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Risk, Uncertainty and Profit by Knight - Book Report/Review Example

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This paper aims to discuss the theory of Frank Knight and his distinction between risk and uncertainty. It also aims to prove through mathematical inquiry to what extent long-term investment appraisal based on discounting techniques is rendered a futile exercise in the valuation of investments.
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Risk, Uncertainty and Profit by Knight
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Download file to see previous pages At one end is pure risk, sometimes called actuarial risk, in which situation probabilities are capable of being exactly determined on the basis of hard, physical data. At the other end of the continuum is pure uncertainty that, according to Knight, defies analysis. Somewhere in between the two extremes fall most random variables that are encountered in economic problems, depending on their relative uncertainties. These differentiations, however, apparently is not understood or accepted by many researchers due to the apparent confusion between the two concepts in many economic studies today. Methodologies developed for the case of pure risk are often made to apply on problems that are concerned with uncertainty (Taylor, 2002).
To draw distinctions between the concepts of risk and uncertainty, it must be kept in mind that probabilities under condition of pure risk are determinable, while those under condition of pure uncertainty are unmeasurable and therefore unanalyzable; the two are thus not the same, despite the fact that they are interchangeably used in many economic studies.
In moving from the point of pure risk to that of pure uncertainty, three economic modelling issues become apparent, according to Taylor (2002). First, as uncertainty increases, it becomes increasingly difficult to conceptualize and define random variables. In such cases, the set of random variables one analyst would tend to consider as applicable in a case would tend to differ significantly from the set of random variables another analyst would believe appropriate for the same case. Which one of the two conceptual models or sets of random variables is more appropriate becomes a matter of opinion for lack of defining criteria, and will continue to remain a contentious issue until the uncertainties surrounding the case are diminished or removed entirely.
The second issue is that of insurance; in conditions of pure risk, many insurance companies would be able to build a viable market, because determinate risk is insurable, and in fact, it is the presence of risk that makes insurance necessary. However, in the case of pure uncertainty, no insurance firm would venture to extend the coverage. In fact, as uncertainty increases along the continuum, the cost of premiums would move to higher and higher levels until the point where they present a moral hazard.
The third issue that creates problems for modelling is that as uncertainty increases, the estimation or specification of probabilities become increasingly involved and difficult, whether objectively or even subjectively, as to be almost arbitrary. While, as Taylor points out, frequentists and Bayesian theorists contend that no matter how high the uncertainty, a probabilities specification could always be subjectively arrived at, this has understandably been called into question in the ensuing philosophical debates.
In contrast with Taylor's depiction of Knight's theory as a two-attribute, linear, continuum, Norman and Shimer (1992) explains that Knight actually considered three types of probability: aside from uncertainty and risk, there is also statistical probability. In differentiating the ...Download file to see next pagesRead More
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