This paper in the Quarterly Journal of Economics was Keynes' rebuttal against some of the criticism's of his 1936 magnum opus The General Theory of Employment, Interest and Money. Keynes begins by addressing some of the issues concerning his liquidity-preference theory, which was said to lack originality and supposedly did not constitute and improvement over orthodox theory. After replying to his critics and agreeing on certain points, Keynes begins re-expressing some of the main points from the book that he had considered as most vital. Firstly Keynes disagrees with the so called long-run approach which had been employed by classical economists, where we should mention, that Keynes used the word classical to describe both classical political economists and the neoclassical marginal economists of the late 19th and early 20th century. Apart from the fact that those authors had mainly imagined a world of full employment of all resources (mind you, it's not like the Amazon rainforest was crying out to be »employed«, unemployment of labour is the only problematic form of unemployed resources), they had also envisioned a very simplified economic process one where uncertainty has been effectively reduced to risk. Once this is done we can employ methods of utilitarian Benthamite calculus (with the appropriate probability distributions taken into account!), which allows us to glare into the future, thereby reducing the future to a mere reflection of today. However, as we know, not all change is quantitative and indeed the biggest change in the economic system is often qualitative in nature which makes this sort of analysis quite useless both as a means of predicting economic trends and as a metaphore to explain how the economy works. In a very nice passage Keynes explains the difference between wholly uncertain knowledge and probable knowledge:
»By "uncertain" knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is only probable. The game of roulette is not subject, in this sense, to uncertainty; nor is the prospect of a Victory bond being drawn. Or, again, the expectation of life is only slightly uncertain. Even the weather is only moderately uncertain. The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence, or the obsolescence of a new invention, or the position of private wealth‑owners in the social system in 1970. About these matters there is no scientific basis on which to form any calculable probability whatever. We simply do not know. Nevertheless, the necessity for action and for decision compels us as practical men to do our best to overlook this awkward fact and to behave exactly as we should if we had behind us a good Benthamite calculation of a series of prospective advantages and disadvantages, each multiplied by its appropriate probability, waiting to be summed.«
Very few economists take this distinction seriously, for should this be done, a lot of our existing body of labour would find its value plumetting downwards to the last circle of hell, by which I mean that it would get relegated to some obscure chapter in a history of economic thought textbook. I believe that at least in terms of formal models, making use of dynamic systems, where very small changes in parameters produce wild swings in the underlying values of variables is preferable to the current state of affairs. Yet, I suppose, that even in that case, the inherent uncertainty of economic processes would not be properly explained, all that would be shown is how potentially unstable the systems are and how pretending otherwise is foolhardy. However I believe that as metaphores or didactic tools, such models, even though they are essentially deterministic, would be preferable to our current pre-occupation with risk and probability distributions, which are essentially still deterministic, for once we take these distributions for granted – which is to say once we assume they are a good representation of the underlying reality – they effectively reduce uncertainty to a non-existant category. Interestingly enough, no matter how many times these methods prove insufficient when it comes to prognosis, the profession still believes that one day, they will »crack the code«, all we need is the right distribution (the de-tails are in the tails, so to speak ;) ) coupled with correct parameter values, and we're good to go. Essentially the method employed is still based on the same assumption that Keynes mentions in his paper:
»We assume that the present is a much more serviceable guide to the future than a candid examination of past experience would show it to have been hitherto.«
If the economic process is too chaotic, for lack of a better word and if, as Keynes had presumed, we know very little about our future then all the utility calculations that are done in economics courses all over the world, can only make sense in an already stocked supermarket when we're deciding whether to buy a banana or an apple. As a metaphore for a supermarket this sort of methodology would seem to be quite adequate, the problem is that we've extrapolated the same metaphore to the whole fabric of our economic, and indeed the whole of our social reality as well. So now we know why I might go for an apple instead of a banana, but can we then go a step further and use the same methodology to explain accumulation of wealth, social relations and other macroeconomic conundrums? What does this sort of approach, without taking it to a level of a tautology, tell us about how the supermarket got stocked in the first place? What does it tell us about the future without actually presuming to know the future?
Another practical impossibility and a potential danger is that this approach requires perfect information about today and tomorrow. Obviously neither of those two goals can be achieved, but when comes to the former, at least we can strive to know as much as possible. This is why it should come as no surprise that empirically minded individuals find themselves so immersed in the dominant neoclassical paradigm and why also, out of all the social scientists, it was economists who were least troubled by the spying scandals, because information is good, because the more you have, the more likely you will be able to use the existing metaphore to explain how the apples and bananas got into the supermarket in the first place. Even with all the information about today, however, this same approach can explain only in ex-post fashion why I, for example, like (or at least buy and use) smartphones. Yet, perhaps, with chips monitoring our dreams and thoughts, this obstacle too, will have eventually become a thing of the past and we will live in a glorious world where a giant Google supercomputer will be able to devise new theories on particle physics by combining the knowledge of every inhabitant of the Earth, even Kim Kardashian!
So you see, metaphores can get a life of their own and they can be pretty dangerous. They can also be pretty fun, imagine a centrally planned Google-run world, devised, among others, by these very same empirically minded economists on the basis of utilitarian calculus with the underlying principles of »free enterprise«, »free markets«, »freedom of choice« and just freedom in general, cuz for an economic agent (yes, I am looking at you!) maximizing her or his utility function, there's never enough of freedom, am I right? The Hoff knows:
 It should be mentioned, however, that these qualitative changes are often understood, or at least they partially reveal themselves, in the form of increased »productivity« via technological change.
 This also explains why new institutional economics and behavioural economics aren't all that new or revolutionary; they merely express, by observing some additional empirical facts, that certain institutional (cultural) and genetic traits, respectively, will make me prefer an apple to a banana.
 Again, it is not as if the future is actually presumed to be known, that would be far too pedestrian, instead we make use of probabilistic calculus and the future is known once we know the underlying probability distributions.