Micro Stars, Macro Effects
On the face of it, economics has had a dreadful decade: it offered no prediction of the subprime or euro crises, and only bitter arguments over how to solve them. But alongside these failures, a small group of the world's top microeconomists are quietly revolutionising the discipline. Working for big technology firms such as Google, Microsoft and eBay, they are changing the way business decisions are made and markets work.
Take, for example, the challenge of keeping costs down. An important input for a company like Yahoo! is internet bandwidth, which is bought at group level and distributed via an internal market. Demand for bandwidth is quite lumpy, with peaks and troughs at different times of the day. This creates a problem: because spikes in demand must be met, firms run with costly spare capacity much of the time.
小星星，大光彩
表面上看，过去十年里经济学的表现十分糟糕：它没能预测到次贷危机和欧元危机，而只是就如何解决危机的问题争论不休。然而，与这种失败如影随形的事实是，一些世界顶级的微观经济学家正悄悄革新着这门学科。供职于诸如谷歌、微软和易趣这些大型科技公司的微观经济学家正改变着商业决策和市场运作的方式。
比如说，降低成本，这个具有挑战性的课题，对于一个像雅虎这样的公司来说最重要的投入就是网络带宽。网络带宽的投入方式是，集团层面来购买带宽，然后再进行内部分销。在一天的不同时间里如高峰期和低谷期对带宽的需求波动是相当大的。这就带来了一个问题：由于高峰期的最大带宽需求必须得到满足，因此高峰以外的大部分时间就会有大量的带宽闲置，这便使得公司处于高成本运营状态。
This was one of the first questions that Preston McAfee, a former California Institute of Technology professor, looked at when he arrived at Yahoo! in 2007. Mr McAfee, who now works for Google, found that uses of bandwidth fall into two categories: urgent (displaying a web page) and delayable (backups and archiving). He showed how a two-part tariff (high prices when demand peaks, low ones otherwise) could shift less time-sensitive tasks to night-time, allowing Yahoo! to use
costly bandwidth more efficiently.
The solution—two types of task, two prices—has intuitive appeal. But economists' ideas on how to design markets can seem puzzling at first. One example is the question of how much detail an online car auctioneer should reveal about the condition of the vehicles on offer. Common sense would suggest some information—a car's age and mileage—is essential, but that total transparency about other things (precise details on subpar paintwork) might deter buyers, lowering the auctioneer's commissions. Academic theory suggests otherwise: in some types of auction more information always raises revenues.
这就是前加州理工学院教授普雷斯顿·麦卡艾菲2007年初到雅虎时遇到的问题之一。现就职于谷歌的麦卡艾菲先生发现带宽的使用可以分为两类：一类是紧急需求(比如网页显示)，一类是可延迟需求(比如备份和存档)。他向人们展示了两部收费制(高峰期时高价格，其他时段低价格)如何可以把时效性不强的任务转为夜间进行，从而使雅虎能够更高效地利用昂贵的带宽。
两类任务，两种价格，这个解决方案具有非常直观的魅力。然而，经济学家最初对如何设计市场的想法似乎令人费解。就拿网络汽车拍卖商应显示多少车况细节问题的例子来说，依常理，一些基本信息如车龄和行驶里程是必须要予以显示的内容，但是如果完全透明化(比如具体到欠佳的面漆)可能会让购买者望而却步，从而减少拍卖商的佣金收入。然而，学术理论的逻辑正好相反：在某些类型的拍卖中更多的信息总是能够增加收入。
To test the idea, Steve Tadelis of the University of California at Berkeley (now also working for eBay) and Florian Zettelmeyer of Northwestern University set up a trial, randomly splitting 8,000 cars into two groups. The first group were auctioned with standard information, including age and mileage. The second had a detailed report on the car's paintwork. The results were striking: cars in the second group had better chances of a sale and sold for higher prices. This effect was most pronounced for cars in poorer condition: the probability of a sale rose by 23%, with prices up by 5%. The extra information meant that buyers were able to spot the type of car they wanted. Competition for cars rose, even the scruffier ones.
为了检验这个理论，加州大学伯克利分校的斯蒂夫·塔德里斯（如今也就职于易趣）和西北大学的弗洛里安·泽特梅尔进行了一项试验，他们将8000辆汽车随机分成两组。第一组被拍卖的汽车使用标准信息，包括车龄和行驶里程。第二组的汽车信息中包含了对面漆的细节描述。结果令人吃惊，反而是第二组汽车售出的几率更高，而且售价也较高。这种结果在车况较差的汽车中最为明显，其出售的几率上升了23%，价格提高了5%。更多的信息意味着买家能够找到他们想要购买的汽车类型。因而竞价更为激烈，就连状况较差的汽车也不例外。
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