Home > Uncategorized > Model uncertainty and ergodicity

Model uncertainty and ergodicity

from Lars Syll

Post Keynesian authors have offered various classifications of uncertainty … A common distinction is that of epistemological versus ontological uncertainty, with the former depending on the limitations of human reasoning and the latter on the actual nature of social systems …

Uncertainty and reflexivity — two things missing from Krugman's economics |  LARS P. SYLLModels of ontological uncertainty tend to hinge on the existence of information that is critical to the decision-making task. Fundamental uncertainty occurs in “situations in which at least some essential information about future events cannot be known at the moment of decision because this information does not exist and cannot be inferred from any existing data set” (Dequech 1999, 415-416). For Davidson (1991, 131), “true” uncertainty arises when “the decision maker believes that no information regarding future prospects exists today and therefore the future is not calculable.”

In the model-based view of uncertainty, by contrast, it is not the existence of information that determines uncertainty, but the credibility of the model(s) used to encode available information. By focusing on the existence of information, or its completeness, these Post Keynesian accounts of ontological uncertainty implicitly accept the possibility that if economic agents had sufficient information they could apply that information to a model without uncertainty. Yet a suitably complex deterministic system … can prompt model uncertainty even if future outcomes are in principle knowable … Model uncertainty is thus epistemological rather than ontological in nature. It occurs even in environments with stable data generating processes.

Owen F. Davis

An interesting paper that merits a couple of comments.

To understand real-world ”non-routine” decisions and unforeseeable changes in behavior, ergodic probability distributions are of no avail. In a world full of genuine uncertainty – where real historical time rules the roost – the probabilities that ruled the past are not those that will rule the future.

Time is what prevents everything from happening at once. To simply assume that economic processes are ergodic and concentrate on ensemble averages – and a fortiori in any relevant sense timeless – is not a sensible way of dealing with the kind of genuine uncertainty that permeates open systems such as economies.

What is important in recognizing that real social and economic processes are nonergodic is the fact that uncertainty – not risk – rules the roost. That was something both Keynes and Knight basically said in their 1921 books. Thinking about uncertainty in terms of “rational expectations” and “ensemble averages” has had seriously bad repercussions on the financial system.

Knight’s uncertainty concept has an epistemological founding and Keynes’ definitely has an ontological founding. Of course, this also has repercussions on the issue of ergodicity in a strict methodological and mathematical-statistical sense. I think Keynes’ view is the most warranted of the two.

The most interesting and far-reaching difference between the epistemological and the ontological view is that if one subscribes to the former, the Knightian view, you open up to the mistaken belief that with better information and greater computer power we somehow should always be able to reduce model misspecification and/or invent new and better models to calculate probabilities and describe the world as an ergodic universe. As Keynes convincingly argued, that is often (unless we think we actually live our lives in Savage’s “small world”) not ontologically possible.

To Keynes, the source of uncertainty was in the nature of the real — nonergodic — world. It had to do, not only — or primarily — with the epistemological fact of us not knowing the things that today are unknown, but rather with the much deeper and far-reaching ontological fact that there often is no firm basis on which we can form quantifiable probabilities and expectations at all.

Sometimes we do not know because we cannot know. 

  1. deshoebox
    December 20, 2022 at 3:13 am

    Speaking now as an ordinary human being, I would like to say that (a) I do not base my decisions on my assessments of the probabililty of various possible outcomes, and (2) I do not think this is even possilble. I am aware of the existence and perhaps the prevalence of non-transitive preferences, of course, which would probably make a joke of my attempts at probabilitiy comparisons, if I were capable of them. But no, even if I had an instantaneous command of all the information in the universe (it’s close because I do have a recent-model smart phone) I would not necessarly make better decisions. I would still choose to spend my last thousand dollars on liquor and a really good guitar, for example, instead of buying food for my wife and children. I am, as I have said, an ordinary human being.

  2. yoshinorishiozawa
    January 9, 2023 at 7:23 am

    For some Post Keynesian economists, uncertainty is a holy word. In front of that, economists can do nothing but to worship. This is a new cult that appeared roughly in 1960’s about a quarter century after the publication of The General Theory of Employment, Interest, and Money. Don Patinkin traced the emergence of uncertainty emphasis which goes beyond the level it deserves. I cite Patinkin (1990) On different interpretations of the General Theory, Journal of Monetary Economics 26: 205-242. It was reprinted in Snowdon and Vane (eds.) A Macroeconomics Reader, Routledge, London and New York. I cite from the reprinted version.

    [I]t is just about that time that such interpretations do begin to appear. I am referring in particular to Sidney Weintraub’s (1961) Classical Keynesianism, Monetary Theory, and the Price Level and to George Shackle’s survey article of the same year on ‘Recent Theories Concerning the Nature and Role of Interest’. (Patinkin 1997[1990], p.64)

    Let me finally note that the presentation of the nonprobabilistic nature of economic uncertainty can hardly be considered to be a contribution of the General Theory: it had been emphasized long before by Frank Knight (1921) in his classic Risk, Uncertainty, and Profit. Furthermore, as Samuelson (1946:320) observed many years ago, the General Theory ‘paves the way for a theory of expectations, but it hardly provides one’ (see also Hart 1947). (Patinkin 1997[1990], p.66)

    This [Post Keynesian economics] is actually only in part concerned with the interpretation of the General Theory. In this context it is largely a combination of George Shackle’s interpretation of the book in terms of the overriding impact of uncertainty on economic behavior, and Sidney Weintraub’s interpretation in terms of the major importance in the book of the aggregate supply curve and of the analysis of the determination of the price level. (Patinkin 1997[1990], p.67)

    In these circumstances the obscurities and loose ends of the General Theory provided ample opportunities for different interpreters with different—and quite familiar—motivations: in particular, some interpreters wanted to invoke the authority of a canonical text in support of their prior theoretical views; and others wanted to invoke the authority of a canonical figure in support of their prior political views. Milgate, Shackle and Weintraub were clearly motivated by the first of these considerations. (Patinkin 1997[1990], p.79)

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