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Bounded Rationality In Macroeconomics A Review Essay

Bounded Rationality in Macroeconomics.

Article Type:

Book Review


Books (Book reviews)


Name: Southern Economic Journal Publisher: Southern Economic Association Audience: Academic Format: Magazine/Journal Subject: Business; Economics Copyright: COPYRIGHT 1995 Southern Economic Association ISSN: 0038-4038


Date: July, 1995 Source Volume: v62 Source Issue: n1


NamedWork: Bounded Rationality in Macroeconomics (Book) Review Grade: A


Reviewee: Sargent, Thomas

Accession Number:


Full Text:

When former communists denounce Lenin, it makes headlines. A public disavowal of rational expectations by Thomas Sargent would also make headlines. In his new book, Bounded Rationality in Macroeconomics, Sargent does not quite apostatize. Yet, he does concede that rational expectations modeling leaves important research and policy questions unanswered. To search for potential answers, Sargent surveys the literature on bounded rationality. He also advocates bounded rationality as a new approach to macroeconomic modeling. Though Sargent offers an effective literature survey and several interesting applications of bounded rationality, he fails to persuade the general reader to embrace the new approach. Indeed, Sargent's reliance on mathematics at the expense of intuition limits the audience of Bounded Rationality in Macroeconomics to economists with highly technical research tastes.

Sargent's literature survey is effective because it clearly contrasts modeling with bounded rationality and modeling with rational expectations. In a rational expectations model, agents optimize subject to constraints and hold mutually consistent views about the constraints. Mutual consistency of views implies that agents know a great deal about the environment. As Sargent puts it:

When implemented numerically or econometrically, rational expectations models impute much more knowledge to the agents within the model (who use the equilibrium probability distributions in evaluating their Euler equations) than is possessed by an econometrician, who faces estimation and inference problems that the agents in the model have somehow solved [p. 3].

In contrast, bounded rationality drops the assumption of mutually consistent perceptions. Dropping mutual consistency forces agents to act like econometricians; now agents in the model must use theory and statistics to learn about the environment. While more realistic as a working assumption than rational expectations, bounded rationality exacts a computational price. Again, in Sargent's words:

Ironically, when we economists make the people in our models more "bounded" in their rationality and more diverse in their understanding of the environment, we must be smarter, because our models become larger and more demanding mathematically and econometrically [p. 2].

Researchers will pay the computational price if bounded rationality promises a large return. Sargent sees large returns in three areas of research: multiple equilibria, regime changes, and transitional dynamics. One problem with rational expectations models is that they generate multiple equilibria; bounded rationality can help identify a subset of admissible equilibria. Another problem with rational expectations models arises when analyzing regime changes. Analyzing regime changes under rational expectations implies that agents immediately accept the permanence of any change in policy rules; analyzing regime changes under bounded rationality allows agents to learn slowly about the consequences of policy changes. A third problem is that rational expectations models can predict outcomes inconsistent with real-world observations; bounded rationality offers new sources of dynamics that better capture some real-world processes.

Sargent uses Jean Tirole's No-Trade theorem to demonstrate that modeling with bounded rationality captures real-world processes effectively. Under rational expectations, Tirole proved that equilibrium prices in financial markets completely reveal private information without trade. The zero-trading-volume implication of the theorem strains credulity, given the observed volume in real-world financial markets. Sargent shows that replacing Tirole's rational agents with adaptive agents generates frictions capable of explaining volume. Indeed, in simulations security prices with least squares learning diverge from rational expectations prices, thereby generating volume, for hundreds of periods.

The no-trade example ranks as Sargent's most interesting application of bounded rationality. Appreciating the no-trade application is difficult, however, because the exposition leans heavily on mathematics at the expense of intuition. Consider an example lifted from the section:

Since [z.sub.jt] is a subvector of [z.sub.t], system (24) can be used to deduce the projections

E([z.sub.jt] [where] [Z.sub.jt-1]) = [S.sub.j]([Beta])[Z.sub.jt-1],

where [S.sub.j]([Beta]) depends on (T([Beta]), V([Beta])) and the moments Eutu't. Thus, we have a mapping from a pair of perceived laws of motion [Beta] = ([[Beta].sub.a], [[Beta].sub.b]) to a pair of matrices ([S.sub.a]([Beta]), [S.sub.b]([Beta])) that determine optimal (linear least squares) predictors. A rational expectations equilibrium is a fixed point of this mapping [p. 117]. To be fair, a random passage plucked from any mathematical treatise could bewilder the casual reader. Still, the passage above proves difficult after reading the previous 116 pages carefully.

The entire middle section of Bounded Rationality proves equally difficult. In Chapter four, for example, Sargent divides the subject-networks and artificial intelligence - into seven daunting subheadings: the Perceptron, Feedforward Neural Networks with Hidden Units, Associative Memory, Stochastic Networks, Local and Global Methods, The Genetic Algorithm, and Classifier Systems. In the perceptron discussion, Sargent confronts the reader with Heaviside step functions and sigmoid functions. Later, in the associate memory discussion, the reader trips over Hopfield networks and Hebb's rule. The material under the other subheadings proves no easier. The difficulty of the exposition is puzzling since Sargent seems to want a wider audience than simply highly technical economists. Indeed, in the closing pages of the book, he complains that ". . . macroeconomists have shown very little interest in applying models of bounded rationality to data." To reach a wider audience, Sargent could have expanded the book, including enough intuition to allow macroeconomists of all stripes to grasp the argument. Instead, he choose to argue at a level that only a subset of macroeconomists can follow.

In Bounded Rationality in Macroeconomics, Thomas Sargent seeks to inform the reader about bounded rationality and, more importantly, to persuade him that bounded rationality is a valuable approach to macroeconomic problems. The bounded rationality approach, Sargent argues, makes agents in macroeconomic models behave more like econometricians. Grasping the argument in Bounded Rationality requires, unfortunately, that readers behave more like econometricians. The book reads more like Macroeconomic Theory, a compilation of Sargent's Ph.D. lecture notes, than Rational Expectations and Inflation, a collection of his policy essays. In the introduction to Rational Expectations and Inflation, Sargent observes:

One consequence of the highly technical orientation of early work on rational expectations in macroeconomics is that an appreciation has been slow to develop for the relevance of the ideas for the practice of day-to-day macroeconomics [p. ix].

If Sargent had recalled the observation, he would have produced a valuable introduction to bounded rationality modeling. But, by emphasizing mathematics over intuition, Sargent reduced the value of Bounded Rationality in Macroeconomics. Some future economist will complain that macroeconomists failed to appreciate the relevance of bounded rationality to practical problems. To express the complaint, the economist can use Sargent's observation, with "bounded rationality" in place of "rational expectations."

Mark D. Vaughan The Federal Reserve Rank of St. Louis

Gale Copyright:

Copyright 1995 Gale, Cengage Learning. All rights reserved.

Bounded rationality is the idea that in decision-making, rationality of individuals is limited by the information they have, the cognitive limitations of their minds, and the finite amount of time they have to make a decision.

HECK : A - F, G - L, M - R, S - Z, See also, External links


Quotes are arranged alphabetically by author

A - F[edit]

  • The type of rationality we assume in economics — perfect, logical, deductive rationality — is extremely useful in generating solutions to theoretical problems. But it demands much of human behavior — much more in fact than it can usually deliver. If we were to imagine the vast collection of decision problems economic agents might conceivably deal with as a sea or an ocean, with the easier problems on top and more complicated ones at increasing depth, then deductive rationality would describe human behavior accurately only within a few feet of the surface. For example, the game Tic-Tac-Toe is simple, and we can readily find a perfectly rational, minimax solution to it. But we do not find rational “solutions” at the depth of Checkers; and certainly not at the still modest depths of Chess and Go.
  • There are two basic ways market organization is brought about... Some combination of the two is usual the case:
    1. Strategic structuring, informal or formal, whereby social agents, including the state, establish a rule regime regulating market access and transactions...
    2. Emergent structuring, whereby participants discover or adopt certain similar strategies within bounded rationality and situations with certain opportunity structures and incentive structures. Social network and ecological properties result in relatively well-defined aggregate performance characteristics...
    • Tom R. Burns, The shaping of social organization (1987) p. 127.

G - L[edit]

  • Models of bounded rationality describe how a judgement or decision is reached (that is, the heuristic processes or proximal mechanisms) rather than merely the outcome of the decision, and they describe the class of environments in which these heuristics will succeed or fail.
  • One is forced to assume that ordinary people have the computational capabilities and statistical software of econometricians.
    • Gerd Gigerenzer and Reinhard Selten (2001), in Bounded Rationality. The Adaptive Toolbox, chapters 1 and 2. Cambridge, Massachusetts, quoted in “Bounded Rationality and Macroeconomics”
  • Although contributions of many writers have helped the rise of behavioral economics including psychologists Kahneman and Tversky, I regard the works of George Katona and Herbert Simon instrumental in its rise. While the works of Katona and his colleagues at Michigan University led to the use of survey method in economics and its utilization in measuring the impact of consumer expectations on macroeconomic activity, the work of Simon at Carnegie Tech. (a tremendously stimulating intellectual environment for economic theorizing then) resulted in the important theoretical foundations of behavioral economics, such as the concept of bounded rationality.
    • Hamid Hosseini, "The Arrival of Behavioral Economics: From Michigan, or the Carnegie School in the 1950s and the early 1960s?." The Journal of Socio-Economics 32.4 (2003): 391-409.; abstract
  • Two types of conventions [ in organizational settings] may be distinguished here: (a) conventional rules of behavior demonstrated in the classroom mental experience (first part of the story) and (b) conventional representation of the world revealed in the following discussions with ‘‘experienced” friends (second part).
  • Simon’s conventionalism leads to a decision paradigm, according to which understanding problems of coordination is impossible without taking into consideration individual cognitive limits and social representations of reality.

M - R[edit]

  • In a fundamental sense, Alchian's theory of economic organizations is different from those of Coase or Simon. He disavows an explicit model of individual choice... and... offers a system-level explanation of organizational emergence, structure, and survival that is largely independent of decision making at the micro level... Yet it is precisely this independence of a distinct model of choice that ultimately renders it compatible with the individualistic theories of both Coase and Simon....
Whether individuals optimize under uncertainty or satisfice under the more limiting conditions of bounded rationality... , Alchian's logic of natural selection, when grafted onto either approach, provides a powerful means of deriving and integrating expectations about individuals, organizations and systems. The result in either case is an approach that gains in scope and coherence, and that does so by remaining true to its underlying model of individual choice.
  • Terry M. Moe, "The new economics of organization." American journal of political science (1984). p. 746-747;

S - Z[edit]

  • Around 1958, I became aware of H.A. Simon's seminal papers on bounded rationality and was immediately convinced by his arguments. I tried to construct a theory of boundedly rational multi-goal decision making. Together with Heinz Sauermann, I worked out an "aspiration adaptation theory of the firm" which was published as a journal article in 1962... More and more I came to the conclusion that purely speculative approaches like that of our paper of 1962 are of limited value. The structure of boundedly rational economic behavior cannot be invented in the armchair, it must be explored experimentally.
  • The principle of bounded rationality [is] the capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real world — or even for a reasonable approximation to such objective rationality.
    • Herbert A. Simon, (1947). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. p. 198.
  • Broadly stated, the task is to replace the global rationality of economic man with a kind of rational behavior that is compatible with the access to information and the computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist.
    • Herbert A. Simon (1955) in “A Behavioral Model of Rational Choice”, Quarterly Journal of Economics 69(1), p. 99 quoted in “Bounded Rationality and Macroeconomics”
  • … I shall assume that the concept of ‘economic man’(...) is in need of fairly drastic revision, and shall put forth some suggestions as to the direction the revision might take.
    • Herbert A. Simon (1955) in “A Behavioral Model of Rational Choice”, Quarterly Journal of Economics 69(1), p. 99 quoted in “Bounded Rationality and Macroeconomics”
  • The problem can be approached initially either by inquiring into the properties of the choosing organism, or by inquiring into the environment of choice.
    • Herbert A. Simon (1955) in “A Behavioral Model of Rational Choice”, Quarterly Journal of Economics 69(1), p. 100 quoted in “Bounded Rationality and Macroeconomics”
  • Both from these scanty data and from an examination of the postulates of the economic models it appears probable that, however adaptive the behavior of organisms in learning and choice situations, this adaptiveness falls far short of the ideal of ‘maximizing’ postulated in economic theory. Evidently, organisms adapt well enough to‘satisfice’; theydo not, in general, ‘optimize’.
    • Herbert A. Simon (1956) in “Rational Choice and the Structure of the Environment”, Psychological Review 63(2), p. 129, quoted in “Bounded Rationality and Macroeconomics”
  • A comparative examination of the models of adaptive behavior employed in psychology (e.g., learning theories), and of the models of rational behavior employed in economics, shows that in almost all respects the latter postulate a much greater complexity in the choice mechanisms, and a much larger capacity in the organism for obtaining information and performing computations, than do the former. Moreover, in the limited range of situations where the predictions of the two theories have been compared (...), the learning theories appear to account for the observed behavior rather better than do the theories of rational behavior.
    • Herbert A. Simon (1956) in “Rational Choice and the Structure of the Environment”, Psychological Review 63(2), p. 129, quoted in “Bounded Rationality and Macroeconomics”
  • The first consequence of the principle of bounded rationality is that the intended rationality of an actor requires him to construct a simplified model of the real situation in order to deal with it. He behaves rationally with respect to this model, and such behavior is not even approximately optimal with respect to the real world. To predict his behavior we must understand the way in which this simplified model is constructed, and its construction will certainly be related to his psychological properties as a perceiving, thinking, and learning animal.
  • In Administrative Behavior, bounded rationality is largely characterized as a residual category — rationality is bounded when it falls short of omniscience. And the failures of omniscience are largely failures of knowing all the alternatives, uncertainty about relevant exogenous events, and inability to calculate consequences. There was needed a more positive and formal characterization of the mechanisms of choice under conditions of bounded rationality... Two concepts are central to the characterization: search and satisficing.
    • Herbert A. Simon, "Rational decision making in business organizations", Nobel Memorial Lecture 1978. p. 502.
  • If (...) we accept the proposition that both the knowledge and the computational power of the decision maker are severely limited, then we must distinguish between the real world and the actor’s perception of it and reasoning about it.
  • In the literature of problem solving, the topic I am now taking up is called "problem representation." In the past 30 years, a great deal has been learned about how people solve problems by searching selectively through a problem space defined by a particular problem representation. Much less has been learned about how people acquire a representation for dealing with a new problem—one they haven't previously encountered.
    • Herbert A. Simon, "Bounded rationality and organizational learning." Organization science 2.1 (1991): 125-134.
  • Information impactedness is a derivative condition that arises mainly because of uncertainty and opportunism, though bounded rationality is involved as well. It exists when true underlying circumstances relevant to the transaction, or related set of transactions, are known to one or more parties but cannot be costlessly discerned by or displayed for others.

See also[edit]

External links[edit]