经济预测是在招摇撞骗？
作者：英国《金融时报》专栏作家提姆•哈福德(Tim Harford)
2008年7月9日 星期三
长久以来经济预测一直是个笑柄，但在信贷危机发生之后，笑声变得刺耳和苦涩。传统的看法似乎是：经济预测是不可能的，而那些经济预测者都是在招摇撞骗。
“如果是那样的话，”戴维•亨德里教授(David Hendry)在皇家经济学会(Royal Economic Society)一场春季讲座上问道，“为什么我还在这上面浪费自己的时间呢？”
作为英国最受尊重的经济学家之一，亨德里给人留下了孤独无援的深刻印象。
这应归咎于他所选择的领域——经济预测理论。不仅门外汉对该领域持怀疑态度，大多数学院派经济学家也持这种观点。然而他的研究——将令人困惑的计算机辅助运算和简单常识统统结合在一起——让我相信，仍不应将经济预测完全归为骗术。
为什么大多数经济预测没有价值呢？有一个简单的原因：预测很困难。对于那些我们希望预测的结果（经济增长、通胀、房价），我们没有充分理解产生这些结果的潜在经济过程，我们不能准确地衡量所有变量，也不能预见政治或技术变化造成的突变。有些预测——特别是对股价或其它资产价格的预测——本质上讲是自我击溃的，因为如果股价显然将上涨，那么它应该已经上涨了。
然而，亨德里的见解之一——这是与他的合著者迈克尔•克莱门茨(Michael Clements)共同提出的——是：这些困难并非都会带来错误的预测。真正影响预测的是“结构性突变”(structural break)，意即某个基本参数的变动超出了预测者模型所能预见的范围。
这些突变的发生频率之高令人惊讶，但真正的问题在于，即使在发生这些情况之后，常规的预测方法也意识不到。油价预测家从2000年起就预言油价会下降，但油价却一直在攀升。相反的问题出现在上世纪80年代：当时油价暴跌，而专家一致认为价格很快将回升。这种普遍看法持续了多年。1997年英镑大幅升值；而在接下来的8年里，预测家一直预言这种情况将很快逆转。
在所有这些例子中，预测者之所以犯错误，原因在于他们有一种关于油价或英镑汇率“均衡点”的固有观点。在每一个例子中，这种均衡点都变成新的，而在所有例子中，预测家们一次又一次错误地预测一切将回复正常。其中的教训是，无法应对结构性突变的预测方法，会几乎无限次地失效。
亨德里的终极目标是预测结构性突变。这几乎是不可能的：因为这需要一个（或几个）外部力量的平行模型——这些外部力量可以是任何东西，从技术突破、立法变革到一场战争。
有些结构性突变永远都无法预测，虽然亨德里认为，预测者能够（并应该）作出更多的努力以尝试预见到它们。
不过，即使结构性突变无法预测，这也不能成为虚无主义的借口。亨德里的方法论已经创造出一些有价值的东西：能够在发生结构性突变时发现它们。尽管亨德里无法预测世界何时变化，但他的计算机自动化技术能迅速找出已发生的改变。
这听上去可能毫无意义。
事实上，考虑到传统经济预测始终忽略了结构性突变，这种预测不仅难度很大，也很有用。
与亨德里交谈时，我想起了去年夏天信贷危机爆发时最有名的悲叹。高盛首席财务官当时曾表示：“我们注意到连续几天出现了25倍标准方差事件。”其实只要一天就足以意识到世界已然改变。
译者/管婧
阅读本文章英文,请点击 Why economic forecasts are so hard to get right
Why economic forecasts are so hard to get right
By Tim Harford
Wednesday, July 09, 2008
Economic forecasting is a long-standing joke, but the laughter has turned harsh and bitter in the wake of the credit crisis. The conventional wisdom seems to be that economic forecasting is impossible, and that economic forecasters are charlatans.
“In that case,” asked Professor David Hendry in a spring lecture at the Royal Economic Society, “why am I wasting my time on this?”
For one of Britain's most respected economists, Hendry gives the strong impression of a man ploughing a lonely furrow.
His choice of field – the theory of economic forecasting – is to blame. It is viewed with scepticism not only by laymen but by most academic economists, too. But his research – a heady mix of bewildering computer-assisted mathematics and straightforward common sense – has convinced me that economic forecasting shouldn't be consigned to the realm of quackery quite yet.
There is a simple reason why most economic forecasts are useless, which is that forecasting is hard. We don't fully understand the underlying economic processes that produce the results we wish to forecast (growth, inflation, house prices), nor can we measure all the variables accurately, nor anticipate the sudden shifts caused by politics or technological change. Some forecasts – notably of the price of shares and other assets – are intrinsically self-defeating, because if it was obvious that share prices would rise, then they would have risen already.
But one of Hendry's insights – developed with his co-author Michael Clements – is that not all of these difficulties produce bad forecasts. What really screws up a forecast is a “structural break”, which means that some underlying parameter has changed in a way that wasn't anticipated in the forecaster's model.
These breaks happen with alarming frequency, but the real problem is that conventional forecasting approaches do not recognise them even after they have happened. Oil-price forecasters have been predicting since 2000 that the oil price will fall; all the while it has been climbing. The reverse problem applied during the 1980s: oil prices collapsed, but the expert consensus was that the price would recover soon. That consensus persisted for years. The pound appreciated sharply in 1997; for the next eight years, forecasters predicted this appreciation would soon be reversed.
In all these cases, the forecasts were wrong because they had an inbuilt view of the “equilibrium” oil price or sterling exchange rate. In each case, the equilibrium changed to something new, and in each case, the forecasters wrongly predicted a return to business as usual, again and again. The lesson is that a forecasting technique that cannot deal with structural breaks is a forecasting technique that can misfire almost indefinitely.
Hendry's ultimate goal is to forecast structural breaks. That is almost impossible: it requires a parallel model (or models) of external forces – anything from a technological breakthrough to a legislative change to a war.
Some of these structural breaks will never be predictable, although Hendry believes forecasters can and should do more to try to anticipate them.
But even if structural breaks cannot be predicted, that is no excuse for nihilism. Hendry's methodology has already produced something worth having: the ability to spot structural breaks as they are happening. Even if Hendry cannot predict when the world will change, his computer-automated techniques can quickly spot the change after the fact.
That might sound pointless.
In fact, given that traditional economic forecasts miss structural breaks all the time, it is both difficult to achieve and useful.
Talking to Hendry, I was reminded of one of the most famous laments to be heard when the credit crisis broke in the summer. “We were seeing things that were 25-standard deviation moves, several days in a row,” said Goldman Sachs' chief financial officer. One day should have been enough to realise that the world had changed.经济预测经济观察,经济预测是在招摇撞骗
