Von Neumann-Morgenstern Lecture II. Utility and different views of risk Knightian – Frank Knight Risk – known probabilities of events Uncertainty – unknown.

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Presentation transcript:

Von Neumann-Morgenstern Lecture II

Utility and different views of risk Knightian – Frank Knight Risk – known probabilities of events Uncertainty – unknown or unknowable probabilities Von Neumann – Morgenstern Axiomatic treatment Consumers maximize expected utility

Savage Consumers maximize subjective utility Arrow – Debreu State – preference securities

Numerical Stuff In the preceding lecture, we found the expected utility of a gamble that paid $150,000 with probability of.6 and $50,000 with probability.4. Assuming a r=.5, the power utility function yields a certainty equivalent of $103,569.

Let’s work on a slightly different problem, again assume that we have a risky gamble that pays $150,000 with some probability p and $50,000 with probability (1-p). I assert that we can find a p that makes the decision maker indifferent between the risky gamble and a certain payoff of $108,000. Naturally, we assume that p is higher than.6 (why?).

Using our power utility function, we know that Mathematically, the probability then becomes

Changing the problem slightly, assume that the payoffs are $150,000 with probability.6 and $50,000 with probability.4. What is the r required to make the certainty equivalent $108,000? Our conjecture is that this risk aversion is less than the original risk aversion of.5 (why?).

Borrowing from the above analysis, the problem this time is slightly different As long as r does not equal 1, we can simplify the problem and write it in implicit functional form as:

Von Neumann and Morgenstern The conjectures under Von Neumann and Morgenstern are actually close to the first problem. Assume that you have three points A, B, and C. Further, assume that points B and C represent a risky gamble with probabilities.50,.50.

The producer can tell you whether he prefers the risk-free point A and the risky gamble B/C. Rule out the cases where A is preferred to both B and C and B and C are preferred to A.

Mathematically, either A is preferred to the gamble or lottery between B and C: or the lottery is preferred to A

As a second postulate, as depicted in the previous example, we can define a probability that makes the lottery indifferent with the certain payoff.

Conceptual Structure of the Axiomatic Treatment of Numerical Utilities In an axiomatic treatment, we want to propose a set of axioms or basic notions that are acceptable and show that a conclusion follows from direct logic based on these axioms or notions. In this case, we want to show that there exists a utility mapping U(Y) such that if X is preferred to Z then U(X)>U(Z).

Axioms: u > v is a complete ordering of U.  For any two u, v one and only one of the three following relations hold

 u > v, v > w implies u > w. Basically, the axiom assumes that preferences are transitive. Ordering and Combining 

Algebra of Combining  where . This is an iterated gamble.