Ditch ‘ceteris paribus’!
from Lars Syll
When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on 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. The snag is that if the models are to be relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often don’t. When addressing real economies, the idealizations necessary for the deductivist machinery to work — as e. g. IS-LM and DSGE models — simply don’t hold.
If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? The logic of idealization is a marvellous tool in mathematics and axiomatic-deductivist systems, but a poor guide for action in real-world systems, in which concepts and entities are without clear boundaries and continually interact and overlap.
Or as Hans Albert has it on the neoclassical style of thought:
In everyday situations, if, in answer to an inquiry about the weather forecast, one is told that the weather will remain the same as long as it does not change, then one does not normally go away with the impression of having been particularly well informed, although it cannot be denied that the answer refers to an interesting aspect of reality, and, beyond that, it is undoubtedly true …
We are not normally interested merely in the truth of a statement, nor merely in its relation to reality; we are fundamentally interested in what it says, that is, in the information that it contains …
The neoclassical style of thought – with its emphasis on thought experiments, reflection on the basis of illustrative examples and logically possible extreme cases, its use of model construction as the basis of plausible assumptions, as well as its tendency to decrease the level of abstraction, and similar procedures – appears to have had such a strong influence on economic methodology that even theoreticians who strongly value experience can only free themselves from this methodology with difficulty …
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 …
Defending his IS-LMism from the critique put forward by e. g. Hyman Minsky and yours truly, Paul Krugman writes:
When people like me use something like IS-LM, we’re not imagining that the IS curve is fixed in position for ever after. It’s a ceteris paribus thing, just like supply and demand.
But that is actually just another major problem with the Hicksian construction! As Hans Albert so perspicaciously writes:
The law of demand is an essential component of the theory of consumer market behavior. With this law, a specific procedural pattern of price-dependent demand is not postulated, that is, a certain demand function, but only the general form that such a function ought to have. The quantity of the good demanded by the consumers is namely characterized as a monotone-decreasing function of its price.
The law appears prima facie to predicate a relatively simple and easily testable relationship and thus to have a fair amount of content. However, upon closer examination, this impression fades. As is well known, the law is usually tagged with a clause that entails numerous interpretation problems: the ceteris paribusclause … The ceteris paribus clause is not a relatively insignificant addition, which might be ignored. Rather, it can be viewed as an integral element of the law of demand itself. However, that would entail that theoreticians who interpret the clause differently de facto have different laws of demand in mind, maybe even laws that are incompatible with each other …
Bringing this to bear on our law of demand, the consequence is that … if the factors that are to be left constant remain undetermined, as not so rarely happens, then the law of demand under question is fully immunized to facts, because every case which initially appears contrary must, in the final analysis, be shown to be compatible with this law. The clause here produces something of an absolute alibi, since, for every apparently deviating behavior, some altered factors can be made responsible. This makes the statement untestable, and its informational content decreases to zero.
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Real-World Economics Review Blog 
“T. W. Hutchison… called attention to the significance of ceteris paribus clauses as a form of alibi…” — Hans Albert
Methiness
Comment on ‘Ditch ‘ceteris paribus’!’
Lars Syll writes: “When applying deductivist thinking to economics, neoclassical economists usually set up “as if” models based on 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.” (See intro)
Exactly so. Now, it is not breaking news that the neoclassical premises are green-cheese assumptions. The neo-Walrasian approach takes, among other nonentities, constrained optimization and equilibrium into the premises (Weintraub, 1985, p. 147). Only for the representative economist it comes as a surprise that the logical conclusions from these premises have never found a correspondence in reality. Yet, as we all know since J. S. Mill, this and nothing else is the point of the whole exercise.
“The ground of confidence in any concrete deductive science is not the à priori reasoning itself, but the accordance between its results and those of observation à posteriori.” (Mill, 2006, p. 896)
Reality is the final arbiter of the deductive method. Absolutely nothing has changed between the classical economist Mill and the modern physicist Feynman.
“It does not matter that moos and goos cannot appear in the guess. You can have as much junk in the guess as you like, provided that the consequences can be compared with experiment.” (Feynman, 1992, p. 164)
What the representative economist never understood is that his green-cheese assumptions have no testable consequences and therefore are inadmissible in the first place.
Alternatively, if it turns out that there is no accordance between ‘results and observation’ modus tollens applies, that is, one can be sure that at least one of the premises is false. This is the built in error-correction mechanism that guarantees progress. The wrong premise has to be found and eliminated.
Having dealt long enough with the neoclassical approach it is obvious that all premises are false. Therefore, there remains but one consequence: all neoclassical premises have to be replaced. Debunking Orthodoxy is the easy part, to spell out the heterodox axiom set is the real task.
Let us face the facts: since Veblen’s fundamental critique of Orthodoxy Heterodoxy has failed at this task. What is worse, many heterodox economists simply have no clue how to use the deductive method to their advantage.*
The methiness of economics consists of two interlocked mistakes: (i) to spoil the deductive method with green-cheese assumptionism (=Orthodoxy) and (ii), not to apply it at all (=Heterodoxy).
Egmont Kakarot-Handtke
References
Feynman, R. P. (1992). The Character of Physical Law. London: Penguin.
Mill, J. S. (2006). A System of Logic Ratiocinative and Inductive. Being a Connected View of the Principles of Evidence and the Methods of Scientific Investigation, volume 8 of Collected Works of John Stuart Mill. Indianapolis, IN: Liberty Fund.
Weintraub, E. R. (1985). Joan Robinson’s Critique of Equilibrium: An Appraisal. American Economic Review, Papers and Proceedings, 75(2): 146–149. URL
http://www.jstor.org/stable/1805586.
* See the references to the discussions on this blog
http://axecorg.blogspot.de/2014/12/whose-failure-cross-references.html
Rigorous deductions from precise axioms is mathematics, not economics, not science.
Do we have to keep saying it over and over?
Mathematical models may or may not have any useful resemblance to the observable world. Science, and proper economics, is addressing *that* question.
No
Comment on ‘Ditch ‘ceteris paribus’!’
You say: “Rigorous deductions from precise axioms is mathematics, not economics, not science.”
“It is my conviction that pure mathematical construction enables us to discover the concepts and the laws connecting them which give us the key to the understanding of the phenomena of Nature. Experience can of course guide us in our choice of serviceable mathematical concepts; it cannot possibly be the source from which they are derived; experience of course remains the sole criterion of the serviceability of a mathematical construction for physics, but the truly creative principle resides in mathematics.” (Einstein, 1934, p. 167)
It is pretty obvious that you do not understand the relationship between science and mathematics and in particular of economics, science, and mathematics.*
The answer to your question ‘Do we have to keep saying it over and over?’ is therefore No.
Egmont Kakarot-Handtke
References
Einstein, A. (1934). On the Method of Theoretical Physics. Philosophy of Science,
1(2): 163–169. URL http://www.jstor.org/stable/184387.
* The study of the new heterodox curriculum is strongly recommended
http://axecorg.blogspot.de/2015/04/new-curriculum-cross-references.html
I agree that one cannot ditch ‘ceteris parabis’ or formal models – the former is unavoidable (reflecting the restricted scope of models) and the latter essential (for any inter-scientist collaboration and progress).
The problems with economics, and the above examples, is the lack of connection between formal models and what is observed/the data — they are just insufficiently validated for their claimed purposes. To put it another way, purely formal results are assumed to hold (at least in some vague way) to observed phenomena WITHOUT SOLID EVIDENCE that this is so. In fact they may not just be approximately wrong, but fundamentally wrong. Economics understands the importance of formal models and the importance of data, but fails to connect the two in a sufficiently rigorous manner.
Well, yes, ditch ‘ceteris paribus’; or perhaps think of it as reminding us that the axiomatic approach and indeed description generally is NOT true. What may or may not be true is the logic being used, and the point of that is to lead us (near enough) to the point where we don’t need it, because we can SEE what to do to achieve what we need or intend.
What turned a mathematician, C E Shannon, into a scientist was his accidental discovery that logic is not just a set of rules but a structure like a telephone switchboard, the circuits of which (when connected) guide conversations to their destination but do not describe or predict their content (which if of interest should be listened to). He later showed how such conversations can encode information in different ways: most efficiently in structures of bits encodable in terms of switched circuits being closed or open, and most reliably when these “word” structures are combined with redundant (logically unnecessary) check bits enabling changes during transmission to be detected and corrected. Like Hans Albert here (fourth praragraph above), this theory points to limitations of capacity. The mathematical logic for deconstructing axioms does not explain scientifically why and how it works; the mathematics of the logical structure of PID information feedback systems does both.
So how to have a conversation about a structure? I’ve used words to point to a structure (an electrical circuit transmitting information) which can be seen in the imagination. Egmont has offered a set of equations pointing to generalisations about what is going on in economic conversations. Geoff, I regret to say, seems unaware of the communications going on in “observing the world”, and hence of the significance of having the wrong logical framework, or of being misled deliberately or by following the crowd, and in general of would-be scientists not looking in the right place. Not seeing theory as telling us where to look. Seeing mathematics as about numbers when in fact Pythagoras began with circles. And circles, ceteris paribus, though descriptively less variable in geometric form than circuits, nevertheless are circuits and illustrate their topological invariances.
If we want to know what’s going on in economics we need to look in the right place. Almost the one thing common in the ecological catastrophe which is our present “economic” system is money. Would-be scientists should be focussing on what money is, how it is created and what happens to it, rather than trying to read between deliberately deceptive “bottom lines”. It might help them to study humble electrical, communications and computing circuits first, along with brain and computer architecture (input/output, index/encoded memory).
Ditch it all
Comment on ‘Ditch ‘ceteris paribus’!’
Environmental pollution is, no doubt, one of our most serious problems. Second, perhaps, only to intellectual pollution. It can be said without much exaggeration that the collective human brain is a voluminous stockpile of slogans, memes, beliefs, legends, barren paradigms, and defunct theories. Orthodox economics has contributed much to this pile. Think of general equilibrium, constrained optimization, rational expectation, supply-demand-equilibrium.
It has to be admitted, though, that Heterodoxy too has contributed a fair amount of confused stuff. Dave Taylor’s monetary communication PIDs are a case in point (see his previous posts on this blog).
This big heap of analytical rubble has to be shoved aside. What is most urgently needed is a new beginning on cleared ground. This reset requires a small number of absolutely transparent foundational propositions that are entirely free from hidden assumptions and, above all, from psychologism/sociologism. From historical experience we have learned that this dabbling in PsySoc is the bane of economics.
All this applies also to the theory of money. There is a subjective and an objective theory of money. The former is not much different from gossip, only the latter is of real interest. The fault of traditional Heterodoxy is that it could not get out of the PsySoc impasse. In marked contrast, Constructive Heterodoxy gives an objective and consistent account of how money and the diversity of financial markets emerge from the elementary monetary circuit (2015).
Orthodoxy and traditional Heterodoxy have been ditched. Constructive Heterodoxy is the only game in town.
Egmont Kakarot-Handtke
References
Kakarot-Handtke, E. (2015). Essentials of Constructive Heterodoxy: Financial Markets. SSRN Working Paper Series, 2607032: 1–33. URL
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2607032.
The fact that Egmont finds Dave Taylor’s stuff confusing doesn’t mean to say it is. It seems to be that Egmont neither understands the concepts Dave Taylor’s words refer to, nor that Shannon’s information science is not “PsySoc babble” but a fundamental, revolutionary, extraordinarily successful and entirely formal way of making sense of and of how brains work. Nor is it “traditional Heterodoxy”, for the simple reason that other heterodox economists as well as Egmont haven’t learned enough of what it is about to see the point of taking the trouble to become familiar with it.
It is not at all evident to me how Egmont’s equations can distinguish the past, present and future change dimensions mathematically captured in terms of current, integral and differential errors and symbolically as PID, thus the possibility of emergence in his model. In any case, there is no elementary monetary circuit. Money is not necessary for elementary economic reproduction, and when introduced generates not a simple but four monetary circuits linking production, distribution, consumption and development, the idea of money having to develop before it could come into general use.
With only natural language available here, Dave Taylor is left with the insuperable difficulties of trying to translate abstract pictures into words and providing relatively familiar examples in hope of sparking insight in people likely to see only the example. He can regret that, but it takes two to tango. Responding to Bruce Edmond’s helpful comment on this below, I’m talking primarily about scientific METHODS not familiar to economists, my models being examples simple enough to be taken as starting points for exploration and development.
Correction: “entirely formal way of making sense of THAT [i.e. “PsySoc babble”] and of how brains work”.
Re Egmont’s renewed attack on Keynes in response to Bruce, the point he apparently refuses to accept is that Keynes in 1935 was feeling his way to PID control (via unemployment as an indication of the accumulating – i.e. integrating – effects of error) before Shannon’s formal theory of control by means of error correction feedbacks and the Heaviside-based PID extension of it became available in 1948 and c.1964 respectively. He should be praised as a pioneer, not denigrated for using the only tools available to him.
With any model there will be a large number of unstated, background assumptions. This is especially true of social models (which includes economic models). One can never make them all explicit in any formal model, so if one is using a formal model some ‘ceteris paribus’ clauses are inevitable.
Natural language accounts get around this by utilizing the shared knowledge of the appropriate context (something I will blog about here in the future), but at the expense of those being fluid and vague. Thus such accounts are not entirely satisfactory and will necessarily be context-, culture- and time-dependent.
Formal models ARE important to enable scientists to unambiguously share and collaborate – which is why fields that use them often achieve more progress in the long term – BUT only if they select their models according to the evidence (evidence always trumping models). The trouble with the examples above is not the ‘ceteris paribus’ but the insufficiency of their rigorous correspondence to what is observed.
Sloppiness as economic methodology
Comment on ‘Ditch ‘ceteris paribus’!’
Bruce Edmonds asserts “Natural language accounts get around this [drawback of formal models] by utilizing the shared knowledge of the appropriate context ….”
This brings us almost verbatim back to Keynes who was a tireless proponent of the Cambridge School of Loose Verbal Reasoning.
“Another danger is that you may ‘precise everything away’ and be left with only a comparative poverty of meaning. … Such a problem was avoided, said Keynes, by Marshall who used loose definitions but allowed the reader to infer his meaning from ‘the richness of context’.” (Coates, 2007, p. 87)
In other words, the reader is encouraged to substitute almost any meaning he likes. The result is well-known. Keynes loose verbal reasoning triggered an enthusiastic exegesis movement that circled for some decennia around the question ‘What Keynes really meant?’ Predictably, the question has never been answered. Richness of meaning only generated a wealth of blah.
But Keynes made also one very precise statement in his General Theory, viz.
“Income = value of output = consumption + investment. Saving = income – consumption. Therefore saving = investment.” (Keynes, 1973, p. 63)
Unfortunately, this simple syllogism contains a fundamental conceptual error (2011) which makes nonsense of all I=S-models beginning with Hicks’s IS-LM and straightforwardly continuing to Krugman’s and Wren-Lewis’s confused blogs. After more than 75 years Keynes’s definitional sloppiness is still with us.
Since Adam Smith, economics has never been in any danger to ‘precise everything away.’ To the contrary, sloppiness enabled a senseless productivity. Neither Walrasian pseudo-rigor nor Keynesian looseness has produced anything that satisfies the scientific standards of material and formal consistency.
The call for more natural-language economics can only prolong the agony.
Egmont Kakarot-Handtke
References
Coates, J. (2007). The Claims of Common Sense. Moore, Wittgenstein, Keynes and the Social Sciences. Cambridge, New York, NY, etc.: Cambridge University Press.
Kakarot-Handtke, E. (2011). Why Post Keynesianism is Not Yet a Science. SSRN Working Paper Series, 1966438: 1–20. URL http://ssrn.com/abstract=1966438.
Keynes, J. M. (1973). The General Theory of Employment Interest and Money. The Collected Writings of John Maynard Keynes Vol. VII. London, Basingstoke: Macmillan.
“But Keynes made also one very precise statement in his General Theory …”.
Unfortunately for Egmont’s thesis, this statement, as I’ve pointed out before, is not Keynes’s conclusion but a tenet of economic orthodoxy that he is going to reject. The quotation continues:
“Thus ANY set of conclusions which satisfy the above conditions leads to the same conclusion. It is only by denying the validity of one or the other of them that the conclusion can be avoided”.
Again, Bruce was hardly defending sloppy terminology. In Shannon’s analysis we get away with communicating in natural language because it contains so much redundant [e.g. contextual] information that we can usually recognise and allow for e.g. typos. But the same thing can be true in mathematics. Astronomy only took off when Kepler relaxed the assumption that orbits must be circular by showing they could be elliptical. The right question is not, have we accounted for everything, but have we got all the information we need? Do you need a geometrically accurate map of London to travel on the underground? No, we use a much simpler topological map which shows all the lines in the right circular order and the stations in the right linear order. Likewise in the mapping of electrical systems: for most purposes a topological circuit diagram suffices. One can use a geometrical map, but the price of its greater precision is inefficiency and redundancy.