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philosophy of economics

Scientific epistemology is a serious business in economics—as it is in any science. Not surprisingly, therefore, discussions about value-ladeness tend to focus on theoretical and methodological issues within the discipline, while the question of the social consequences of science is approached with more reservation. And for many good reasons, one may say, because it is not entirely up to scientists how will the scientific product be disseminated and interpreted in society, or how will it be used by policy makers. Or, that’s not the job of the scientist, one could reason, to determine and be ready for all possible applicative scenarios.

Since the last few decades, research practices have undergone a far-reaching transformation at the interface between science, policy and society. It involves an increased engagement of science in problem solving and policy advice, and the enhancing role of participatory research methods in problem-based approaches. The social consequences of science become therefore more readily visible, opening up new perspectives on debates about facts and values dichotomy, or the relationship between knowledge, truth, and values (cf. Kitcher, 2001). One way of looking at the transformation of scientific practices focuses on the criteria of scientific rationality with regard to scientific knowledge and the very process of knowledge production, echoing a Weberian contrast between instrumental and axiological rationality of social action (Weber 1968). Specifically, the scientific rationality criteria have been extended in the process from purely (i) internal rationality, that can be defined as a conventional scientific rationality approach focused on disciplinary epistemology and methodology, to (ii) external rationality that pertains to axiological, ethical, and societal elements of knowledge and its production (Kiepas, 2006). 

There are many reasons for including external rationality in scientific practices. For one thing, all applied sciences can be considered as value-laden in virtue of their goal-oriented values (Pullin, 2002). Furthermore, many contemporary problems, as subjects of research, are radically complex. They are laden with systemic uncertainties, meaning that “the problem is concerned not only with the discovery of a particular fact (as in traditional research), but with the comprehension or management of a reality that has irreducible complexities or uncertainties” (see more in Funtowicz & Ravetz, 1994, p. 1882). They also pose future incalculable risks in an unprecedented scope. For example, in the context of complex, adaptive problems such as climate change, uncertainty in science follows (Brown, 2013). Scientific uncertainty regarding the severity and scope of the problem fuels general disagreement about the appropriate actions to undertake. Attempts to accurately assess all the possible climate change impacts and to exhaustingly assign an economic value to alternative courses of action are bound to fail (Jamieson, 2010). That being the case, the policy-relevance of standard economic analysis as the sole knowledge-base for environmental decision making is limited.

In case of economics, the shift in approaches to rationality can be seen in debates about reflexivity in economics, bounded rationality, or performativity of economic models, to name a few topics. But for the most part, ethical- and value-neutrality continue to feature much of economic research, such as in standard normative theories of decision making under uncertainty and risk. The burgeoning of economics as a separate discipline, accompanied by distancing from philosophy, build up strong methodological foundations to prevent any extra-scientific elements to interfere in its analysis (cf. Hausman, 1992).

The classic conceptualisation of uncertainty and risk in economics is very specific and differs from the above-mentioned, sociologically incrusted understanding. Following the paradigmatic distinction formulated by Knight (1921), uncertainty refers to situations of radical uncertainty that cannot be expressed as sets of probabilities, whereas risk is related to situations in which actions do not lead with certitude to specific outcomes, but the alternative outcomes and their probabilities can be discerned. 

The categories of uncertainty and risk, as considered here, lend themselves to complexity of many policy issues, and are associated with the transformation of postmodern societies due to technology, consequences of globalisation, and environmental crises that follow (Beck, 1992; Giddens, 1990). These circumstances, “external” to standard methodological practices, motivate the extension of scientific rationality criteria and rethinking the role of science by researchers themselves. An example of this transformative process is the so-called advocacy science for environmental justice. It represents a socially engaged, multidisciplinary research approach that emerged in response to environmental toxicity movements, and developed an alternative epidemiological paradigm based on participatory research methods (see, e.g., Ottinger & Cohen, 2011).

With regard to the interface between science, policy, and society and the extra-scientific aspects of uncertainty and risk, one can note that the assessment and acceptance of risk are not purely a matter of data analysis or applying the “right” indicators. The perception and interpretation of uncertainty and risk are influenced by a mixture of social, political, and scientific processes that interact with each other. Consider the relationship between environmental pollution and risk. While pollution appears to be solely as a matter of scientific measures, the question of what is an acceptable level of pollution and its risk for a given society, and whether there are cases of unacceptable risks, involves our pre-conceptions and assumptions about what constitutes a good quality of life, wellbeing, and sustainable development (cf. Evernden, 1999).

Why would an individual economist care about the science-policy interface, or about considering extra-scientific elements of her research practice? There are several reasons to seriously reflect on this question. For one thing, transparency about the value content of specific research programs may translate into more careful and accountable approach to complex problems of public policy and the remedying capacity of science and technological progress. Furthermore, Söderbaum (2000) argues that economics should be more properly approached as political economics to make clear the fact that each scientist, as the discipline itself, has an ideological orientation (in the sense of means-ends philosophy) that plays out in the problem-framing, and reflects on the performative features of economic expertise. To the latter point, the analyst’s conclusion that reduces the extra-monetary aspects of a given problem to monetary ones is not without policy consequences; it suggests certain framings and solution-imageries to economic agents and decision makers. Besides, academia itself is not free of subjective interests and rent seeking. But—I haste to add—this does not undermine the value of scientific expertise per se. Neither does it suggest that citizens and policy makers are passive or unreflective recipients of scientific knowledge. It rather suggests a double-edge approach to science that recognises the subjective, cultural, and societal components in scientific practices on the one hand, and the aspiration of scientific community to reach objectivity (understood broadly as a normative objective) on the other hand. Although scientific practices are saturated with theoretical pre-conceptions and cultural perspectives, it does not immediately follow that science has nothing to do with truth and objectivity (a subject that deserves a separate discussion). 

The double-edge approach to science calls for more explicit discussions about the social consequences of science and scientific literacy in society:

  • Concerns about the role of science and scientific expertise in society may facilitate disciplinary reflexivity. It may also feed into methodological approaches. In case of economics, instead of focusing only on expanding the standard framework of economic analysis onto new subjects, concerns about the social consequences of science create a platform for a more direct consideration of methodological alternatives. Especially for contexts in which standard economic tools of analysis display some limits (e.g., cost-benefit analysis in sustainable development planning), alternative approaches that directly accommodate non-monetary impacts and justice concerns are needed (Brown et al., 2017). 
  • According to a political scientist Frank Fischer, in face of technical and social complexity that characterises most of policy issues, citizens and politicians need to display a good level of competence (2009, 1). In this context, an urgent question arises: how to democratise science on the one hand, and how to prevent populism and the spread of fake facts to take the provenience of science (as a source of information about the world) on the other hand? While the aspiration of science to be the absolute truth holder has been widely challenged, it does not immediately follow that there is nothing to scientific knowledge that would make it somehow different from other forms of knowledge. No differentiation at all can give way to anti-science of dangerous kind, in which “facts” are matters of preferences or interests. A caveat here is in order: such differentiation does not imply that scientific knowledge is inherently better than any other form of knowledge.

Certainly there are many challenges to balancing the double-edge approach to science both within and outside of the scientific community, as there are multiple philosophical framings of the role and status of scientific expertise in society. To be continued!

References

Beck, U. (1992). Risk Society: Towards a New Modernity. London: Sage.

Brown, J. Söderbaum, P. & Dereniowska, M. (2017). Positional Analysis for Sustainable Development: Reconsidering Policy, Economics and Accounting. London: Routledge. 

Evernden, N. (1992). The Social Creation of Nature. Baltimore and London: The John Hopkins University Press.

Hasuman, D. M. (1992). The Inexact and Separate Science of Economics. New York: Cambridge University Press.

Fischer, Frank (2009). Democracy & Expertise. Reorienting Policy Inquiry. Oxford: Oxford University Press.

Funtowicz, S. O. & Ravetz, J. R. (1994). Uncertainty, Complexity and Post-normal Science. Environmental Toxicology and Chemistry 13(2), 1881-1885. 

Jamieson, D. (2010). Ethics, Public Policy, and Global Warming. In S. M. Gardiner, S. Caney, D. Jamieson & Henry Shoue (Eds), Climate Ethics. Essential Readings (pp. 77-86). Oxford: Oxford University Press.

Kiepas, A. (2006). Ethics as the Eco-development Factor in Science and Technology. Problems of Eco-development 1(2), 77–86.

Kitcher, P. (2001). Science, Truth, and Democracy. Oxford University Press, Oxford, New York. 

Knight, F. H. (1921). Risk, Uncertainty and Profit. Chicago: University of Chicago Press.

Ottinger, G. & Cohen, B. R. (Eds). (2011). Technoscience and Environmental Justice. Expert Cultures in Grassroots Movement. Cambridge: the MIT Press.

Pullin, A. S. (2002). Conservation Biology. Cambridge & New York; Cambridge University Press. 

Söderbaum, P. (2000). Ecological Economics. A Political Economics Approach to Environment and Development. London: Earthscan/Routledge.

Weber, M. (1968). Economy and Society. New York: Bedminster Press.

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This post is a continuation of ET1%: Blindfolds Created by Economic Theory, We show how the Invisible Hand theory appears to be neutral but actually favors the top 1%.

As quoted and refuted in my earlier post on “Failures of the Invisible Hand“, Mankiw writes that: “The reason for excellent functioning of decentralized market economies is that all participants are motivated by self-interest. This self-interest works better than love and kindness in terms of promoting social welfare.”  

What a monstrous statement! How can any human being think such thoughts? This is what comes from cutting off human experience as a source of knowledge, removing hearts from bodies, and leaving only brains floating in vats as a the sole source of knowledge.

Our hearts — in their pure states –would revolt at the oxymoron of a society based on selfishness. However, contamination by the poisons of economic theory and positivism leads to the blindness to sources of human welfare displayed in the Mankiw quote. In earlier times, A Christmas Carol of Dickens was sufficient as a reminder the wealth is not a measure of welfare. However, modern times reflect modern mindsets, which convert greed and wealth to desirable virtues, as reflected in the Disney version of Uncle Scrooge. So, sadly, it becomes necessary to argue on logical grounds, appealing to brains in vats, instead of appealing to the heart.

First, let us note that “excellent functioning” just means maximization of wealth, and “social welfare” is also measured by the amount of wealth owned by society. At the individual level, the end-of-life psychiatric disorders of Howard Hughes have been the subject of numerous books and articles. Would anyone consider that the billions he made pursuing profits in a market economy created greater social welfare for him than love and kindness would have? What is true at an individual level is also true at a social level — The Easterlin Paradox shows that massive gains in wealth in societies have not caused corresponding increases in happiness. This is true both in time series for single countries, and for cross sectional studies across countries. As detailed and careful studies show — there is no long run relationship between happiness and increases in GNP per capita. Because this finding threatens the foundations of economic theory, economists have challenged it on many different grounds. In a review of these critiques which re-affirms their original findings, Easterlin et. al. have shown that, they do not differentiate between short and long run. The Easterlin Paradox is more accurately stated as – money does buy happiness in the short run, but not in the long run. This is exactly in accordance with my post on “The Coca-Cola Theory of Happiness” — Coca-Cola does buy happiness in the short run, but is not the formula for long run happiness.

Evolutionary biology has now discredited that idea that the survival of the fittest requires selfishness and competition; see Cooperation and Generosity leads to Evolutionary Success. It is almost obvious that groups would be strengthened by coooperation and generosity. There is no question that we would all prefer to live in a society based on love and kindness, instead of living in jungle ruled by survival of the fittest.  If “social welfare” is understand properly, instead of being reduced to a quantity of money in the bank, it is clear that love and kindness would work much better at promoting social welfare.

Why then have economists in the twentieth century insisted on attributing a mis-interpretation of the invisible hand to Adam Smith (see “Adam Smith & the Invisible Hand“) and have made this the central pillar of modern economic theory? The answer lies in ET1%: the necessity for the top 1%  in democratic societies, to invent theories which appeal to the bottom 90%, while actually favoring the rich and powerful. The Invisible Hand asks us to let everyone do whatever they want, since it will all work out to the best for the entire society. Even if the rich and wealthy appear to be exploiting others, the invisible hand will make sure that their greed is harnessed for the welfare of the society. The only way to make sense of this nonsensical message is to understand it as a clever piece of propaganda which supports the interests of the rich and the powerful, by identifying these interests with those of the society as a whole. This is very similar to the “trickle-down” theory, according to which enriching the wealthy will (eventually) bring benefit to the entire society. Even though it is easy to demonstrate “The Failures of the Invisible Hand” both empirically and theoretically, this theory dominates the pages of the modern economics textbooks. This demonstrates the main theme of my post on ET1%: Blindfolds created by Economic Theory;  modern economic theory is meant to blindfold students to the tremendous advantages the capitalist system confers on the tiny minority of the rich and wealthy, the 1%. It systematically distorts our vision and mindset to cause the tremendous inequities of the system disappear. See my paper on “The Invisible Hand: Death of a Metaphor“, for further explanation for how, with repeated use, a metaphorical usage becomes conflated with reality in the public mind. This is extremely beneficial for the 1% as it allows them to create myths which protect their interests, and have them accepted as truths in the form of modern economics. This illustrates the Power/Knowledge thesis of Foucault.

Romer writes that macro-economists casually dismiss facts, and the profession as a whole has gone backwards over the past few decades, losing precious and hard-won knowledge. He does not consider WHY this happened. What are the methodological flaws that create the possibility of moving backwards, losing knowledge, affirming theories known to be in conflict with facts. How is it that leading economists can confidently assert theories which border on lunacy, and receive Nobel Prizes instead of psychiatric treatment?

This is due to the famous AS-IF methodology of Friedman, which gave economists a license for lunacy.  Friedman came up with this defense of orthodoxy when numerous emprical investigation revealed clearly that firms did not maximize profits, did not know their marginal costs, typically used mark-up pricing, and did other things which did not square with neo-classical theories.  Friedman argued that the validity of the axioms of a theory was not relevant; all that mattered was the ability to derive true conclusions from them. This has been called the F-twist:  “Truly important and significant hypotheses will be found to have “assumptions” that are wildly inaccurate descriptive representations of reality, and, in general, the more significant the theory, the more unrealistic the assumptions.” Friedman’s fallacious argument satisfied a deep-seated need — since the daily bread and butter of economics is ‘wildly inaccurate descriptive representations’ — and hence it became wildly popular and widely accepted throughout the economics profession. Now one can, without any embarrassment, make bizarre assumptions worthy of the lunatic asylum, and this is indeed the daily occupation of leading economists.

Friedman’s argument has been universally condemned by logicians and philosophers as an instance of the logical fallacy of “Affirming the consequent” – the use of modus ponens in reverse. That is, Friedman says, in effect, that theory T implies observable consequence C. We observe C, and therefore we can affirm that T holds. This is obviously fallacious since many different theories, inconsistent with T, may also imply consequence C. Even more importantly, a false theory T will always imply consequences C* which are not observed — since the theory is false, it will have consequences which are false. Ignoring all of these problems,  Boland uses an instrumentalist interpretation to defend Friedman, just like all economics textbooks. He writes that even though critics universally condemn his logic, Friedman is right, and ALL the critics are wrong.

In my lecture on  AM2L07 (code for Advanced Micro II: Lecture 7) Methodological Mistakes: Prospect Theory and Psychology Protocols, I explain why Friedman is wrong and his critics are right by discussing this methodological debate within the concrete context of trying to understand search theory. Consider a hypothetical problem where a person is searching for the highest wage. He goes from one firm to next. At each point he is offered a job at a certain wage W. He can accept and quit searching, or reject the offer and go on searching. We want to find a theory which explains search behavior that we observe in lab experiments designed to emulate this situation.

In simple models, it is easy to show that optimal search sets a reservation wage W* and the laborer searches until he/she finds the first offer above this value. The Economist is committed to the assumption that humans are hyper-rational, and they maximize. ONLY theories satisfying these assumptions will be examined for validity. This means that there is NO QUESTION of looking at human behavior itself to see whether or not this hypothesis about behavior holds. Rather, the ONLY problem is to find the FUNCTION which is being maximized.  Economists start by using Expected Utility theory. A rather large number of empirical examples show that this theory does not match human behavior. Nonetheless, this continues to be the dominant theory of decision making under uncertainty and continues to be taught in textbooks, even though the theory is KNOWN to be wrong.

An improvement upon this is PROSPECT theory. By making ad-hoc modifications to probabilities, utilities, and FRAMING the problem in a suitable way, this theory can achieve a MUCH BETTER match to observed behavior than Utility theory. This theory preserves MAXIMIZATION – humans maximize something. However it abandons rationality — why should humans treat probabilities INCORRECTLY. Economists cannot stomach this observed failure of rationality and so AFFIRM theories solidly in conflict with observed facts about human behavior.

NEITHER of these approaches is scientific, since both dogmatically assert allegiance to the maximization principle regardless of observation. The articles by John Hey show how one can move beyond this to a genuinely scientific methodology. He explains how many researchers have investigated search behavior, but have only been concerned with whether or not it matched ASSUMED theories of behavior. INSTEAD he proposes to investigate how humans ACTUALLY behave, without imposing any assumptions about behavior in advance. He used psychological protocols, asking subject to think out loud about the process with which they arrive at the decision on whether to accept an offer or to go on to search for the next one. As can be expected, humans cannot make complex calculations that theory requires of them, and instead they use various heuristics and rules of thumb. These heuristic work fairly well, and get them reasonable close to what someone with full information and infinite computational capabilities could achieve. Nonetheless, the use of heuristics gives radically different results about what we could expect to see in markets where these behaviors, rather than the hypothesized AS-IF behavior is used. The full lecture is linked below

For lecture slides and reference materials, links to related articles, as well as the whole sequence of lectures, see the course website: Advanced Micro II (shortlink: bit.do/ee2018)

POSTSCRIPT: The process of lecturing, trying to explain to my students how their fellow students are being duped by economic textbook, always give me greater clarity. In this lecture, I examine three approaches to understanding human behavior in the process of searching for the best wage (or searching for the best price).

1: AXIOMATIC — represented by Expected Utility. Here we know in advance what human behavior is. We do not need to look at human behavior at all. If someone ELSE studies this behavior and finds that our theories do not match actual behavior, we say that the experiment must be wrong.

2: DESCRIPTIVE — represented by Prospect Theory. Unlike economists, experimentalists and behaviorists study actual behavior. When it fails to match Expected Utility, they came up with a new theory — prospect theory — which summarizes and encapsulates a description of how humans behave in decisions under uncertainty. Economists REJECT this picture because it shows how human behavior is IRRATIONAL – and this conflicts with their FUNDAMENTAL assumptions of rationality, which must be maintained regardless of any inconvenient facts or observations or introspection.

3: SCIENTIFIC: An accurate description permits us to proceed to the next stage, which is to try to understand the REASONS for this behavior. For example, we observe that most people are risk-averse. They prefer the certain outcome of $50 to a gamble with offers $0 and $100 with equal probabilty. Now we can ask why — this is with regards to unobservable, hidden motivations, about which we can never be certain. A good explanation for this is REGRET. Because of our psychological makeup, the flatness of the utility function in gains, a win of 100 does not feel vastly superior to a win of 50. But the real kicker is the feat that if I take a gamble and lose, I will feel so stupid. Avoiding the regret that might occur when I say I should have taken that certain $50 might be the explanation for risk aversion.

Actually, even “reverse Modus Ponens” is not a good description of Friedman’s methodology — there is an added F-Twist: If we can FIND some observations C such that theory T implies them, then we affirm theory T, and IGNORE any other implications of T which actually conflict with observations.

The METHODOLOGICAL point is the Friedman, like all nominalists and instrumentalists, GIVES up on the possibility of understanding human behavior. All he wants is a model which provides a SUPERFICIAL match to some observations. However, many many real life situations show that this is NOT ENOUGH — we need to have a deeper understanding, in order to be able to explain economic and social phenomena.

See also previous related post on Economists Confuse Greek Methodology with ScienceA more recent related post is: The Methodology of Modern Economics.

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That economics is a value-laden science is not a new idea. Most of the prominent economic thinkers were also philosophers, wary of moral and philosophical content of scientific assumptions, models, and theories. That economics needs philosophy, and the separation between these two cannot be maintained any longer, is gaining recognition, and has become a subject of debates in the field of philosophy of economics that brings together (to various extends) philosophers, mainstream, and heterodox economists. For example, Daniel Hausman (1992) discusses that at an analytic level economists do successfully separate the philosophical and ethical content from economic analysis, albeit this separation is possible only at the analytic level. Karl Polanyi (1957), in his discussion on the entanglement of economic activities in the social totality, gives insights from a different perspective how considering the subject of economic study in social vacuum can in fact lead to thinking that scientific practice indeed has disentangled from society.

Today economists of both mainstream (e.g., Jean Tirole) and heterodox approaches more readily admit: economics is a moral and philosophical science. Yet the meaning and scope of the normative components of economics, the epistemic consequences of the social embeddedness of science, and the social consequences of economics are raising so far inconclusive debates. These issues constitute two-tiered dimensions of scientific rationality: external and internal ones. While the criteria of internal rationality (which constitute the standard approach to scientific rationality) refer to disciplinary epistemology and methodology, the criteria of external rationality involve the axiological, ethical, and societal elements of the process of knowledge production and the social consequences of science.

Interestingly, as Gustav Márquez (2016) points out, even in the field of philosophy of economics, the discussions are often focused on the elements of what I call here internal rationality. Márquez argues that the predominant focus on these issues characterize the mainstream philosophy of economics, while the more normatively-laden issues, such as a broader theoretical reorientation towards more responsive and socially engaged approaches (which I considered as aspects related to the external scientific rationality), are not so much a part of the dominant concerns and discourse.

Why would an external rationality matter? What is the meaning of the social consequences of economics as a science? And how the acknowledgment of the value-laden component of scientific practices plays out in research practices of the scientific community, and of an individual researcher? These questions are not easy to answer, as they involve several complex issues, such as what is the meaning of scientific truth, scientific objectivity, how to account for the normative components of science, or what are the grounds for our confidence in scientific methods and analysis—to name a few. While each of these questions opens a Pandora box by itself, my goal is to simply open up some of the ways these profound issues can be approached for a discussion. My guiding thought is that one of the elements that drastically shapes our take on these questions pertains to the context in which science and the process of knowledge production is considered.

My specific focus will be on the role of science in society and for policy making. In my next entries of the WEA Pedagogy Blog, I am going to consider several issues, problems, and controversies raised at the intersection of economics, society, and policy, with an eye towards their educational and pedagogical challenges. My objective is to problematize, hopefully for a broader discussion with the readers, the fact that the specific philosophical commitments (e.g. ontological and epistemological assumptions about the role of science, function of knowledge, scientific truth, etc.) bear impact on how the epistemic consequences of the value-ladedness of economics are framed, and on the acknowledgment and role assigned to the extra-scientific components of research practices.

References:

Hasuman, Daniel M. 1992. The Inexact and Separate Science of Economics. New York: Cambridge University Press.

Márquez, Gustavo. 2016. A Philosophical Framework for Rethinking Theoretical Economics and Philosophy of Economics. London: College Publications.

Polanyi, Karl, [1944] 1957. The Great Transformation. Boston: Beacon Press.