Archive for the ‘Forecasting’ Category

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Evaluating prophecy

Published by peter on 2009-01-19 in Argumentation, Computer technology, Decision theory, Forecasting, Prophecy and Uncertainty. 0 Comments

With the mostly-unforeseen global financial crisis uppermost in our minds, I am led to consider a question that I have pondered for some time:   How should we assess forecasts and prophecies?   Within the branch of philosophy known as argumentation, a lot of attention has been paid to the conditions under which a rational decision-maker would accept particular types of argument.

For example, although it is logically invalid to accept an argument only on the grounds that the person making it is an authority on the subject, our legal system does this all the time.  Indeed,  the philosopher Charles Willard has argued that modern society could not function without most of us accepting arguments-from-authority most of the time, and it is usually rational to do so.  Accordingly, philosophers of argumentation have investigated the conditions under which a rational person would accept or reject such arguments.   Douglas Walton (1996, pp. 64-67) presents an argumentation scheme for such acceptance/rejection decisions, the Argument Scheme for Arguments from Expert Opinion, as follows:

  • Assume E is an expert in domain D.
  • E asserts that statement A is known to be true.
  • A is within D.

Therefore, a decision-maker may plausibly take A to be true, unless one or more of the following Critical Questions (CQ) is answered in the negative:

  • CQ1:  Is E a genuine expert in D?
  • CQ2:  Did E really assert A?
  • CQ3:  Is A relevant to domain D?
  • CQ4:  Is A consistent with what other experts in D say?
  • CQ5:  Is A consistent with known evidence in D?

One could add further questions to this list, for example:

  • CQ6:  Is E’s opinion offered without regard to any reward or benefit upon statement A being taken to be true by the decision-maker?

Walton himself presents some further critical questions first proposed by Augustus DeMorgan in 1847 to deal with cases under CQ2 where the expert’s opinion is presented second-hand, or in edited form, or along with the opinions of others.
Clearly, some of these questions are also pertinent to assessing forecasts and prophecies.  But the special nature of forecasts and prophecies may enable us to make some of these questions more precise.  Here is my  Argument Scheme for Arguments from Prophecy:

  • Assume E is a forecaster for domain D.
  • E asserts that statement A will be true of domain D at time T in the future.
  • A is within D.

Therefore, a decision-maker may plausibly take A to be true at time T, unless one or more of the following Critical Questions (CQ) is answered in the negative:

  • CQ1:  Is E a genuine expert in forecasting domain D?
  • CQ2:  Did E really assert that A will be true at T?
  • CQ3:  Is A relevant to, and within the scope of, domain D?
  • CQ4:  Is A consistent with what is said by other forecasters with expertise in D?
  • CQ5:  Is A consistent with known evidence of current conditions and trends in D?
  • CQ6:  Is E’s opinion offered without regard to any reward or benefit upon statement A being adopted by the decision-maker as a forecast?
  • CQ7:  Do the benefits of adopting A being true at time T in D outweigh the costs of doing so, to the decision-maker?

In attempting to answer these questions, we may explore more detailed questions:

  • CQ1-1:  What is E’s experience as forecaster in domain D?
  • CQ1-2: What is E’s track record as a forecaster in domain D?
  • CQ2-1: Did E articulate conditions or assumptions under which A will become true at T, or under which it will not become true?  If so, what are these?
  • CQ2-2:  How sensitive is the forecast of A being true at T to the conditions and assumptions made by E?
  • CQ2-3:  When forecasting that A would become true at T, did E assert a more general statement than A?
  • CQ2-4:  When forecasting that A would become true at T, did E assert a more general time than T?
  • CQ2-5:  Is E able to provide a rational justification (for example, a computer simulation model) for the forecast that A would be true at T?
  • CQ2-6:  Did E present the forecast of A being true at time T qualified by modalities, such as possibly, probably, almost surely, certainly, etc.
  • CQ4-1:  If this forecast is not consistent with those of other forecasters in domain D, to what extent are they inconsistent?   Can these inconsistencies be rationally justified or explained?
  • CQ5-1: What are the implications of A being true at time T in domain D?  Are these plausible?  Do they contradict any known facts or trends?
  • CQ6-1:  Will E benefit if the decision-maker adopts A being true at time T as his/her forecast for domain D?
  • CQ6-2:  Will E benefit if the decision-maker does not adopt A being true at time T as his/her forecast for domain D?
  • CQ6-3:  Will E benefit if many decision-makers adopt A being true at time T as their forecast for domain D?
  • CQ6-4:  Will E benefit if few decision-makers adopt A being true at time T as their forecast for domain D?
  • CQ6-5:  Has E acted in such a way as to indicate that E had adopted A being true at time T as their forecast for domain D (eg, by making an investment betting that A will be true at T)?
  • CQ7-1:  What are the costs and benefits to the decision-maker for adopting statement A being true at time T in domain D as his or her forecast of domain D?
  • CQ7-2:  How might these costs and benefits be compared?  Can a net benefit/cost for the decision-maker be determined?

Automating these questions and the process of answering them is on my list of next steps, because automation is needed to design machines able to reason rationally about the future.   And rational reasoning about the future is needed if  we want machines to make decisions about actions.
References:
Augustus DeMorgan [1847]: Formal Logic.  London, UK:  Taylor and Walton.
Douglas N. Walton [1996]:  Argument Schemes for Presumptive Reasoning. Mahwah, NJ, USA: Lawrence Erlbaum.
Charles A. Willard [1990]: Authority.  Informal Logic, 12: 11-22.

The second time as farce

Published by peter on 2008-10-15 in Economics and Forecasting. 0 Comments

Karl Marx was correct, it seems, in predicting that capitalism would suffer recurring crises.  What he seems to have overlooked is the impact of his own predictions (with companies and governments taking steps to eliminate or ameliorate the worst effects of the system), and capitalism’s adaptability.  With the socialization of the means of exchange taking place in much of the western world this month, capitalism has shown that it is even willing to adopt its own antithesis in order to survive.

Macro-economic models

Published by peter on 2008-05-13 in Decision theory, Economics and Forecasting. 0 Comments

The New Zealand-born economist, Bill Phillips, is best known for identifying an empirical relationship between a country’s inflation rate and its unemployment, the so-called Phillips curve.  However, before becoming an economist, Phillips had been an engineer, and in 1949 he built one of the first models of a national economy, the MONIAC.  MONIAC used flows of coloured water to represent money flows through an economy, and perhaps explains (or is a reflection of) traditional economics’ obsession with distinguishing stocks from flows.
In the 1970s, the Australian cartoonist Bruce Petty also built a physical model of a national economy, but this time with seats for several human operators, representing variously The Government, The Unions, Big Business, etc.   Instead of the hydraulic flows used by Phillips, Petty’s model used mechanical levers and pulleys, which impacted in convoluted ways on the machine and on the other operators.   This model looked something built by Heath Robinson or Rube Goldberg, and was immense fun to watch it at work.   I’ve not yet been able to find a video of Petty’s model at work.

Sexapedalianism

Published by peter on 2008-04-13 in Culture, Decision theory, Economics and Forecasting. 0 Comments

Statistician Dennis Lindley wrote a book called “Making Decisions” which included the stunningly-arrogant sentence: “The main conclusion [of this book] is that there is essentially only one way to reach a decision sensibly.” He justifies this outrageous claim, contrary to all human experience and a moment’s reflection, by saying that, “any deviation from the precepts is liable to lead the decision-maker into procedures which are demonstrably absurd — or as we shall say, incoherent.” (page vii, second edition, 1985). There follows an account of maximum-expected utility decision theory, which is justified in the standard way using Dutch Book arguments (considerations of certain infinite gambles).

I have never trusted these Dutch Book arguments, first because we all live in a finite world, and so games in which one party is guaranteed to win after an infinitely-large time strike me as games selling pie-in-the-sky. Everyone is rich eventually when investing in a Ponzi scheme, also. And second, gambling is such a socially- and culturally-embedded practice that I cannot possibly conceive how it could be used to justify decision-making procedures claiming universal validity. (For a start, to gamble you need to believe that events in the universe are not pre-determined, something which perhaps half of humanity does not currently believe.) The statistician Cosma Shalizi over at Three-Toed Sloth has a nice parody of the advice of decision-theory ideologues here.

A: Hey, you over there, the one walking! You’re doing it wrong.
B: Excuse me?
A: You’re only using two feet! You should keep at least three of your six in contact with the ground at all times.
B: …
A: Look, it’s easily proved that’s the optimal way to walk. Otherwise you’d be unstable, and if you were walking past a Dutchman he could kick one of your legs with his clogs and knock you over and then lecture you on how to make pancakes.
B: What? Why a Dutchman?
A: You can’t trust the Dutch, they’re everywhere! Besides, every time you walk it’s really just like running the gauntlet at Schiphol.
B: It is?
A: Don’t change the subject! Walking like that you’re actually sessile!
B: I don’t seem to be rooted in place…
A: It’s a technical term. Look, it’s very simple, these are all implications of the axioms of the theory of optimal walking and you’re breaking them all. I can’t get over how immobile you are, walking like that.
B: “Immobile”?
A: Well, you’re not walking properly, are you?
B: Your theory seems to assume I have six legs.
A: Yes, exactly!
B: I only have two legs. It doesn’t describe what I do at all.
A: It’s a normative theory.
B: For something with six legs.
A: Yes.
B: I have two legs. Does your theory have any advice about how to walk on two legs?
A: Could you try crawling on your hands and knees?

The post-modern corporation

Published by peter on 2008-03-09 in Forecasting, Market planning, Planning and Prophecy. 0 Comments

Anyone who has done any strategic planning or written a business case knows that planning requires one to forecast the future.  If you want to assess the financial viability of some new product or company, you need to make an estimate of the likely revenues of the company, and this requires making a prognosis of the level and nature of demand for whatever it is the company plans to provide.   “Taking a view on the future” is what the M&A people call this.
The problem is that the future is uncertain and different people may have different views of it.   There are usually many possible views one could take, and stakeholders are not always able to agree on which is the most likely.  Financial planners typically deal with this uncertainty by developing a small number of scenarios: often called a best case,  an average case, and a worst case.    These scenarios are very rarely ever the actual “best” or the actual “worst” that the planners could conceive.  More typically, they are the best or worst “plausible” cases.  Similarly, the middle case may not be average in any sense of the word, but simply a case the planners happen to favour that is somewhere between the best and worst.   Often the average case is the best the planners think they can get away with, and they contrast this with an outlandish upside and a still-profitable downside.   As with other human utterances (eg, speeches and published papers), effective business planners take into account the views of their likely audience(s) when preparing a business plan.
For telecommunications companies operating in a regulated environment, there is a further wrinkle:  the fifth “P” of telecoms marketing, Permission.  To gain regulatory approval or an operating licence for a new service, telcos in many countries need to make a business case to the regulatory agency.  Here, the regulators may have their own  views of the future.  Quite often, governments and regulators, especially those in less developed countries, feel they are behind in technology and believe that their country has a vast, untapped market ready for the taking.   Sometimes, governments have public policy or even party-political reasons for promoting a certain technology, and they want the benefits to be realized as quickly as possible.   For these and other reasons, governments and regulators often have much more optimistic views of likely demand than do the companies on the ground.
Thus, we have the situation where a company may prepare different business plans for different stakeholders, each plan encoding a different view of the future:  an optimistic plan for the regulator, a parsimonious plan for a distribution partner and yet another for internal use.   Indeed, there may be different views of the future and thus different plans for different internal audiences also, for reasons I will explain in my next post.   Living with uncertainty, the post-modern corporation treats its view of the future as completely malleable — something which can be constructed and re-constructed as often as occasion or audience demands.
In my next post, I’ll talk about the challenges of planning with multiple views of the future, and give some examples.
Reference:  This post was inspired by Grant McCracken’s recent post on Assumption-Hunting.