A central banking model for neither gods nor monkeys
The quest for a scientific foundation for central banking has been going on for a long time. This quest led in the 1960s and 1970s to large-scale econometric models with hundreds of equations describing the economy in much detail. Central banks used them to predict howinterest rate movements would affect the economy and to discover thebest way to react to shocks like the oil price increases of the 1970s.
It quickly turned out that these large models led to unreliable predictions. The first serious attempt to put central banking on a sound scientific basis failed miserably.
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The diagnosis of this failure was given by Robert Lucas, Nobel Prize winner in economics. The old models considered individual agents (consumers and producers) as passive "nuts and bolts" in a huge machinery. Prof Lucas stressed that these agents are human beings endowed with intelligence and a desire to look for the best possible outcome. In such an environment, he argued, the nuts and bolts should be modelled as active agents trying to anticipate what the central bank would do.
This criticism led to the rational expectations revolution in economics. New models were built in which a new assumption was introduced. Individual agents now were assumed to understand the complexity of the world in which they live and to continuously compute the implications of central bank actions for their present and future welfare.
The earlier extreme assumption of complete stupidity of individual agents was replaced by another extreme assumption of supreme understanding of the intricacies of the economy. In the old models, agents were assumed to have the brains of monkeys. In the new "rational expectations models", agents were given god-like features allowing them to see through the complexities of the world. Milton Friedman reminded us a long time ago that even if the underlying assumptions of a model seem implausible, its power depends on how well it performs in making predictions. On that score, trouble started as soon as the rational expectations models were implemented empirically. They failed, so much so that they had to be brought back to the repair shops almost immediately. There, ad-hoc features that had little to do with rational agents were added until the model ran better.
In spite of this empirical failure, many central banks today use versions of this model. The model is inhabited by super-rational agents for whom the complexity of the world has few secrets. They continuously optimise their present and future consumption plans and are capable of calculating with great precision what the effects will be of interest rate changes implemented by the central bank. This is a fairytale world.
It is quite paradoxical that macroeconomics has arrived at such an extreme view now that we start to learn from psychology and brain sciences that the economic paradigm of perfectly informed optimisers may not be the correct way to model individual decision-making. We learn from these other sciences that individuals experience great problems when they try to understand the world in which they live. They find it difficult to collect and to process the complex information with which they are confronted.
Since they cannot see the whole picture, they use simple rules ("rules of thumb") and partial information to guide their decisions. They are not fools though. They regularly subject these simple rules to profitability tests and only keep those rules that keep their profits at reasonable levels.
These new insights are important for central banks. In a world in which nobody knows the full picture and everybody, including the central banker, struggles to understand what is going on, economic cycles will follow very different paths than the one predicted by the rational agent models. Thus, when individuals fail to understand the functioning of the economy, they will often follow others and be subject to herding behaviour.
As a result, bubbles and crashes become an endemic feature of the economic cycle. Waves of optimism are set in motion in quite unpredictable ways, leading to economic cycles whoseorigins are to be found not in observable data but in the minds of individuals who try to understand the world.
All this is absent in the rational agent models that are now popular among central bankers. These models view the economy in an utterly simplistic way. Sure, they recognise that there are a lot of unpredictable shocks, but once a shock occurs economic agents in these models are capable of forecasting how they will affect the economy. In these models, the role of the central bank is to maintain price stability and to announce its intentions, so that these rational agents can make their complex calculations in a reliable way. An illusion of understanding reality is created that is simply not there in the real world.
The uncertainty central bankers face today is very different from the one found in the rational agent models. First, there is a great deal of unpredictability concerning the effects of interest rate policies. Sometimes interest rate changes introduced by the central bank are quite effective in changing the course of the economy. At other times, these changes fail to have any impact. Second, as the economy is subject to cycles whose origin is difficult to grasp and whose direction can change at the whim of capricious psychological movements, the central banker has often no way of knowing what he will do next.
There has been some debate recently about what a central banker should announce concerning his future intentions. The academic consensus today, which is based on the rational agent model, is that the central bank should announce the path of future interest rates.
I tend to side with Mervyn King, the governor of the Bank of England, who has taken a different view, arguing that there is no point in announcing intentions for the future if that future is clouded in mystery, all too often forcing him to backtrack.
There is a need to move away from extreme assumptions when modelling human behaviour. Human beings are neither the dumb automatons of the old models nor the supreme creatures of knowledge and understanding of the new models.
There is good news though. Increasingly, academic researchers are trying to model the economy assuming that agents with imperfect knowledge are learning and revising their knowledge about the workings of the economy. This approach is still in its infancy but is full of promise for a scientific foundation of central banking. In the meantime, until these new insights mature, central banking will continue to be more art than science.
The writer is professor of economics at the University of Leuven
央行决策要回归人性
对
央行工作科学基础的探求由来已久。这种探求使得上世纪60年代和70年代出现了大量计量经济学模型，这些模型用数以百计的方程式详细描述经济状况。央行利用它们预测利率走势如何影响经济，以及发现应对70年代油价飙升等冲击的最佳方式。
但结果很快表明，这些庞大的模型得出的预测并不可靠。人们将央行工作置于健全科学基础上的首次认真尝试，以失败而狼狈告终。
诺贝尔经济学奖得主罗伯特?卢卡斯(Robert Lucas)对这次失败进行了诊断。这些老模型将经济个体（消费者和生产者）视为一台巨型机器中被动的“螺丝钉”。卢卡斯教授强调，这些个体是具有智慧的人类，渴望寻求最佳的可能结果。他认为，在这样一个环境中，这些“螺丝钉”应当以积极个体的角色被纳入模型中，他们会试图预测央行将采取何种行动。
“理性预期”
卢卡斯的批评，引发了经济学中的理性预期(rational expectations)革命。新模型在建立过程中引入了一项新的假设，即假定经济个体能够理解他们所生活的这个复杂世界，并不断计算央行的行动对他们当前乃至未来的福祉有何影响。
早期模型中经济个体完全愚昧无知的极端假设，被另一个极端假设所取代，即经济个体对经济的复杂机制拥有超凡的理解。在旧模型中，经济个体被假定拥有猴子般的智商。而在新的“理性预期模型”中，经济个体被赋予了神一般的特征，他们能够洞察这个复杂的世界。米尔顿?弗里德曼(Milton Friedman)很久以前就提醒我们，即使一个模型的基本假设看上去并不可信，它的威力仍然取决于预测的准确性。在这方面，理性预期模型一经套用到实践中便遇到了困难。它们遭到失败，以至于不得不立即送回“修理车间”。模型中添加了与理性经济个体无关的特征后，运转才有所改善。
“这个复杂的世界没有奥秘”
尽管在实证中遭遇了失败，如今许多央行仍然采用理性预期模型的各种衍生版本。该模型中的经济个体是超级理性的，对他们来说，这个复杂的世界没有奥秘。他们不断优化当前和未来的消费计划，并且能够相当精确地计算央行实行的利率变化将会产生何种影响。这是一个童话般的世界。
宏观经济学得出如此极端的观点，实在是颇为荒谬，当今我们通过心理学和脑科学认识到，假定个体拥有完美信息并追求利益最大化的经济学范式，也许并不是模拟个体决策的正确方法。我们从这些其它科学中认识到，人们在试图理解他们所生活的这个世界时，遇到很大的困难。他们发现，很难收集和处理自己面对的复杂信息。
既然不能纵观全局，他们便只能运用简单的法则（“经验法则”）和片面的信息来指导决策。但他们也不是傻子。他们会定期用盈利能力分析，来检验这些简单的法则，并且只保留那些能维持合理利润的法则。
这些新见解对于央行非常重要。当今世界，没有人能了解事物全景，而所有人，包括央行行长，都竭力想要理解当前在发生什么，经济周期的运行，与理性个体模型得出的预测结果非常不同。因此，当个体无法理解经济的运行状况时，他们往往会追随其他人，形成羊群行为(herding behaviour)。
经济周期的起源在人们脑海里
其结果是，泡沫与破产成为经济周期的普遍特征。乐观思潮以不可预知的方式兴起，导致经济周期，这些经济周期的起源，并不在可观测的数据中，而在千千万万企图揣测世界的个体的脑海里。
所有这些因素，都没有被纳入如今受到央行行长欢迎的各种理性个体模型。这些模型用一种完全简单化的方式看待经济。当然，这些模型承认，经济中有许多不可预知的冲击，而一旦冲击发生，这些模型中的经济个体有能力预测它们将如何影响经济。在这些模型中，央行的角色是维持价格稳定并公布它们的意图，以便这些理性个体能以可靠的方式进行复杂运算。这样就创造了一个理解现实的假象，而它是完全脱离真实世界的。
央行行长目前面临的不确定性，与理性个体模型里看到的截然不同。首先，利率政策的效果相当不可预知。有时，央行采取的利率变动对于改变经济进程十分有效。而有时，这些变动没有任何效果。其次，由于经济受周期的影响，而周期的起源难以捉摸，方向也会因反复无常的心理活动造成的一念之差而改变，央行行长往往无法知道自己接下来会怎么做。
央行意图应“透明”吗？
近期有一些辩论，探讨央行行长应该公布多少未来意图。如今，基于理性个体模型得出的学术共识是，央行应当宣布未来利率的走向。
我倾向于支持英国央行(Bank of England)行长默文?金恩(Mervyn King)与众不同的立场。他认为，既然未来是一团迷雾，宣布对未来的打算就毫无意义，在许多情况下，这么做会迫使他收回自己的话。
在模拟人类行为时，需要改变极端假设的做法。人类既不是旧模型里傻乎乎的机器人，也不是新模型里无所不知的超凡生灵。
但也有好消息。越来越多的学术研究人员试图基于这样一条假设建立经济模型，即拥有不完全信息的经济个体，会不断学习和修正对经济运行的知识。这种方法仍然处于襁褓阶段，但它给央行工作的科学基础带来了巨大希望。同时，在这些新见解成熟之前，央行的操作仍将更多地是一门艺术而非科学。
作者是比利时鲁汶大学(University of Leuven)经济学教授。
