What makes economics a science?
from Lars Syll
Well, if we are to believe most mainstream economists, models are what make economics a science.
In a recent Journal of Economic Literature(1/2017) review of Dani Rodrik’s Economics Rules, renowned game theorist Ariel Rubinstein discusses Rodrik’s justifications for the view that “models make economics a science.” Although Rubinstein has some doubts about those justifications — models are not indispensable for telling good stories or clarifying things in general; logical consistency does not determine whether economic models are right or wrong; and being able to expand our set of ‘plausible explanations’ doesn’t make economics more of a science than good fiction does — he still largely subscribes to the scientific image of economics as a result of using formal models that help us achieve ‘clarity and consistency’.
There’s much in the review I like — Rubinstein shows a commendable scepticism on the prevailing excessive mathematisation of economics, and he is much more in favour of a pluralist teaching of economics than most other mainstream economists — but on the core question, “the model is the message,” I beg to differ with the view put forward by both Rodrik and Rubinstein.
Economics is more than any other social science model-oriented. There are many reasons for this — the history of the discipline, having ideals coming from the natural sciences (especially physics), the search for universality (explaining as much as possible with as little as possible), rigour, precision, etc.
Mainstream economists want to explain social phenomena, structures and patterns, based on the assumption that the agents are acting in an optimizing (rational) way to satisfy given, stable and well-defined goals.
The procedure is analytical. The whole is broken down into its constituent parts so as to be able to explain (reduce) the aggregate (macro) as the result of interaction of its parts (micro).
Modern mainstream (neoclassical) economists ground their models on a set of core assumptions (CA) — basically describing the agents as ‘rational’ actors — and a set of auxiliary assumptions (AA). Together CA and AA make up what might be called the ‘ur-model’ (M) of all mainstream neoclassical economic models. Based on these two sets of assumptions, they try to explain and predict both individual (micro) and — most importantly — social phenomena (macro).
The core assumptions typically consist of:
CA1 Completeness — rational actors are able to compare different alternatives and decide which one(s) he prefers
CA2 Transitivity — if the actor prefers A to B, and B to C, he must also prefer A to C.
CA3 Non-satiation — more is preferred to less.
CA4 Maximizing expected utility — in choice situations under risk (calculable uncertainty) the actor maximizes expected utility.
CA4 Consistent efficiency equilibria — the actions of different individuals are consistent, and the interaction between them result in an equilibrium.
When describing the actors as rational in these models, the concept of rationality used is instrumental rationality – choosing consistently the preferred alternative, which is judged to have the best consequences for the actor given his in the model exogenously given wishes/interests/goals. How these preferences/wishes/interests/goals are formed is typically not considered to be within the realm of rationality, and a fortiori not constituting part of economics proper.
The picture given by this set of core assumptions (rational choice) is a rational agent with strong cognitive capacity that knows what alternatives he is facing, evaluates them carefully, calculates the consequences and chooses the one — given his preferences — that he believes has the best consequences according to him.
Weighing the different alternatives against each other, the actor makes a consistent optimizing (typically described as maximizing some kind of utility function) choice, and acts accordingly.
Beside the core assumptions (CA) the model also typically has a set of auxiliary assumptions (AA) spatio-temporally specifying the kind of social interaction between ‘rational actors’ that take place in the model. These assumptions can be seen as giving answers to questions such as
AA1 who are the actors and where and when do they act
AA2 which specific goals do they have
AA3 what are their interests
AA4 what kind of expectations do they have
AA5 what are their feasible actions
AA6 what kind of agreements (contracts) can they enter into
AA7 how much and what kind of information do they possess
AA8 how do the actions of the different individuals/agents interact with each other.
So, the ur-model of all economic models basically consists of a general specification of what (axiomatically) constitutes optimizing rational agents and a more specific description of the kind of situations in which these rational actors act (making AA serve as a kind of specification/restriction of the intended domain of application for CA and its deductively derived theorems). The list of assumptions can never be complete, since there will always unspecified background assumptions and some (often) silent omissions (like closure, transaction costs, etc., regularly based on some negligibility and applicability considerations). The hope, however, is that the ‘thin’ list of assumptions shall be sufficient to explain and predict ‘thick’ phenomena in the real, complex, world.
In some (textbook) model depictions we are essentially given the following structure,
A1, A2, … An
———————-
Theorem,
where a set of undifferentiated assumptions are used to infer a theorem.
This is, however, to vague and imprecise to be helpful, and does not give a true picture of the usual mainstream modeling strategy, where there’s a differentiation between a set of law-like hypotheses (CA) and a set of auxiliary assumptions (AA), giving the more adequate structure
CA1, CA2, … CAn & AA1, AA2, … AAn
———————————————–
Theorem
or,
CA1, CA2, … CAn
———————-
(AA1, AA2, … AAn) → Theorem,
more clearly underlining the function of AA as a set of (empirical, spatio-temporal) restrictions on the applicability of the deduced theorems.
This underlines the fact that specification of AA restricts the range of applicability of the deduced theorem. In the extreme cases we get
CA1, CA2, … CAn
———————
Theorem,
where the deduced theorems are analytical entities with universal and totally unrestricted applicability, or
AA1, AA2, … AAn
———————-
Theorem,
where the deduced theorem is transformed into an untestable tautological thought-experiment without any empirical commitment whatsoever beyond telling a coherent fictitious as-if story.
Not clearly differentiating between CA and AA means that we can’t make this all-important interpretative distinction and opens up for unwarrantedly ‘saving’ or ‘immunizing’ models from almost any kind of critique by simple equivocation between interpreting models as empirically empty and purely deductive-axiomatic analytical systems, or, respectively, as models with explicit empirical aspirations. Flexibility is usually something people deem positive, but in this methodological context it’s more troublesome than a sign of real strength. Models that are compatible with everything, or come with unspecified domains of application, are worthless from a scientific point of view.
Economics — in contradistinction to logic and mathematics — ought to be an empirical science, and empirical testing of ‘axioms’ ought to be self-evidently relevant for such a discipline. For although the mainstream economist himself (implicitly) claims that his axiom is universally accepted as true and in no need of proof, that is in no way a justified reason for the rest of us to simpliciter accept the claim.
When applying deductivist thinking to economics, mainstream (neoclassical) economists usually set up ‘as if’ models based on the logic of idealization and a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is of course that if the axiomatic premises are true, the conclusions necessarily follow. But — although the procedure is a marvellous tool in mathematics and axiomatic-deductivist systems, it is a poor guide for real-world systems. As Hans Albert has it on the neoclassical style of thought:
Science progresses through the gradual elimination of errors from a large offering of rivalling ideas, the truth of which no one can know from the outset. The question of which of the many theoretical schemes will finally prove to be especially productive and will be maintained after empirical investigation cannot be decided a priori. Yet to be useful at all, it is necessary that they are initially formulated so as to be subject to the risk of being revealed as errors. Thus one cannot attempt to preserve them from failure at every price. A theory is scientifically relevant first of all because of its possible explanatory power, its performance, which is coupled with its informational content …
Clearly, it is possible to interpret the ‘presuppositions’ of a theoretical system … not as hypotheses, but simply as limitations to the area of application of the system in question. Since a relationship to reality is usually ensured by the language used in economic statements, in this case the impression is generated that a content-laden statement about reality is being made, although the system is fully immunized and thus without content. In my view that is often a source of self-deception in pure economic thought …
Most mainstream economic models are abstract, unrealistic and presenting mostly non-testable hypotheses. How then are they supposed to tell us anything about the world we live in?
Confronted with the massive empirical failures of their models and theories, mainstream economists often retreat into looking upon their models and theories as some kind of ‘conceptual exploration,’ and give up any hopes whatsoever of relating their theories and models to the real world. Instead of trying to bridge the gap between models and the world, one decides to look the other way.
To me this kind of scientific defeatism is equivalent to surrendering our search for understanding the world we live in. It can’t be enough to prove or deduce things in a model world. If theories and models do not directly or indirectly tell us anything of the world we live in – then why should we waste any of our precious time on them?
The way axioms and theorems are formulated in mainstream (neoclassical) economics standardly leaves their specification without almost any restrictions whatsoever, safely making every imaginable evidence compatible with the all-embracing ‘theory’ — and a theory without informational content never risks being empirically tested and found falsified. Used in mainstream economics ‘thought experimental’ activities, it may of course be very ‘handy’, but totally void of any empirical value.
Mainstream economic models are nothing but broken pieces models. That kind of models can’t make economics a science.
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Real-World Economics Review Blog 
My model of economics is that it is a foolish pseudo-discipline that enables people of very dubious ability to get paid fabulous sums for what amounts to modern witch-doctoring.
That’s my model, and if you like I can supply any number of mathemtical equation – and even Kronecker Deltas and bessel functions, if you like.
So my model is scientific, and must be correct.
Q.E.D.
Nothing can make economics a science. It is a reductionist discipline. Under radical uncertainty, there exists no single criteria, no single correct answer, and therefore no correct method to find that answer.
The best models are multiscenario multicriteria optimization models.
But he best that even these models can do is to construct a number of reasonably good (under multiple scenarios and multiple criteria) and reasonably safe (under main criterion of self-preservation and multiple scenarios) candidate strategies. The strategy to be implemented has to be chosen by decision-makers subjectively.
Period.
If your son or daughter were deciding upon a major in college, would you recommend that he or she study economics on the grounds that the major would make a person a useful citizen?
useful to who? and what is a ‘citizen’ – for instance has that category (‘citizen – sub species politics) been replaced by consumer (subspecies economics)
No. My son studied math and OR, my two granddaughters currently study math. (Everybody in good universities, too.)
Economists are the enemies of the country. Their post-industrial dream turned out a nightmare, costing the country more than half-a-trillion a year, no less than 12T overall .
Free trade and globalization are completely wrong theoretically.
They do not impose Pigovian tax on externality (overall trade deficit), as well no fine on common good (the same). With movable capital and technology, it is the absolute advantage that matters. Slaves of 0.1% killed or worsened dozens of millions jobs.
But going back to the three turtles, even the max utility is wrong, unnatural. For billions of years, every living creature starts with self-preservation, only after risks are out starts selecting breakfast berries.
Stop me – can talk on the subject infinitely.
Vladimir, it seems to me the problem is deeper than that. What makes anything a science? What makes a statement about anything scientific? I suggest it is the ability to unambiguously distinguish one thing from another – to measure, not necessarily in quantitative terms – and to use unambiguous terminology: i.e. in combination, sufficiently precisely to express the facts. Without it, Syll’s CA1 assumption fails.
Agreed, then, economics as it is – with obscure terminology like ‘value’ and ‘money’ – is not a science. However, why is it not possible to reconstruct it so that its statements are scientific, but are complex, i.e. point to ambiguity where it exists in fact? I say the terminology has to distinguish the dimensionality of the metric, so that direction of motion (change of position or ordering in time) is included (which it is not if one restricts one’s method to counting), and not merely linear (one way or the other) but angular (which it is, given the whole of space-time). Even assuming money flows, the present assumption is that it is linear and the present practice is to portray it quantitatively, so the fact that it is flowing from the poor to the rich does not arouse too much comment, and representation of flows by single quantities chimes with the gravitational flow of a river or electrical circulation from a central power station – with no mention of what it is for. (Cf. Syll’s CA2). There is, however, a minimally complex (branching) electrical circuit for measuring resistances (Wheatstone’s Bridge), a minimally complex method of directional control (a PID servo), and a minimally complex method of disambiguating terminology by interpreting the use of quantifiable bits (differences which make a difference) in terms of the different uses of the four grammatical functions (adjectives, nouns, adverbs and verbs).
If this seems a bit weird, let me remind you that I worked for twenty years with Algol68. That originated in Frege’s “sense and reference” logic (c.1890) and Russell’s paradox (1903), which opened the floodgates to different types of logic, notably typed, dynamic and error-correcting. Those who developed it as a programming language told me it was intended to both enable and require scientists to specify their proposals unambiguously. By chance I discovered G K Chesterton (also in 1903) had recognised sense and reference in brain logic, such that the linguistic side of our brain refers to (indexes) the sensory side: a functional difference now widely accepted. In any case, as our experiments with Algol68 showed, such indexing turned out to be the key to the relational databases which now serve the internet. Money is an index of value – a pointer to things of value, not a scientific measure – and as such is to be found not in bank statements but in the likes of till rolls.
I will leave you trying to realise the possibility of a scientifically organised economy based on goods and information flows between people performing different economic functions, who need them in the right order: this being controlled not by optimising pricing but (like the internet) by systems of personal addressing and of “giving way” rather like traffic lights or priorities at a roundabout, so we wait longer if we reproduce valuable resources less quickly than we acquire or use them. (Cf. Syll’s CA3 – more or less of what? Both his CA4’s – relating to risk and consistency – require creation of independence by giving way, hence applicability to everyone and all the lights working. If “Models that are compatible with everything, or come with unspecified domains of application, are worthless from a scientific point of view”, wouldn’t that make logic and number formats scientifically worthless?).
The wisdom of G K Chesterton’s masterpiece “Orthodoxy” (on orthogonal logic?) is too rich to quote in full, but this bit is applied later to “man at the cross-roads”.
“Such, it seemed, was the joy of man, either in elfland or on earth; the happiness depended on NOT doing something which you could at any moment do and which, very often, it was not obvious why you should not do”.
One can abstract from this, my position, to more or less your own, Vladimir, but without a concept of science encompassing the logic of its own language I suspect it is not quite what you had in mind.
We entered the age of radical uncertainty. We have to make decisions on basis of information about the future. But there is no more unambiguous, minimally reliable such information – economic, technological, geopolitical, about climate, AI, anything. Zero. Zilch. And several Decision Analysis criteria. So there is no correct strategy – only strategy most acceptable to decision-makers. Depending on their today’s mood. Max of what we can do – construct a number of reasonably safe (flexible without catastrophic outcomes, what I call “adaptable to great many ‘black swan’ scenarios”) candidate strategies to give to the DMs.
Under radical uncertainty, everything upends.
Under radical uncertainty,
where does self-interest and rational discourse leave off, or is it all self-interest when people discuss, or some of the discussion rationally based. If any part of the discourse involves self-interest, then all parties whose interests are involved must be at the table, which is not possible under proprietary capitalism. Answer: stakeholder capitalism.
The most important message of this extraordinarily long post of Lars Syll would be the following:
To me this kind of scientific defeatism is equivalent to surrendering our search for understanding the world we live in. (Third paragraph from the last.)
Lars Syll is attacking the mainstream neoclassical economics. He is right on his critique. But these are a kind of words which have a boomerang effect.
Syll concludes that “Mainstream economic models are nothing but broken pieces models. That kind of models can’t make economics a science.” All right! What should we do? It is to present an economics as science. If it does not exist, Syll should present at least a prospectus for the reconstruction of economics.
I have read several Syll’s posts which criticize the mainstream economics. They are witty and deep and his points are always exact. However, I never read what Syll proposes as an alternative to the mainstream economics. If he doesn’t, he is also a victim of defeatism. He is surrendering our search for understanding the world we live in.
Among many comments, davetallor1 is much more constructive. He is trying to make economics science given the condition that economy is a highly complex object. Uncertainty is only a feature of complexity. We have means to compete with complexity. Don’t surrender to defeatism.
The description of what economists do is certainly in large part accurate, when we consider that no two economists approach their work in the same way or with the same pre-understandings. Radical uncertainty has a long and detailed history in philosophy and science. And thus, is certainly relevant to any discussion of economics. But this is still not science. Not to speak too much in riddles, science is what scientists do. And what scientists do is revealed by observing scientists and the processes of creating not just scientific knowledge but also scientific practice. Via observation we see scientists collect, collate, and interpret data from the “natural” world, recognizing that the “natural” world only exists as theoretical constructs made by humans, whether any one construct is called a “fact” or a “theory.” Students of science try to see and describe these processes – creating nature, creating facts, separating facts from theory, doing observation, etc. All disciplines have similar processes. In history, the study of them is called historiography. In science, historians, and sociologists-anthropologists of science study these processes (social studies of science).
The scientist legitimates scientific judgments by reference to the state of nature, of society, of the human psyche, etc. Historians, sociologists, anthropologists attempt to comprehend these judgements by reference to the cultural context in which they are made. In terms of the cultural processes through which they are constructed. Thus, the emphasis is on scientific practice, which is accessible to the methods of historians, sociologists, and anthropologists, rather than the putative but inaccessible reality of scientists’ theoretical constructs. Our goal here is to interpret the cultural-historical development of economics, including the patterns of judgments entailed in it, in terms of the dynamics of research practice. The social studies of economics emphasize the instrumental aspect of economic knowledge and the agency of economists: knowledge is for use, not simply for contemplation, and economists have their own interests that instruments can serve well or ill. Introduction of the distinctively sociological concept of interest serves to solve the problem of closure in two ways. Closure refers to the achievement of consensus among economists on specific extensions/revisions of culture called economics. On the one hand, actors can be seen as tentatively seeking to extend culture in ways that might serve their interests rather than in ways that might not. And on the other hand, interests serve as standards against which the products of such extensions, new conceptual nets, can be assessed. A good extension of the net is one that serves the interest of the economists’ community best. This, then, is the basic social studies of economists’ practice. With this in hand we can return to the starting point — problematic of science-as-knowledge — and articulate a position: scientific knowledge must be seen, not as the transparent representation of nature, society, or culture, but rather as knowledge relative to a specific culture, with this relativity detailed through a sociological concept of interest.
See: Andrew Pickering, “Science as Practice and Culture, and “Constructing QUARKS: A Sociological History of Particle Physics.”
“Historians, sociologists, anthropologists attempt to comprehend these judgements by reference to the cultural context in which they are made. In terms of the cultural processes through which they are constructed. Thus, the emphasis is on scientific practice, which is accessible to the methods of historians, sociologists, and anthropologists, rather than the putative but inaccessible reality of scientists’ theoretical constructs.”
I would not lump historians and sociologists in the same camp if I were you, Ken. More than once have I encountered, at gatherings (once at one in my honor as a guest lecturer in the management school Trinity College Dublin) the sociologist’s sneer questioning why historians are preoccupied with uniqueness and hence suspicious of the application of models to the real world. Why do sociologists think that preoccupation with specificity and uniqueness is not scientific?
Robert, I earned my PhD in history first, and then Anthropology. For the Anthropology work I complete 60 hours of Sociology. Gives me a rather “unique” perspective. Certainly, my own experience is the same as yours in the 1970’s and 1980’s for most specialties in Sociology. But over time this has changed. Especially in specialties such as science, knowledge, technology, and mathematics. Sociologists and historians now work on many joint projects. With sociologists describing historical and cultural processes as the foundations of actor-networks (systems) and historians applying and testing “models” from sociology. The partnership is mutually advantageous. That said, conflicts do still occur, especially in the areas of individualism, causality, and the durability and stability of collective life (culture).
Some interesting responses to my own “much more constructive” comment (thanks for that recognition, Yoshinori). Vladimir is as usual spot on in his criticism. Reliable knowledge has disappeared beneath a torrent of opinionated, largely mis-information – even about decision criteria – so we are left subject to the whims of powerful “decision-makers”, and the best we can do is promote fail-safe strategies. Giving way at a roundabout (in effect the main roads giving way to side-roads, the rich giving priority to the needs of the poor) is one such strategy, as is Robert’s stakeholder capitalism. So is my “honest money” (credit card) strategy. It’s importance lies in localising decision making and requiring evaluation of consequences before decisions (as against ignoring them afterwards).
Sadly, Ken’s mercurial tongue once again rolls our discussion of science into the rut of his Humean misconceptions, describing beautifully what is true but beside the point. Science is not merely either a successful practice or a failure: it has an aim, which indeed varies with culture. Before the Reformation, reliable knowledge was sought in our Maker’s (or failing that, Nature’s) Handbook. Modern science thereafter began with the insights of one man, Sir Francis Bacon: a decision maker faced with mass unemployment due to mergers and depopulation of landed estates comparable to our recent experiences with the financialisation of industry. Leaving eternity to the theologians, Bacon proposed a secular science “for the glory of God and the relief of Man’s estate”, envisaging its Bible as an encyclopedia of knowledge established for the practical benefit of future generations. Only after 140 years of this, and the likes of Descartes, Newton, Locke, Berkeley and the cynic Voltaire, did Hume turn Descartes’ methodological doubt into practical scepticism: denying (100 years before the revelations of Faraday’s experiments with electricity and magnetism) the existence of forces he could not see (hence God and the validity of any Maker’s handbook).
Here’s the paradox in what you say, Ken: this one man, aiming to make his fortune, told the rich what it was convenient for fortune-seekers to hear, reducing science and likewise morality and politics to agreement by scientists and decision makers on how to describe what they could all see (but could ensure others could not). His student Adam Smith (despite echoes of Bacon’s “relief of Man’s estate”) reinforced the message by famously reducing economics to self-interested pursuit of “The Wealth of Nations”. So, via “economic” decisions taken by the rich and powerful over time, this one rotten apple has infected the whole barrel, until most Anglo-Americans, including you, take his rot for granted insofar as they are even aware of it.
Remember, Descartes doubted his own opinions, Voltaire ridiculed other people’s. Change has to begin somewhere, but it is about planting and nurturing seeds, and in one’s own mind is as good a place as any.
Dave, let me sum up for you what I’m trying to say. First, if you want to appreciate the form of the science created by economists, look at the interests (matters of concern) that economists prefer and want to put into practice. These don’t just vary with culture, they are culture. So, what is the form of economists’ culture today, and what is the history of its creation. Recognizing all along that part of this culture is the assertion that economists alone create it. Which is obviously incorrect. If scientists, then economists crave to observe and describe such cultural artefacts as economy, economics, money, finance, price, cost, etc. To the extent economists reveal rather than obscure these artefacts, economists are pursuing science. And, vice versa. Finally, to the extent observing and describing are primarily or solely in the form of mathematics, economists are failed scientists. So, we need to investigate just how and what mathematics economists use, and in what ways it helps or hinders disclosure of their subject matter.
Ken, the only way I can make sense of “These don’t just vary with culture, they are culture” is that you are referring to the subset of our cultures which is that of economists”, and that is characterised not by its scientific artefacts but by what it leaves out.
This blog is about “What makes economics a science”, which I take as a rhetorical question, for science seeks to reveal “the truth, the whole truth and nothing but the truth”, and economics does not. Looking back through it I found myself agreeing with Hans Albert:
“Science progresses through the gradual elimination of errors from a large offering of rivalling ideas, the truth of which no one can know from the outset”.
Don’t you think that ties in rather well with the model of a horticulturalist planting seeds, not knowing in advance which will turn out to be weeds and which useful? But this next bit seems to sum up one of the things I’ve been trying to get you to understand about the significance of basic as against applied science:
“Clearly, it is possible to interpret the ‘presuppositions’ of a theoretical system … not as hypotheses, but simply as limitations to the area of application of the system in question”.
Given Cartesian coordinates and the two-dimensional surface of a world or universe, one can map where e.g. the local markets are, but not what is going on in them. Such a map is important, however, for without it we would have no idea where to look.
Dave, the central theme of Karl Polanyi’s “The Great Transformation” is a historical description of the emergence of the market economy as a competitor to the traditional economy. One of these “competing” economies is not correct and the other incorrect. Both are alternative cultures. They do not evolve from culture. They are culture. The question we need to consider is how one alternative today is more dominant than the other. This is as Polanyi notes, an historical study. This is what I mean when I say, “the interests (matters of concern) that economists prefer and want to put into practice” are culture. Just not one that is popular with some heterodox economists (and others). This version prefers certain ways of life. Is concerned with certain interests and not others. As are all the alternatives the heterodox and other contrarian economists offer, along with other options preferred by historians, social scientists, moral philosophers, etc.
None of this is about truth. Scientist don’t consider truth. They consider observation compared to other observations. Sometimes as Feynman suggests we begin with a guess (theory) about how some part of the world works, which leads to observations. Other times we just observe something that interests us. The result of this is theoretical constructs (e.g., gravity, supply and demand, social class) which are retained so long as they seem consistent with continuing observations. But at no point does a scientist use the word truth or expect to find it. Even so called “facts” are just the result of observations, in which scientists have significant belief. Therefore, I emphasize the interests or matters of concern of scientists. Considering these reveals where scientists want to go, what they want to study, what kind of science they want to create. That’s why I suggest focusing on these for economists. Looking at these for economists answers the question posed here, “what makes economics a science?” To proceed as suggested by Hans Albert humans would be gods, not humans.
“Clearly, it is possible to interpret the ‘presuppositions’ of a theoretical system … not as hypotheses, but simply as limitations to the area of application of the system in question”. But as I just said the systems, the hypotheses, and the limitations are human constructed based on matters of concern (interests). And so are maps. So, the place to begin is the matters of concern.
Ken, you seem to be at it again, diverting attention from the lines of thought I’m trying to suggest by overpowering them with your own Humean preconceptions. For the benefit of other readers of this (if there are any left), I will try and state as simply as possible where Hume and therefore you are wrong.
Back in 1740, Hume argued that because there was then no known way information could get into heads, “every man is an island”, able at best to agree with other observers about his experience of objects and feelings. On this he built Ken’s individualist theories of science, morality and politics: based on agreement but shorn of invisible activity and communication.
When Ken talks about competing economies as culture, therefore, he is seeing economies in different people’s heads: as states of mind of people who disagree, not evolving for right or wrong, not proposed as truths, but preferred by particular persons. What Ken wants to know is to be found by voting.
Ken’s “None of this is about truth”, therefore, follows logically from his Humean position. Prior to C E Shannon’s work 200 years later, on electronic logic, encoded language and information, any logical alternative was based on denying Hume’s axioms despite what we can’t see. Descartes argued, “I think, therefore I am”; in general, things happen despite us.
Given the distinction between language and energetic action, scientists indeed don’t SEEK truth, they USE it, as a criterion for the reliability of propositions: of correspondence between the meaning of a proposition and an active reality it represents. In other words, not so much descriptively, in a Humean sense, but eventually in the sense of a program doing what it is intended to. We communicate to influence each other’s minds and thereby influence each others’ actions. Hence, sadly, the possibility of computer viruses and rotten apples.
Ken will doubtless continue to believe the story he is familiar and therefore comfortable with rather than concern himself with the significance of mental operations he cannot visualise. I have learned the importance of giving way from bringing up a large family: children have to be allowed to learn from their own mistakes. However, as this discussion is in public, I am going to have to publicly insist that Ken has got it wrong.
Dave, Western philosophy and by extrapolation western science has been stuck in the Enlightenment. Dogmatically so. Hume included. Enlightened moderns remain asleep, spellbound by the euphemism called natural religion, still stuck within the paradigm of design (by mechanistic de-animation or deistic over-animation), still paralyzed by the false split between science and religion, matter and spirit, fact and value, etc. We reject the Enlightenment. Seek to step outside and beyond it. To create opportunities to depict and examine the cultures humans construct and use. Once nature and the natural sciences, society and the social sciences are fully ”secularized,” to use Bruno Latour’s term, it becomes possible to revisit also the category of the supernatural. Then, a different landscape opens which can be navigated through an attention to agencies and their composition. Such freedom of movement allows the use of the rich literature of anthropology and history to compare the ways different “collectives” manage to assemble and totalize different sets of agencies.
Consider these authors that follow the path I describe. They’ve been examining these topics for decades. Yuval Noah Harari, John Darwin, David Christian, Azar Gat, Stephen R. Bown, Michael L. Wilson, I.J.N. Thorpe, David Sloan Wilson, Richard Dawkins, Bruno Latour, John Law, Michel Callon, Andrew Pickering, Naill Ferguson, Glyn Davies, Richard Hofstadter.
As for the remainder of your post, it’s my view that you’ve either been asleep or willfully not looking for the last 45 years. You’ve missed entire ages of change and evolution in science and particularly in sociology, history, and anthropology. And in philosophy. I strongly suggest you reconsider your notion of science. It’s completely wrong headed. If economists follow it, this likely explains why their pursuit of science is a complete failure.
Ken, its a sign of weakness when one has to wheel out the big guns. Try getting your head round Frege’s seminal “Basic Laws of Arithmetic” instead of camp-followers like Dawkins.
I’ve recommended that examining the interests or matters of concern of economists reveals where they want to go, what they want to study, what kind of science they want to create. In this way, we’re able to answer the question, “what makes economics a science?” For example, let’s consider these matters of concern; these choices made by economists. 1) Economists focus their study on individual human agents. Research begins with the assumptions that each human is independent and concerned almost exclusively with satisfying her/his desires. 2) Next, economists assume individuals connect with one another through markets, by which they can satisfy their needs and obtain all the resources needed for survival. 3) Finally, economists’ research assumes the markets are stable; will always settle on an equilibrium that is “efficient” for all market participants and “effective” in meeting the needs of all these participants.
Economists face many problems in producing such a science. First, they cannot study governments, corporations, or what’s generally known as institutions (e.g., religion, family, military) except as individual persons, or as a market. This means it is virtually impossible to use data or research results from the other social sciences or history to verify economists’ research findings or to support broad policy statements and actions. This also leaves economists to focus on the study of “stand-ins” such as CEO’s, entrepreneurs, Senators, fathers, generals, etc. Using these individuals to speak for governments, corporations, etc. Second, there is extensive research by historians, sociologists, and anthropologists showing clearly that markets often fail not only to provide the basics for survival but to create efficient pricing for market participants. Economists generally ignore such research in practice, or attack it as inconsistent with the basic norms of economics. Finally, even a cursory examination of the history of current and historical markets demonstrates they are often unstable and frequently even wild and senseless. Plus, stronger participants commonly control markets to meet purposes these participants choose.
Dave:
I lost the blog with recent proposal of Paul Davidson on organization of balanced international trade. Can you please forward it to my email, skipandscan@optonline.net?
Thank you
Vladimir