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The Contingent Expectations Hypothesis: Rationality and Contingent Knowledge in Macroeconomics and Finance Theory*

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The Contingent Expectations Hypothesis: Rationality and Contingent Knowledge in Macroeconomics and Finance Theory* Preliminary Draft, March 19, 2013 Copyright Roman Frydman and Michael D. Goldberg The Contingent Expectations Hypothesis: Rationality and Contingent Knowledge in Macroeconomics and Finance Theory* Roman Frydman** and Michael D. Goldberg*** *The authors are grateful to the Institute for New Economic Thinking (INET) for supporting this research. This preliminary draft was prepared for presentation at INET’s April 2013 Annual Plenary conference in Hong Kong. **Department of Economics, New York University and INET Program on Imper- fect Knowledge Economics (IKE) http://www.econ.nyu.edu/user/frydmanr and http://ineteconomics.org/research- program/imperfect-knowledge-economics, respectively. ***Peter T. Paul College of Business and Economics, University of New Hampshire, http://pubpages.unh.edu/~michaelg/, and INET Program on Imperfect Knowl- edge Economics 1 Introduction: The Choice for Macroeco- nomics For macroeconomists, an individual is rational if she uses her understanding of the way the economy works in making decisions that do not conflict with her objectives. In this paper, we reconsider how macroeconomists can build models that are compatible with rational decision-making. We show that, by design, the Rational Expectations Hypothesis (REH) is an abstraction of ra- tional decision-making in a world in which individuals’ knowledge about the process underlying market outcomes does not grow over time. This conclu- sion concerning REH’s limited domain of applicability leads us to propose the contingent expectations hypothesis (CEH) for modeling rational forecasting in markets in which outcomes are driven in part by the growth of participants’ knowledge. CEH rests on Karl Popper’s insights concerning the importance of recognizing the growth of knowledge for developing empirically relevant economic models.1 Our hypothesis also rests on key insights by John Muth and Robert Lucas that led to REH: an economist’s own model can be used to build more rationality into his analysis, and compatibility with rational decision-making requires that the model be internally coherent. We show how CEH provides a way to synthesize REH’s focus on the im- portance of fundamental factors in underpinning rational forecasting with the two other major advances in macroeconomics over the last four decades: Phelps’s et al (1970) research program of basing aggregate relationships on micro-foundations that accord an autonomous role to participants’ expecta- tions, and behavioral economists’ use of empirical observation in representing individuals’ decision-making. By recognizing the importance of the growth of participants’ knowledge for how market outcomes unfold over time, CEH- based analysis can incorporate these approaches, which are usually thought to be incompatible with profit-seeking and rational behavior, into macroeco- nomic models that are compatible with rational decision-making. The importance of constructing such models was the impetus for the rational-expectations revolution. In proposing (REH), Muth (1961, p. 315) persuasively argued that “a systematic theory of fluctuations in markets or in the economy” requires that models of aggregate outcomes “include an explanation of the way expectations are formed.” The difficulty in relating 1 Popper’s (1946, 1957, 1983) insights on the growth of knowledge have had a pro- found impact on our understanding of the scientific process and thinking about change in societies. Our reliance on those insights builds on George Soros’s use of them. Soros’s (1987) analysis was based on the idea of “fallibility”: every understanding of markets is necessarily contingent, eventually becoming inadequate and requiring revision. 2 “the way expectations are formed” to individuals’ understanding of the econ- omy is that there are many ways to understand the process that underpins outcomes in real-world markets — and many ways to understand when and how this process might change. Moreover, market outcomes are driven by participants’ combined buy and sell decisions, which are typically related in macroeconomic models to the aggregate forecast. Any formal representation of the understanding — the knowledge — that underpins the market’s forecast must therefore be a bold abstraction. Muth’s (1961) striking insight was that an economist could use his own model to represent how the market — the aggregate of participants — under- stands how the economy works and how it forecasts outcomes. REH formal- ized this idea: market participants’ “expectations, since they are informed predictions of future events, are essentially the same as the predictions of the relevant economic theory” (p. 316). Although imposing consistency within a macroeconomic model is neces- sary, it is far from sufficient to render a model “relevant” for representing how rational participants understand and forecast economic outcomes over long stretches of time. To be sure, the ultimate test of any model’s relevance is its empirical adequacy in accounting for the observed regularities in time- series data. On this score, the performance of REH models has been less than stellar; they have encountered widespread empirical difficulties in many markets. But REH can be used in myriad models. Thus, rejection of one REH model does not preclude the possibility that another, either existing or yet to be invented, might be empirically adequate and thus could serve as a basis for representing rational forecasting. Indeed, macroeconomists continue to expend enormous resources and tal- ent in this search. In this paper, we advance a theoretical argument that provides an a priori criterion for deciding whether we should continue to rely on REH models, or redirect our research agenda to developing an alternative class of models on which to base our representations of rational forecasting. 2Overview Our argument makes use of the observation that all macroeconomic models that can serve as a basis for representing rational forecasting can be divided into two mutually exclusive classes. Models in both classes relate outcomes to a set of causal factors and characterize the process that governs those fac- tors. This “structure” expresses an economist’s understanding of the process driving aggregate outcomes, including how market participants forecast. Model structures in the two classes may share specifications of partici- 3 pants’ preferences and other components. But, as time passes, the process that underpins economic outcomes may change, at least intermittently, im- plying that distinct structures may be required to represent this process during different stretches of time. The two classes of models formalize sharply different conceptions of such change. One class represents change as determinate: conditional on their structure at any point in time, these models specify in advance all potential structures that might represent the process driving outcomes at any other point in time.2 The other class leaves its models partly open to unanticipated structural change: these models constrain change in their structures over time; but, conditional on any one of the causal structures that is implied by a model at a given point in time, they do not specify in advance the exact structures that may be needed to represent the market process at any other point in time. In conceiving REH, Muth (1961, p. 315-316) emphasized that “the way expectations [are formed] would change when. .the structure of the system is changed.” Muth’s idea was that an economist’s model could serve as the basis for representing changes in “the structure of the system” as well as mar- ket participants’ understanding of such changes. But, because an economist’s model provides “informed predictions of future events” (p. 316), he must choose which of the two classes of models he considers relevant for represent- ing change. By choosing a determinate model as the basis for representing individuals’ understanding of how the “structure of the system is changed,” later theorists in effect adopted a particular conception of change on which to base their representations of rational forecasting. As Lucas (1995, p. 255; 2001, p. 13) pointed out, given this choice, acceptance of REH models as the only valid way to represent rational forecasting follows on logical grounds.3 2 As we show in Frydman and Goldberg (2007), the class of determinate models includes standard REH models, in which the causal structure is constrained to be time-invariant. It also includes REH bubble and multiple-equilibrium models, as well as behavioral-finance models. In section 2, we provide a formal definition of a model’s causal structure, as well as an example of a determinate model that is typical of macroeconomic and finance theory. In Frydman and Goldberg (2007) and our subsequent work, we refer to models that fully prespecify change in probabilistic terms as “fully predetermined.” In Frydman and Gold- berg (2013a), we pointed out that all such models are determinate. Fully predetermined models specify fully in advance not only all potential structures, but also when and how changes between structures might occur. 3 The argument that standard REH models follow on logical grounds underpins the debate between Krugman (2009) and Cochrane (2009) about the rationality of markets. In Frydman and Goldberg (2011, chapter 1), we suggested that the real problem is that both Cochrane and Krugman have relied on the same REH-based conception of rationality. For a mathematical example and further discussion, see section 3 below and Frydman and Goldberg (2013a) 4 By choosing
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