—and fatally flawed—way to assess risk. A shorter version appears on this month's cover of Wired. 

Probability

Specifically, this is a joint default probability—the likelihood that any two members of the pool (A and B) will both default. It's what investors are looking for, and the rest of the formula provides the answer.

Survival times

The amount of time between now and when A and B can be expected to default. Li took the idea from a concept in actuarial science that charts what happens to someone's life expectancy when their spouse dies.

Equality

A dangerously precise concept, since it leaves no room for error. Clean equations help both quants and their managers forget that the real world contains a surprising amount of uncertainty, fuzziness, and precariousness.

Copula

This couples (hence the Latinate term copula) the individual probabilities associated with A and B to come up with a single number. Errors here massively increase the risk of the whole equation blowing up.

Distribution functions

The probabilities of how long A and B are likely to survive. Since these are not certainties, they can be dangerous: Small miscalculations may leave you facing much more risk than the formula indicates.

Gamma

The all-powerful correlation parameter, which reduces correlation to a single constant—something that should be highly improbable, if not impossible. This is the magic number that made Li's copula function irresistible.


Enter Li, a star mathematician who grew up in rural China in the 1960s. He excelled in school and eventually got a master's degree in economics from Nankai University before leaving the country to get an MBA from Laval University in Quebec. That was followed by two more degrees: a master's in actuarial science and a PhD in statistics, both from Ontario's University of Waterloo. In 1997 he landed at Canadian Imperial Bank of Commerce, where his financial career began in earnest; he later moved to Barclays Capital and by 2004 was charged with rebuilding its quantitative analytics team.
Li's trajectory is typical of the quant era, which began in the mid-1980s. Academia could never compete with the enormous salaries that banks and hedge funds were offering. At the same time, legions of math and physics PhDs were required to create, price, and arbitrage Wall Street's ever more complex investment structures.
In 2000, while working at JPMorgan Chase, Li published a paper in The Journal of Fixed Income titled "On Default Correlation: A Copula Function Approach." (In statistics, a copula is used to couple the behavior of two or more variables.) Using some relatively simple math—by Wall Street standards, anyway—Li came up with an ingenious way to model default correlation without even looking at historical default data. Instead, he used market data about the prices of instruments known as credit default swaps.
If you're an investor, you have a choice these days: You can either lend directly to borrowers or sell investors credit default swaps, insurance against those same borrowers defaulting. Either way, you get a regular income stream—interest payments or insurance payments—and either way, if the borrower defaults, you lose a lot of money. The returns on both strategies are nearly identical, but because an unlimited number of credit default swaps can be sold against each borrower, the supply of swaps isn't constrained the way the supply of bonds is, so the CDS market managed to grow extremely rapidly. Though credit default swaps were relatively new when Li's paper came out, they soon became a bigger and more liquid market than the bonds on which they were based.
When the price of a credit default swap goes up, that indicates that default risk has risen. Li's breakthrough was that instead of waiting to assemble enough historical data about actual defaults, which are rare in the real world, he used historical prices from the CDS market. It's hard to build a historical model to predict Alice's or Britney's behavior, but anybody could see whether the price of credit default swaps on Britney tended to move in the same direction as that on Alice. If it did, then there was a strong correlation between Alice's and Britney's default risks, as priced by the market. Li wrote a model that used price rather than real-world default data as a shortcut (making an implicit assumption that financial markets in general, and CDS markets in particular, can price default risk correctly).
It was a brilliant simplification of an intractable problem. And Li didn't just radically dumb down the difficulty of working out correlations; he decided not to even bother trying to map and calculate all the nearly infinite relationships between the various loans that made up a pool. What happens when the number of pool members increases or when you mix negative correlations with positive ones? Never mind all that, he said. The only thing that matters is the final correlation number—one clean, simple, all-sufficient figure that sums up everything.
The effect on the securitization market was electric. Armed with Li's formula, Wall Street's quants saw a new world of possibilities. And the first thing they did was start creating a huge number of brand-new triple-A securities. Using Li's copula approach meant that ratings agencies like Moody's—or anybody wanting to model the risk of a tranche—no longer needed to puzzle over the underlying securities. All they needed was that correlation number, and out would come a rating telling them how safe or risky the tranche was.
As a result, just about anything could be bundled and turned into a triple-A bond—corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them—an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn't matter. All you needed was Li's copula function.
The CDS and CDO markets grew together, feeding on each other. At the end of 2001, there was $920 billion in credit default swaps outstanding. By the end of 2007, that number had skyrocketed to more than $62 trillion. The CDO market, which stood at $275 billion in 2000, grew to $4.7 trillion by 2006.
At the heart of it all was Li's formula. When you talk to market participants, they use words likebeautiful, simple, and, most commonly, tractable. It could be applied anywhere, for anything, and was quickly adopted not only by banks packaging new bonds but also by traders and hedge funds dreaming up complex trades between those bonds.
"The corporate CDO world relied almost exclusively on this copula-based correlation model," saysDarrell Duffie, a Stanford University finance professor who served on Moody's Academic Advisory Research Committee. The Gaussian copula soon became such a universally accepted part of the world's financial vocabulary that brokers started quoting prices for bond tranches based on their correlations. "Correlation trading has spread through the psyche of the financial markets like a highly infectious thought virus," wrote derivatives guru Janet Tavakoli in 2006.
The damage was foreseeable and, in fact, foreseen. In 1998, before Li had even invented his copula function, Paul Wilmott wrote that "the correlations between financial quantities are notoriously unstable." Wilmott, a quantitative-finance consultant and lecturer, argued that no theory should be built on such unpredictable parameters. And he wasn't alone. During the boom years, everybody could reel off reasons why the Gaussian copula function wasn't perfect. Li's approach made no allowance for unpredictability: It assumed that correlation was a constant rather than something mercurial. Investment banks would regularly phone Stanford's Duffie and ask him to come in and talk to them about exactly what Li's copula was. Every time, he would warn them that it was not suitable for use in risk management or valuation.

David X. Li
Illustration: David A. Johnson
In hindsight, ignoring those warnings looks foolhardy. But at the time, it was easy. Banks dismissed them, partly because the managers empowered to apply the brakes didn't understand the arguments between various arms of the quant universe. Besides, they were making too much money to stop.
In finance, you can never reduce risk outright; you can only try to set up a market in which people who don't want risk sell it to those who do. But in the CDO market, people used the Gaussian copula model to convince themselves they didn't have any risk at all, when in fact they just didn't have any risk 99 percent of the time. The other 1 percent of the time they blew up. Those explosions may have been rare, but they could destroy all previous gains, and then some.
Li's copula function was used to price hundreds of billions of dollars' worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared. Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.
Bankers securitizing mortgages knew that their models were highly sensitive to house-price appreciation. If it ever turned negative on a national scale, a lot of bonds that had been rated triple-A, or risk-free, by copula-powered computer models would blow up. But no one was willing to stop the creation of CDOs, and the big investment banks happily kept on building more, drawing their correlation data from a period when real estate only went up.
"Everyone was pinning their hopes on house prices continuing to rise," says Kai Gilkes of the credit research firm CreditSights, who spent 10 years working at ratings agencies. "When they stopped rising, pretty much everyone was caught on the wrong side, because the sensitivity to house prices was huge. And there was just no getting around it. Why didn't rating agencies build in some cushion for this sensitivity to a house-price-depreciation scenario? Because if they had, they would have never rated a single mortgage-backed CDO."
Bankers should have noted that very small changes in their underlying assumptions could result in very large changes in the correlation number. They also should have noticed that the results they were seeing were much less volatile than they should have been—which implied that the risk was being moved elsewhere. Where had the risk gone?
They didn't know, or didn't ask. One reason was that the outputs came from "black box" computer models and were hard to subject to a commonsense smell test. Another was that the quants, who should have been more aware of the copula's weaknesses, weren't the ones making the big asset-allocation decisions. Their managers, who made the actual calls, lacked the math skills to understand what the models were doing or how they worked. They could, however, understand something as simple as a single correlation number. That was the problem.
"The relationship between two assets can never be captured by a single scalar quantity," Wilmott says. For instance, consider the share prices of two sneaker manufacturers: When the market for sneakers is growing, both companies do well and the correlation between them is high. But when one company gets a lot of celebrity endorsements and starts stealing market share from the other, the stock prices diverge and the correlation between them turns negative. And when the nation morphs into a land of flip-flop-wearing couch potatoes, both companies decline and the correlation becomes positive again. It's impossible to sum up such a history in one correlation number, but CDOs were invariably sold on the premise that correlation was more of a constant than a variable.
No one knew all of this better than David X. Li: "Very few people understand the essence of the model," he told The Wall Street Journal way back in fall 2005.
"Li can't be blamed," says Gilkes of CreditSights. After all, he just invented the model. Instead, we should blame the bankers who misinterpreted it. And even then, the real danger was created not because any given trader adopted it but because every trader did. In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust.
Nassim Nicholas Taleb, hedge fund manager and author of The Black Swan, is particularly harsh when it comes to the copula. "People got very excited about the Gaussian copula because of its mathematical elegance, but the thing never worked," he says. "Co-association between securities is not measurable using correlation," because past history can never prepare you for that one day when everything goes south. "Anything that relies on correlation is charlatanism."
Li has been notably absent from the current debate over the causes of the crash. In fact, he is no longer even in the US. Last year, he moved to Beijing to head up the risk-management department of China International Capital Corporation. In a recent conversation, he seemed reluctant to discuss his paper and said he couldn't talk without permission from the PR department. In response to a subsequent request, CICC's press office sent an email saying that Li was no longer doing the kind of work he did in his previous job and, therefore, would not be speaking to the media.
In the world of finance, too many quants see only the numbers before them and forget about the concrete reality the figures are supposed to represent. They think they can model just a few years' worth of data and come up with probabilities for things that may happen only once every 10,000 years. Then people invest on the basis of those probabilities, without stopping to wonder whether the numbers make any sense at all.
As Li himself said of his own model: "The most dangerous part is when people believe everything coming out of it."
— Felix Salmon (felix@felixsalmon.com) writes the Market Movers financial blog at Portfolio.com.
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martes, 30 de julio de 2013

Huelga en los McJobs

Inédita huelga en las cadenas de comida rápida de Nueva York

Empleados de distintas compañías salieron a la calle para protestar y el servicio quedó a cargo de los supervisores. El reclamo ya se extendió a otras ciudades. Qué piden.

CARTELES. Los empleados también reivindican el derecho de crear un sindicato sin el riesgo de ser despedidos. (AFP)
Cientos de empleados de las principales cadenas de comida rápida de Nueva York realizaron hoy una inédita huelga, en reclamo de un aumento de salarios y otras reivindicaciones. La protesta ya se extendió a otras ciudades de Estados Unidos.

En Nueva York, los trabajadores se manifestaron en Times Square y la Quinta Avenida, entre otros sitios clave. De acuerdo a los organizadores, la protesta alcanzó a cerca de 60 locales, cuyos supervisores quedaron a cargo del servicio.

Los empleados, agrupados en el asociación "Fast Food Forward" piden un salario mínimo de 15 dólares por hora, poco más del doble de los actuales 7,25 que se pagan en la mayoría de las cadenas. 

El haber promedio en Nueva York para ese tipo de empleo es de unos nueve dólares por hora. Pero a diferencia de sus colegas de los restoranes, los empleados de comidas rápidas no reciben propinas.

Jonathan Westin, director de Fast Food Forward, dijo que los trabajadores necesitan una paga de 15 dólares por hora para satisfacer sus necesidades básicas en una de las ciudades más caras del mundo.

Los trabajadores también reivindican el derecho de crear un sindicato sin el riesgo de ser despedidos. "Muchos trabajadores están viviendo en la pobreza, no son capaces de poner comida sobre su mesa o tomar el tren para ir a trabajar", indicó Westin. Fast Food Forward comenzó con una campaña local en Nueva York, pero la protesta ya se extendió a otras partes del país, con huelgas previstas esta semana en Chicago, Saint Louis, Detroit, Milwaukee y Kansas City.
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Los futuros MBA sobreestiman sus futuros ingresos

MBA Students Are Totally Deluded About How Much Money They'll Make
MAX NISEN
Business Insider: 




Many would-be MBAs expect a salary after graduation that's far in excess of what they can actually earn.
The average US MBA student expects to earn $140,000 on graduating, a 240% increase from the average current pre-enrollment salary of $58,000, according to a survey by QS TopMBA.com, 
The reality? Payscale puts the median for grads with 4 or less years of experience at $55,779, and $71,920 for those with 5-9 years. 
Graduates of top schools can usually still expect 6 figures. 
MBA salaries have been flat for some time now as graduates price themselves out of many industries, traditionally lucrative banks slash pay, and startups grow increasingly skeptical. Expected salary has gone down slightly from last year, but it's still extremely high. 
Students expect a salary that only students from the top schools in the country get close to. In fact, even Harvard and Stanford only reach $140,000 if you add the average bonus on top of salary. Since the survey includes students from the full spectrum of programs, these expectations are far out of step with reality.
Students outside the US have even higher expectations, with prospective Indian MBAs expecting a 469% increase, and South Africans, a 387% bump.
Here's the report's chart of what incoming MBAs expect around the world:

TopMBA.com
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