Uncertainty

BIBLIOGRAPHY

In neoclassical theory, markets are portrayed as stable economic systems, with changes in variables having their desired effects: There is a strong tendency for the economic system to converge toward a position of equilibrium. Economic agents are assumed to have all reliable information for decision making, and the future is known with certainty. Any “uncertainty” regarding future events or outcomes is reduced to a probabilistic distribution.

In heterodox economics, and in post-Keynesian theory in particular, however, markets and economic systems are chaotic and unpredictable (Moore 2006). The economic system is set in what is called “historical time”; that is, the past is known and cannot be changed, but the future is unknown and cannot be predicted. This also suggests that we do not simply move from one position of equilibrium to another: The passage of time implies that during the interval when we are shifting, other variables may also be changing, such that a final position of equilibrium is difficult to predict and may never even exist. In other words, the economy is path-dependent: It is continuously moving such that there is no final position of rest.

The source of this instability is the uncertain future and how it affects motives and the decision making of all agents. Indeed, fundamental uncertainty is a central argument of post-Keynesian theory. It is defined as a situation in which agents do not know the future: It is the pure absence of knowledge. This was a central feature in Keynes’s theory of effective demand (see also Knight 1921; Shackle 1967). As Keynes tells us in this memorable passage (1973, p. 113):

We have, as a rule, only the vaguest idea of any but the most direct consequences of our acts.… By “uncertain” knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is only probable. The game of roulette is not subject, in this sense, to uncertainty.… The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence.… About these matters there is no scientific basis on which to form any calculable probability whatever. We simply do not know.

As Keynes makes clear, uncertainty is not the same as risk. In such a situation, outcomes are usually known, or at least the probability of possible outcomes known with certainty. But let us be clear: Uncertainty is not a situation in which agents cannot compute possible outcomes or probabilities or do not have sufficient information. Gathering more information does not make the future less uncertain.

Uncertainty affects decision making in many ways. For instance, if firms do not know the future or cannot predict future levels of effective demand or growth rates, how can they take a rational decision regarding investment? If central banks cannot know with certainty future levels of inflation or output, how can they correctly take decisions about interest rates? Similarly, how can banks lend to potential borrowers if they do not know whether they will be able to repay their loans, given the uncertain levels of effective demand in the future? The presence of uncertainty also leads to the emergence of power and hierarchical relationships: Faced with uncertainty, agents will try to capture the biggest share of wealth by exerting power over other individuals and social groups (Monvoisin and Rochon 2006).

Despite the pervasive nature of uncertainty, it does not lead to nihilism. Post-Keynesians have developed theories and policies that incorporate uncertainty (see Rochon 2006). Indeed, even when faced with uncertainty, agents, of course, still make decisions. Agents rely on “rules of thumb”: They will rely on past decisions, assume the near future is relatively similar to the present, follow the decisions taken by others, or simply postpone taking a decision.

SEE ALSO Economics; Economics, Post Keynesian; Expectations; Risk; Subjectivity: Analysis

BIBLIOGRAPHY

Davidson, Paul. 1978. Money and the Real World, 2nd ed. New York: Wiley.

Keynes, John Maynard. 1973. The General Theory and After: Part II Defence and Development. Vol. 14 of The Collected Writings of John Maynard Keynes, ed. Donald Moggridge. London: MacMillan and St. Martins Press.

Knight, Frank. 1921. Risk, Uncertainty and Profit. London: The London School of Economics and Political Science.

Monvoisin, Virginie, and Louis-Philippe Rochon. 2006. Economic Power and the Real World. International Journal of Political Economy 35 (4): 5–28.

Moore, Basil. 2006. Shaking the Invisible Hand : Complexity, Endogenous Money and Exogenous Interest Rates. London: Palgrave Macmillan.

Rochon, Louis-Philippe. 2006. Endogenous Money, Central Banks and the Banking System: Basil Moore and the Supply of Money. In Complexity, Endogenous Money and Macroeconomic Theory: Essays in Honour of Basil J. Moore, ed. Mark Setterfield, 220–243. Cheltenham, U.K.: Edward Elgar.

Shackle, G. L. S. 1967. The Years of High Theory: Invention and Tradition in Economic Thought, 1926–1939. Cambridge, U.K.: Cambridge University Press.

Louis-Philippe Rochon

uncertainty
1. The uncertainty about a piece of knowledge in a knowledge base can be represented in a variety of ways. The most popular is to attach a number to the fact or rule, e.g. 1 for complete truth, 0 for complete falsity, ¾ for likely. Sometimes these numbers are intended to be the probability of the knowledge being true. Reasoning systems must assign an inferred uncertainty value to an inferred piece of knowledge. See also certainty factor.

2. See entropy.

un·cer·tain·ty / ˌənˈsərtntē/ • n. (pl. -ties) the state of being uncertain: times of uncertainty and danger. ∎  (usu. uncertainties) something that is uncertain or that causes one to feel uncertain: financial uncertainties.

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