Abstract
Unrealisticness is one of the key challenges to Neoclassical Uncertainty Paradigm. In this chapter I discuss the Critique Realist’s approach to uncertainty. I begin by clarifying the meaning of critical Realism and argue that it is not about realisticness per se. Instead, Critical Realism aims at understanding the problem of phenomenon under study, by analysing its ontological structure. Based on these ontological analyses, methods appropriate to the problem need to be identified. Therefore, the Critical Realists Approach of uncertainty begins with an ontological analysis of the structure of economic reality. It is argued that the economy has to be understood as an open and complex system with emergent properties, which is structured and in which demi-regularities can be identified. Furthermore, economic reality is mutable, so that the degree of uncertainty, which originates from the ontological structure of economic reality, may be different in any two economic situations. From my point of view four stages of uncertainty, which vary in their degree of uncertainty, can be differentiated. Though Critical realism allows for this, compared to neoclassical economics rather detailed analysis of economic reality, it also gives no sufficient answer to the question, of how economic analysis should proceed in the face of Fundamental Uncertainty, which is according to Critical Realism the standard case in economics.
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- 1.
Realism has many different faces in economic and the many faces of realism are now emerging within the methodological literature Hands (2001: 53). Boylan and O’Gorman (1995: 89–93) list four stereotypes of scientific realism thought to be broadly acceptable to those who regard themselves as scientific realists: “(1) The minimum criterion is that the statements of a theory are (or may be) either true or false (contrary to instrumentalism). (2) Furthermore, the statements have to be true or false apart from ourselves that is that although a theorist creates such statements their truth or falsehood is independent of the mind that created them (contrary to relativism). (3) At the ontological level, this can be taken to mean the view that the world exists independently of us, that the world really is this way rather than that, and what we think or feel about it makes no difference (contrary to constructivism). (4) Moreover, it is possible to know what the independently existing objects and their properties in the world truly are (contrary to Kantian idealism). Thus in principle there is no impenetrable veil between such objects, even if they are not directly observable, and their access to the human mind. It is the task of science and the role of theory to discover more precisely what the objects and their essential properties are. The main differences between scientific realism and other philosophies of science concern the role of theories as regards description, prediction and explanation. A theory may do all three things but an empiricist’s basic instinct is to describe, an instrumentalist’s is to predict and the scientific realist’s is to explain.” E.g.: Mäki (1998, 2012) and Hands (2001).
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E.g.: Dow (2012: 14): “Faced with uncertainty, however, economists have developed conventions as to how best to reduce it. The dominant convention, which has gained force over the last 50 years, is to build theory within a formal deductivist framework. This framework builds up formal deductivist models on the basis of axioms about optimising behaviour on the part of individual agents, where knowledge is held with certainty (or certainty equivalence) although specific knowledge may be concealed (asymmetric information). The theoretical system is closed in the sense that variables are classified as endogenous or exogenous. Endogenous variables interact in a predetermined way within a given structure, while exogenous variables are known to be random. There is no place for uncertainty in the form of unquantifiable risk. If addressed at all, uncertainty is understood as an impediment to rational choice.”
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In practice the endogeneity of variables is not always obvious. Van der Lecq argued (2000: 161), “[c]onfusingly, in [mainstream] economics the terms closed and open are applied to formal models. A model which consists of only endogenous variables is called a closed model, whereas a model in which exogenous variables are included in order to solve it, is called an open model. The term open model reflects the idea that the model would be indeterminate without information from outside […] In the terminology [of systems], both closed and open models are examples of a closed system approach.”
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Chick (2004: 5) argues that the particular set of connections and absence of connection, “is what differentiates one system from another and gives them a sense of both character and order”, and concludes: “A system is a network, a structure with connections, within which agents act, mostly in ways which reproduce and reinforce the system, but sometimes in ways which lead the system to evolve.”
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Lawson (2003: 79): “According to the concept I defend, social reality is open in a significant way. Patterns in events do occur. But where the phenomena being related are highly concrete (such as movements in actual prices, quantities of materials or outputs, and most of the other typical concerns of modern economic modellers), such patterns as are found tend to take the form of demi-regularities or demi-regs, that is, of regularities that are not only highly restricted but also somewhat partial and unstable.” Italic is in the original. See also Lawson (1997: 204–221).
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Lawson (1997: 210) argues: “In each case, an explanation considered to be satisfactory will identify at least one systematic difference between the causal history of the primary component and that of the chosen contrast, or which would appear to be essential for the contrast if (…) it is only an imagined situation. In each case, the set of causal factors is responsible is likely to be different.”
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Esposito (2013: 104–105) argues: “Economic decisions are never random. They are guided by motives and projects. They often disappoint and behave unpredictably. This unpredictability, however, can be expected.”
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Imperfect information is the physiological condition and reason of markets Esposito (2013: 110). The most relevant information does not relate to the features of goods, but to the orientation and expectations of others. This information is not contained in prices, but is produced by the behaviour of operators who are oriented to prices Grossman (1976, 1989), Grossman and Stiglitz (1980), and Stiglitz (2003). This information cannot be known in advance because it does not yet exist. E.g.: Esposito (2013: 111): “The critical reflections within economics, however, say more. They introduce elements of complexity that the theory of performativity failed to highlight with the same clarity, in a certain sense radicalizing criticism, as an attempt to offer a way out of the stalemate of their own discipline. The key word is uncertainty, understood in a positive sense as a resource. Uncertainty is the basic resource of economic behaviour and of the possibility for obtaining profits. The world of the economy, Shackle (1970: 164) says, feeds on uncertainty. It is an unavoidable and uncontrollable uncertainty, one that is produced by the very behaviour of operators. Without uncertainty, the economy could not function or exist. In a world of rational and efficient markets, one would not be able to earn or invent anything, because any novelty would be neutralized in advance by the perfect distribution of information. However, a genuine entrepreneur produces surprises, invents novelties which could not be predicted in advance because they introduce a point of discontinuity, a ‘crucial moment’ in history that creates opportunities which did not exist previously. These possibilities cannot be planned, and they produce the persistent uncertainty of time as well as the creativity and dynamism of economic behaviour.”
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Cf. Esposito (2013: 112): “A decision does not only choose between pregiven possibilities, establishing which ones are the most convenient, but creates new opportunities which prove unobtainable from the available data.”
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Cf. (ibid.: 110): “The decision exploits uncertainty, without which there would be no freedom, and at the same time reproduces it, regenerating the unpredictability of the future Davidson (1978: 5 and 10), Snowdon et al. (1994: 300 ff.). Uncertainty, we could say, is the other side of creativity and innovation. This fact should be both understood and appreciated.”
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This conceptualisation has a dramatic impact on the concept of the individual in economics, which becomes morally responsible.
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Cf. (ibid.: 112): “There is always a reason. In fact, there are many reasons and they all have consequences. However, this does not mean that things will go as one wishes. Without a reference to motives, predictions and expectations, one cannot explain what is going on (even when such goings-on deviate from these expectations) and cannot prepare to react properly. If there are reasons, however, then there is no randomness. People do not decide by chance, they decide on the basis of the available information. How can we abandon randomness without giving up structures, describing a world that is unpredictable without being random, which is produced by the motives and decisions of operators but is always surprising? Can we describe the economy by starting from uncertainty and its forms?”
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Beside the LIBOR, Esposito (2013: 6) also discussed the performativity of the Black-Scholes formula (the formula calculates the uncertainty of the future though the indirect calculation of the implied volatility and builds the basis for option pricing). She writes: “The Black-Scholes formula promises to calculate the reality that it had itself produced, and not reality as such. This is shown by the fact that, in the beginning (when the formula was proposed in 1973), the procedure appeared utterly implausible, based on a series of absolutely unrealistic assumptions about the functioning of markets (as the authors themselves remarked). It was admittedly a flawed formula, which became valid when the markets (…) began to adopt it, “believing” in the future reality promised by the formula, and, thereby, making it real in the present. The formula produced the reality which validated the formula.”
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According to Esposito (2013: 7) dominant theories of uncertainty in mainstream economics, such as the Efficient Market Hypothesis Fama (1970) or Random Walk Hypothesis Malkiel (1999), Lo and MacKinlay (1999) fail to reflect is own reflexivity and proceed as if economic reality is independent of economic theory. These economic theories treat economic reality “as if” they describe it and neglect the fact that they are unrealistic and performative and therefore anything but descriptions of economic reality. Instead they are analytical instruments Hausman (1992), which have to be used with caution, as they have an impact to the phenomenon they analyse.
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See also Baecker (1988: 52–53).
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E.g.: “The trend towards mathematization rests on imprecise assumptions and leads researchers to lose sight of the complexity and interdependencies of the real world. […] Economics would be plagued by an excess of formalism without theory, which makes it all the more abstract and detached from its object. The result is the “crisis of vision” of an “esoteric” theory speaking about an imaginary hypothetical reality which does not face the data of reality, but merely demonstrates that the real world confirms its predictions Blaug (1992). The detachment from reality is explicit, given that economic theories refer to variables that must be few in number, homogeneous, permanent, and isolated from the rest of the universe, which never is the case Shackle (1979: 74 ff.) These theories are inevitably subject to errors and ambiguities Hicks (1979: Chap. 1), if they are not outright false Zamagni (1982: 13), only serving to remove or neutralise the social factors which generate uncertainty and instability, putting rigor before relevance.” Heilbroner and Milberg (1995: 101–105).
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Köhn, J. (2017). The Nature of Economics. In: Uncertainty in Economics. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-55351-1_9
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