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Archive for the ‘Microeconomics’ Category

Because macroeconomists have messed it up for every one else , says Noah Smith at The Week:

To put it mildly, economists have fallen out of favor with the public since 2008. First they failed to predict the crisis, or even to acknowledge that such crises were possible. Then they failed to agree on a solution to the recession, leaving us floundering. No wonder there has been a steady flow of anti-economics articles (for example, this, this, and this). The rakes and pitchforks are out, and the mob is ready to assault the mansion of these social-science Frankensteins.

But before you start throwing the torches, there is something I must tell you: The people you are mad at are only a small fraction of the economics profession. When people in the media say “economists,” what they usually mean is “macroeconomists.” Macroeconomists are the economists whose job is to study business cycles — booms and busts, unemployment, etc. “Macro,” as we know it in the profession, is sort of the glamor division of econ — everyone wants to know whether the economy is going to do well or poorly. Macro was what Keynes wrote about, as did Milton Friedman and Friedrich Hayek.

The problem is that it’s hard to get any usable results from macroeconomics. You can’t put the macroeconomy in a laboratory and test it. You can’t go back and run history again. You can try to compare different countries, but there are so many differences that it’s hard to know which one matters. Because it’s so hard to test out their theories, macroeconomists usually end up arguing back and forth and never reaching agreement.

Meanwhile, there are many other branches of economics, doing many vital things.

What are those vital things? Some economists find ways to improve social policies that help the unemployed, disabled, and other vulnerable populations. Others design auctions for Google. Some evaluate development polices for Kenya. Others help start-ups. And on and on. Love it or hate it, their work should be judged on its own merits, not lumped in with the very different world of macroeconomics.

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Want to buy a bitcoin?

If you click over to Mt. Gox, the most famous bitcoin exchange, one unit of the crypto-currency will set you back $145. But at Bitstamp you would pay only $129. (At time of writing; prices can change quickly.)

Mt. Gox traders are thus paying a 12% premium for their bitcoins.

That spread seems to violate a fundamental economic law. When transaction costs are low, identical items should trade at nearly identical prices. Otherwise, arbitrageurs would step in to buy cheap and sell dear until the price gap narrows.

But that isn’t happening.

The “law of one price” used to hold. Last fall and winter bitcoin prices at the two big exchanges typically differed by less than 2 percent, a reasonable range given exchange fees and the cost of money transfers (click here if you don’t see the chart or want it bigger):

Bitcoin Spread

In April, however, the bitcoin market went haywire. After spiking to $266 on Mt. Gox, bitcoin prices cratered, falling as low as $54 just two days later. That volatility created large, but temporary spreads between prices on different exchanges (and made it difficult to measure spreads accurately).

When conditions calmed, spreads returned to normal. And then Mt. Gox’s troubles began.

On May 14 the U.S. government accused the exchange of operating an illegal money service business. The government seized $5 million that Mt. Gox held at Dwolla (an online payment processor) and Wells Fargo.

Fearing for their money, Mt. Gox customers converted their at-risk dollars into easy-to-withdraw bitcoins, and the Mt. Gox-Bitstamp spread spiked to 5%.

Spreads briefly normalized until Mt. Gox announced that it was suspending U.S. dollar withdrawals. Mt. Gox had become a Roach Motel (or, if you prefer, a Hotel California) for U.S. dollars. Traders could check their dollars in, but they couldn’t check them out.

Customers responded as you would expect. The spread spiked to 6%, as Mt. Gox traders again converted dollars into bitcoins. The spread briefly narrowed after Mt. Gox’s July 4 announcement of resumed dollar withdrawals. But spreads then spiked to record levels once Mt. Gox customers started reporting that withdrawals remained slow or nonexistent.

Mt. Gox prices are higher than on Bitstamp today because customers apparently can’t get their dollars out of Mt. Gox. So they pay extra for bitcoins. For those customers, a Mt. Gox bitcoin is different from one anywhere else. So the Mt. Gox price isn’t a clean measure of a bitcoin’s value. Instead, it measures the value of a bitcoin plus the desperation of Mt. Gox’s customers.

But that still leaves a puzzle. It makes sense that customers will pay a premium to get their money out. But who is willing to take the other side of the trade, selling bitcoins in return for “Mt. Gox dollars”?

As best as I can tell, those traders have stayed silent on the bitcoin chat boards. Perhaps they are newcomers who think they’ve found an arbitrage opportunity and don’t realize their dollars will be hard to withdraw. Or perhaps they believe that Mt. Gox will get its act together. (A more sinister take, raised on the boards, is that some preferred traders do have the ability to withdraw.) Whatever the case, they stand to make a tidy profit if they can get their dollars out, and sorely disappointed if they can’t.

Sources: For a quick explanation of bitcoin, try this introduction. For price data from numerous exchanges, visit bitcoin charts. My chart uses a 7-day moving average of spreads to smooth the volatility. The measured spread has at times been much higher, e.g., 40%+ on April 10, but that passed quickly.

Disclosure: I own 0.1 bitcoin.

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Creating property rights has helped protect fisheries while making the fishing industry more efficient, according to a nice blog post by Eric Pooley of the Environmental Defense Fund (ht: Dick Thaler). Writing at the Harvard Business Review, Pooley notes the success of the “catch share” approach to fisheries management:

The Gulf of Mexico red snapper fishery, for example, was on the brink of collapse in the early part of the last decade. Fishermen were limited to 52-day seasons that were getting shorter every year. The shortened seasons, an attempt to counter overfishing, hurt fishermen economically and created unsafe “derbies” that often forced them to race into storms like the boats in The Deadliest Catch.

This short window also meant that all of the red snapper were being caught and brought to market at the same time, creating a glut that crashed prices. Many fishermen couldn’t even cover the cost of their trip to sea after selling their fish.

A decade ago, the Environmental Defense Fund began working with a group of commercial red snapper fishermen on a new and better way of doing business. Together, we set out to propose a catch share management system for snapper.

Simply put, fishermen would be allocated shares based on their catch history (the average amount of fish in pounds they landed each year) of the scientifically determined amount of fish allowed for catch each year (the catch limit). Fishermen could then fish within their shares, or quota, all year long, giving them the flexibility they needed to run their businesses.

This meant no more fishing in dangerously bad weather and no more market gluts. For the consumer, it meant fresh red snapper all year long.

After five years of catch share management, the Gulf of Mexico red snapper fishery is growing because fishermen are staying within the scientific limits. Boats that once suffered from ever-shortening seasons have seen a 60% increase in the amount of fish they are allowed to catch. Having a percentage share of the fishery means fishermen have a built-in incentive to husband the resource, so it will continue to grow.

Please read the rest of his piece for additional examples in the United States and around the world. Catch shares don’t deserve all the credit for fishery rebounds (catch limits presumably played a significant role), but they appear to be a much better way to manage limited stocks.

One small quibble: Pooley refers to catch shares as an example of behavioral economics in action. That must be a sign of just how fashionable behavioral economics–the integration of psychology into economics–has become. In this case, though, the story is straight-up economics: incentives and property rights.

For another fun take on property rights and fish, with a very different slant, consider the fight against the invasive lionfish.

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In high school, I learned that absolute zero (about -460° Fahrenheit or -273° Celsius) is as cold as you can get. At that point, all motion ceases, and you can’t get any colder.

So it was a bit of a head-scratcher to learn that physicists recently created a gas whose temperature is below absolute zero. Seems impossible, right?

Well, no. Turns out that the high-school definition of absolute zero doesn’t capture the modern notion of temperature. As Empirical Zeal explains, temperature isn’t only about motion, it’s about an object’s willingness to give up energy. And physicists have been creating negative-temperature objects for more than 60 years.

Measurement is a recurring theme on this blog, so I found this intriguing. All those years, and I didn’t actually know how physicists really measure temperature. But what really caught my eye is that Empirical Zeal uses some ideas from economics to explain what negative temperatures are all about.

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Using the ideas of exchange, marginal utility, and utility maximization, he illustrates how negative temperatures are like a world in which the Dalai Lama should give all his money to Warren Buffett.

I can’t do justice in an excerpt, so please click on over if you are interested.

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Bluefin tuna are swift, gigantic, tasty, and increasingly endangered.* Those last two items go together, of course, with tuna’s high market value encouraging over-exploitation of many populations.

But markets can also encourage creative efforts to preserve threatened species. Jason Kottke points to one example: bluefin farming in Japan. This 5-minute video raises a host of important questions, including the source of baby bluefin and the resource costs of their food. And, full warning, it doesn’t shy away from the bloody reality of bluefin harvesting:

On a closely related note, Felicity Barringer of the New York Times News Service writes about Utah’s market in hunting licenses for deer, elk, moose, and pronghorn.

The auction or sale of scarce licenses inevitably means that some will to well-heeled hunters, often from out-of-state, rather than typical residents. For some, that raises concerns about the marketplace intruding on what was once a natural resource held in public trust. On the other hand, by allocating some licenses to landowners who provide habitat, the program encourages conservation:

Here is how it works: The state has enticed ranchers with an allotment of vouchers for lucrative hunting licenses that they can sell for thousands of dollars as part of a private hunt on their land. Many used to complain bitterly to state officials about elk and other game eating forage meant for their cattle.

The vouchers for hunting licenses, handed out for more than 10 years now, give them ample economic incentive to nurture big game on their land and not get frustrated with ranching and sell their land to developers.

Both the video and the article are great fodder for a discussion of markets and wildlife conservation.

* Note for tuna enthusiasts: There are three species of bluefin (Atlantic, Pacific, and southern) that differ in size and degree of endangerment; see Wikipedia).

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A much-deserved Nobel prize today for Lloyd Shapley and Alvin Roth for their theoretical and practical work on designing markets. In particular, matching markets where you don’t have prices to help you.

The Royal Swedish Academy of Science released a very readable account of their contributions here. Here’s the introduction:

This year’s Prize to Lloyd Shapley and Alvin Roth extends from abstract theory developed in the 1960s, over empirical work in the 1980s, to ongoing efforts to find practical solutions to real-world problems. Examples include the assignment of new doctors to hospitals, students to schools, and human organs for transplant to recipients. Lloyd Shapley made the early theoretical contributions, which were unexpectedly adopted two decades later when Alvin Roth investigated the market for U.S. doctors. His findings generated further analytical developments, as well as practical design of market institutions.

Traditional economic analysis studies markets where prices adjust so that supply equals demand. Both theory and practice show that markets function well in many cases. But in some situations, the standard market mechanism encounters problems, and there are cases where prices cannot be used at all to allocate resources. For example, many schools and universities are prevented from charging tuition fees and, in the case of human organs for transplants, monetary payments are ruled out on ethical grounds. Yet, in these – and many other – cases, an allocation has to be made. How do such processes actually work, and when is the outcome efficient?

Along with his colleague David Gale, Shapley provided theoretical answers to these questions based on the idea of finding stable allocations (i.e., allocations in which no one would later have an incentive to change their mind). Roth then studied how those answers apply in real markets, e.g., designing algorithms to match doctors to hospitals.

Roth also blogs at the aptly-named Market Design. What did he write about yesterday? How Nobel Prizes correlate with chocolate consumption.

P.S. For a moving example of how well-designed matching markets improve human lives, see this post about kidney exchanges.

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The fun economics story of the day is that Orbitz sometimes looks at your computer’s operating system to decide what hotel options to show you. Dana Mattioli breaks the story over at the Wall Street Journal:

Orbitz Worldwide Inc. has found that people who use Apple Inc.’s Mac computers spend as much as 30% more a night on hotels, so the online travel agency is starting to show them different, and sometimes costlier, travel options than Windows visitors see.

The Orbitz effort, which is in its early stages, demonstrates how tracking people’s online activities can use even seemingly innocuous information—in this case, the fact that customers are visiting Orbitz.com from a Mac—to start predicting their tastes and spending habits.

Orbitz executives confirmed that the company is experimenting with showing different hotel offers to Mac and PC visitors, but said the company isn’t showing the same room to different users at different prices. They also pointed out that users can opt to rank results by price.

Here are examples from the WSJ’s experiments:

The WSJ emphasizes that Mac users see higher-priced hotels. For example, Mattioli’s article is headlined: “On Orbitz, Mac Users Steered to Pricier Hotels.”

My question: Would you feel any different if, instead, the WSJ emphasized that Windows users are directed to lower-priced hotels? For example, Windows users are prompted about the affordable lodgings at the Travelodge in El Paso, Texas. (Full disclosure: I think I once stayed there.)

As Mattioli notes, it’s important to keep in mind that Orbitz isn’t offering different prices, it’s just deciding which hotels to list prominently. And your operating system is just one of many factors that go into this calculation. Others include deals (hotels offering deals move up the rankings), referring site (which can reveal a lot about your preferences), return visits (Orbitz learns your tastes), and location (folks from Greenwich, CT probably see more expensive hotels than those from El Paso).

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