421. Risk versus uncertainty
I want to make a distinction that has been lurking below the surface in some of the previous posts in this RiskWi$e series: risk versus uncertainty.
I’ve primarily used the word “risk” so far, but sometimes I’ve really been talking about “uncertainty”, or a mix of the two.
What is the difference? Strictly speaking, “risk” refers to a situation where we don’t know what the outcome will be, but we do know the probabilities of different outcomes. Examples include rolling dice or tossing a coin. If we rolled two dice, the result could be anything between 2 and 12, but if we rolled them a million times, we know with high accuracy what the distribution of results would be.
On the other hand, “uncertainty” refers to a situation where we don’t know the probabilities of different outcomes. For example, if Dave the risk-averse farmer adopts a new wheat variety, he has access to the results of research trials for that variety, but he doesn’t know exactly how it will perform on his own farm. He can combine the research trial results with his own experience of growing other wheat varieties, to make a judgment about how it will perform for him, but it’s just a judgment and some uncertainty remains – he doesn’t know the actual probability distribution.
As he gets experience growing the new variety, his uncertainty about its performance decreases. If he keeps growing it for long enough, he’ll have a good idea of the probability distribution of its yield, although, depending on the type of practice or technology, that can take quite a while (see PD415 on “Learning about the riskiness of a new farming practice”).
So for most farming decisions, the farmer faces a mix of risk and uncertainty. Over time, with experience, uncertainty about a farming practice decreases, and a larger share of what is left is risk.
How does this affect decision making? I recently read a piece that said that uncertainty means that there is no basis for making a decision. In an extreme situation, where you really know absolutely nothing about a practice, that would be true, but in a practical farming situation that is never the case. There is enough information to make an educated guess.
The main difference between risk and uncertainty in decision making is the source of probability numbers to use. Under risk, the probabilities are objective and known precisely, while under uncertainty, it comes down to a subjective judgment by the decision maker. In a sense, the probabilities under uncertainty are not really probabilities – they are something like a strength of feeling.
But when it comes to making decisions, this difference does not affect the decision process. If doing Decision Analysis (see PD420), the two types of probabilities are used in exactly the same way in the calculations, or in the intuitive decision process.
Further reading
This is #14 in my RiskWi$e series. Read about RiskWi$e here or here.
The RiskWi$e series:
405. Risk in Australian grain farming
406. Risk means probability distributions
408. Farmers’ risk perceptions
409. Farmers’ risk preferences
410. Strategic decisions, tactical decisions and risk
412. Risk aversion and fertiliser decisions
413. Diversification to reduce risk
414. Intuitive versus analytical thinking about risk
415. Learning about the riskiness of a new farming practice
416. Neglecting the risks of a project
418. Hedging to reduce crop price risk
419. Risk premium
420. Systematic decision making under risk
421. Risk versus uncertainty (this post)
422. Risky farm decision making as a social process
423. Risk aversion versus loss aversion, part 1
424. Risk aversion versus loss aversion, part 2
Dear Professor, a few years ago I took a course with you (Agriculture, economy and nature) that I found excellent, as did the Pannell Discussions, cordial greetings from Argentina.
Hi David. I take a slightly different view of this issue. I like the Knight (1921) view of uncertainty which you hint at (situations of risk there is a known or knowable probability distribution, and uncertainty exists where it is not possible to specify knowable probabilities), with a distribution of this. This is what you are also talking about with ambiguity as an intermediate state between risk (where information is reliable and all but one distribution is ruled out) and ignorance (where no information exists and no distributions are ruled out). There is good evidence that ambiguity avoidance is more important than risk avoidance in predicting behaviour. However, I like the Emery & Trist (1965) & later developments that distinguish categorise the types of environments ranging from ‘placid random’ to ‘turbulent field’. The two examples of turbulent field for me were the collapse of the Reserve Price Scheme, which none of the farmer I interviewed at the time even considered in their decision making & the contaminated fuel issue for light planes a little after (not a farming one). I believe from a strategic viewpoint we need to at least consider turbulent field environments (the earth moves) in planning & if we do that then we can be more risk neutral when it comes to the decisions you are talking about above. As March & Simon (1958) said: ‘In the case of uncertainty, the definition of rationality becomes problematic’.
Thanks Roy. I didn’t mention Knight, but my take on uncertainty is Knightian.
I’d like to see that evidence (that ambiguity avoidance is more important than risk avoidance in predicting behaviour). Can you point me at references?
Certainly agree that a “turbulant” environment makes uncertainty higher. Yes, people tend not to consider the possibility of big fundamental changes, like the RPS collapse.
I’ve not read March and Simon (1958). If they mean complete uncertainty, fair enough. But almost all decisions are not made under complete ignorance. We know some things but not everything. There is still some uncertainty. In that context, I don’t really agree with their quote.