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Top-down versus bottom-up macroeconomics

The extraordinary assumptions of macroeconomic models have left the outside world perplexed about what economists have been doing during the last few decades. This column contrasts the incongruous rational expectations top-down model with a bottom-up model where no individual is capable of understanding the full complexity of a market system. The bottom-up model creates correlations in beliefs that generate waves of optimism and pessimism. The latter produce endogenous business cycles akin to the Keynesian “animal spirits”.

There is a general perception today that the financial crisis came about as a result of inefficiencies in the financial markets and economic actors’ poor understanding of the nature of risks. Yet mainstream macroeconomic models, as exemplified by the dynamic stochastic general equilibrium (DSGE) models, are populated by agents who are maximising their utilities in an intertemporal framework using all available information including the structure of the model – see Smets and Wouters (2003), Woodford (2003), Christiano et al. (2005), and Adjemian, et al. (2007), for example. In other words, agents in these models have incredible cognitive abilities. They are able to understand the complexities of the world, and they can figure out the probability distributions of all the shocks that can hit the economy. These are extraordinary assumptions that leave the outside world perplexed about what macroeconomists have been doing during the last decades.

Evidence on rationality from other sciences

These developments in mainstream macroeconomics are surprising for other reasons. While macroeconomic theory enthusiastically embraced the view that some if not all agents fully understand the structure of the underlying models in which they operate, other sciences like psychology and neurology increasingly uncovered the cognitive limitations of individuals (see e.g. Kahneman 2002, Camerer et al. 2005, Kahneman and Thaler 2006, and Della Vigna2007). We learn from these sciences that agents only understand small bits and pieces of the world in which they live, and instead of maximising continuously taking all available information into account, agents use simple rules (heuristics) in guiding their behaviour (Gigerenzer and Todd 1999). The recent financial crisis seems to support the view that agents have limited understanding of the big picture. If they had understood the full complexity of the financial system, they would have understood the lethal riskiness of the assets they piled into their portfolios.

Top-down and bottom-up models

In order to understand the nature of different macroeconomic models, it is useful to make a distinction between top-down and bottom-up systems.

  • In its most general definition, a top-down system is one in which one or more agents fully understand the system. These agents are capable of representing the whole system in a blueprint that they can store in their mind. Depending on their position in the system, they can use this blueprint to take command or to optimise their own private welfare. An example of such a top-down system is a building that can be represented by a blueprint and fully understood by the architect.
  • Bottom-up systems are very different in nature. These are systems in which no individual understands the whole picture. Each individual understands only a very small part of the whole. These systems function as a result of the application of simple rules by the individuals populating the system. Most living systems follow this bottom-up logic (see the beautiful description of the growth of the embryo by Dawkins 2009).

The market system is also a bottom-up system. The best description made of this bottom-up system is still the one made by Hayek (1945).

Hayek argued that no individual is capable of understanding the full complexity of a market system. Instead, individuals only understand small bits of the total information. The main function of markets consists in aggregating this diverse information. If there were individuals capable of understanding the whole picture, we would not need markets. This was in fact Hayek’s criticism of the “socialist” economists who took the view that the central planner understood the whole picture and would therefore be able to compute the whole set of optimal prices, making the market system superfluous.

Rational expectations models as intellectual heirs of central planning

My contention is that the rational expectations models are the intellectual heirs of these central-planning models. Not in the sense that individuals in these rational expectations models aim at planning the whole, but in the sense that, as the central planner, they understand the whole picture. These individuals use this superior information to obtain the “optimum optimorum” for their own private welfare. In this sense, they are top-down models.

In a recent paper, I contrast the rational expectations top-down model with a bottom-up macroeconomic model (De Grauwe 2009). The latter is a model in which agents have cognitive limitations and do not understand the whole picture (the underlying model). Instead, they only understand small bits and pieces of the whole model and use simple rules to guide their behaviour. I introduce rationality in the model through a selection mechanism in which agents evaluate the performance of the rule they are following and decide to keep or change their rule depending on how well it performs relative to other rules. Thus agents in the bottom-up model learn about the world in a “trial and error” fashion.

These two types of models produce very different insights. I mention three differences here. First, the bottom-up model creates correlations in beliefs that in turn generate waves of optimism and pessimism. The latter produce endogenous business cycles which are akin to the Keynesian “animal spirits” (see Akerlof and Shiller 2009).

Second, the bottom-up model provides for a very different theory of the business cycle compared to the business cycle theory implicit in the rational expectations (DSGE) models. In the DSGE models, business cycle movements in output and prices arise because rational agents cannot adjust their optimal plans instantaneously after an exogenous disturbance. Price and wage stickiness prevent such instantaneous adjustment. As a result, these exogenous shocks (e.g. productivity shocks, or shocks in preferences) produce inertia and business cycle movements. Thus it can be said that the business cycle in DSGE models is exogenously driven. As an example, in the DSGE model, the financial crisis and the ensuing downturn in economic activity is the result of an exogenous and unpredictable increase in risk premia in August 2007.

In contrast to the rational expectations model, the bottom-up model has agents who experience an informational problem. They do not fully understand the nature of the shock or its transmission. They use a trial-and-error learning process aimed at distilling information. This process leads to waves of optimism and pessimism, which in a self-fulfilling way create business cycle movements. Booms and busts reflect the difficulties of economic agents trying to understand economic reality. The business cycle has a large endogenous component. Thus, in this bottom-up model, the financial crisis and the ensuing economic downturn should be explained by the previous boom.

Finally, the bottom-up model confirms the insight obtained from mainstream macroeconomics (including the DSGE models) that a credible inflation targeting is necessary to stabilise the economy. However, it is not sufficient. In a world where waves of optimism and pessimism (animal spirits) can exert an independent influence on output and inflation, it is in the interest of the central banks not only to react to movements in inflation but also to movements in output and asset prices so as to reduce the booms and busts that free market systems produce quite naturally.


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Akerlof, G., and Shiller, R. (2009), Animal Spirits. How Human Psychology Drives the Economy and Why It Matters for Global Capitalism, Princeton University Press.

Brock, W., and Hommes, C. (1997), “A Rational Route to Randomness”, Econometrica, 65, 1059-1095

Camerer, C., Loewenstein, G., Prelec, D., (2005), “Neuroeconomics: How neuroscience can inform economics”, Journal of Economic Literature, 63(1), 9-64.

Christiano, L., Eichenbaum, M., and Evans, C., (2005), "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, vol. 113(1), pages 1-45, February.

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De Grauwe, P., (2009), “Top-down versus Bottom-up Macroeconomics”, paper presented at the DG ECFIN Annual Research Conference, Brussels, 15-16 October 2009, and at the conference “What is wrong with modern macroeconomics”, CESifo, München, 6-7 November 2009.

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Gigerenzer, G., and Todd, P.M.(1999). Simple Heuristics That Make Us Smart. New York: Oxford University Press.

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