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Consistent choice

Explore different decision rules and principles for making consistent choices in the face of uncertainty. Consider factors such as environmental conditions and subjective probabilities to maximize expected value and minimize regret.

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Consistent choice

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  1. Consistent choice Fred Wenstøp Fred Wenstøp: Consistent choice

  2. Assumptions • State of nature • Environmental conditions (national or international economy, etc.) that will influence the outcome of our decisions • Nature is blind • Nature determines the future state without paying attention to our choices • if this is not the case, we face an opponent instead of nature, and we are into game theory Fred Wenstøp: Consistent choice

  3. Decision tables • Alternative actions are choices between rows • Possible states of nature are columns • Theinterior numbers are payoffs • Money or utilities • Compact form, but it can not show sequential decisions • Use decision trees... Fred Wenstøp: Consistent choice

  4. Strict uncertainty • Strict uncertainty • the decision maker has no inkling of an idea as to how likely the various states of nature are, and is therefore completely unable to asses probabilities • This is not uncommon in practise • Experiment • you are offered the choice between two envelopes • you are told that one contains twice as much money as the other • you are strictly uncertain about how much money it can be • you select one. It contains NOK 200. You may swap. Should you?? Fred Wenstøp: Consistent choice

  5. Strict uncertainty: decision rule 1Wald’s maximin criterion • Choose the action with the highest security level • An action's security level is the worst thing that can happen under that action Fred Wenstøp: Consistent choice

  6. Strict uncertainty: decision rule 2Hurwicz’s optimism-pessimism index • In addition to the security levels, compute the optimism levels (Maxima) • Decide on a pessimism weight a, a=0.1 • Choose the action with the highest combined index Fred Wenstøp: Consistent choice

  7. Strict uncertainty: decision rule 3Savage’s minimax regret • Transform the outcome table into a regret table • For each column, subtract the maximum of that column from all the numbers in the column • Find the security level of each action (regretwise) • Choose the action with the lowest security level • Remember: regrets should be small Fred Wenstøp: Consistent choice

  8. Savage’s minimax regretExample Fred Wenstøp: Consistent choice

  9. Savage’s inconsistency Fred Wenstøp: Consistent choice

  10. Strict uncertainty: decision rule 4Laplace's principle of insufficient reason • If you do not anything about the probabilities of the different states of nature, then all probabilities are identical • Choose the action with the highest expected outcome Fred Wenstøp: Consistent choice

  11. Strict uncertainty impossibility theorem • Theorem: No decision rule can satisfy a reasonable set of consistency axioms • The theorem shows that strict uncertainty is void of meaning • it is seen in the envelop paradox: an assumption of strict uncertainty leads to inconsistent behaviour • We must introduce probabilities Fred Wenstøp: Consistent choice

  12. Subjective probability • Uncertainty • Can be represented as subjective probability • measured by referring to objective probabilities created by tossing of coins, dice, etc. • Example: • What is the probability that Norway will be member of EU before 2050? • Choose A or B • A: You get NOK 100 000 in 2050 if arrow stops in the green area • B: You get NOK 100 000 in 2050 if Norway is a member Fred Wenstøp: Consistent choice

  13. Probabilistic uncertainty: decision rule 1 • Maximize expected value Fred Wenstøp: Consistent choice

  14. The St. Petersburg Paradox • Daniel Bernoulli 1738 • Suppose you are offered the following lottery • A coin is tossed until tails turn up the first time • If it happens at toss #1, you get kr 2 • If it happens at toss #2, you get kr 4 • If it happens at toss #3, you get kr 8 • etc..... • How much are you willing to pay to participate? Fred Wenstøp: Consistent choice

  15. von Neumann-Morgenstern's axioms for preferential consistency I • Axiom 1. Complete ordering • All prices and lotteries can be ordered by the decision maker according to his preferences • No prices or lotteries can be incomparable • This is an uncontroversial axiom • To be able to speak about decision making, one must be able to decide • However, in practise, many decision maker's try to chicken out Fred Wenstøp: Consistent choice

  16. von Neumann-Morgenstern's axioms for preferential consistency II • Axiom 2: Transitivity • If the decision maker prefers • x to y • and • y to z • He must prefer x to z • Uncontroversial • Does not hold for football teams etc. Fred Wenstøp: Consistent choice

  17. von Neumann-Morgenstern's axioms for preferential consistency III • Axiom 3: Continuity • Suppose that • x is preferred to y • y is preferred to z • You get a choice between • y for certain • or • x with probability p • z with probability 1-p • Then there must exist a value of p which makes you indifferent between the choices • Controversial in many situations where z is very bad • for instance irreversible environmental damages Fred Wenstøp: Consistent choice

  18. von Neumann-Morgenstern's axioms for preferential consistency IV • Axiom 4: Reduction of compound lotteries • The only things that matter for the decision maker are the final prices and their probabilities • Therefore compound lotteries are identical to reduced lotteries • This means that fun of gambling is ruled out • The process whereby we arrive at the final prices is irrelevant Fred Wenstøp: Consistent choice

  19. von Neumann-Morgenstern's axioms for preferential consistency V • Axiom 5: Substitutability • Suppose that you are indifferent between a price b and a lottery c • Then c and b can substitute each other in any compound lottery without affecting its attractiveness • Often violated in practise, because the decision maker tries to avoid regret Fred Wenstøp: Consistent choice

  20. Measuring a utility function • Select the working domain • As narrow as possible, still wide enough to contain all values you might want to analyse • Let the utility of the worst point be 0, and of the best point 1.0 • Offer a choice: • Either a 50/50 lottery between the end points • Or a certain outcome xc • Change xc until it is equivalent to the lottery • Then U(xc)=0.5 • Repeat the process as many times as needed • Use the new xc'sas new end points Fred Wenstøp: Consistent choice

  21. Terminology • Certainty equivalent • Certain price which is equally attractive as a lottery • Risk premium • The difference between the certainty equivalent and the expected price • Risk averse utility functions are concave • Risk prone utility functions are convex • Risk neutral utility functions are linear Fred Wenstøp: Consistent choice

  22. Insurance vs. betting • Insurance companies make their living from people who pay a risk premium to avoid uncertainty • Gambling organisations make their living from people who pay to achieve uncertainty • These are the same people! • How can it be explained? Fred Wenstøp: Consistent choice

  23. Multicriteria decision analysis • Paradigme • To help the decision maker formulate goals, weight them and making them operational • To structure complex decision problems • Paying attention to several objectives at the same time • Main reference • Keeney and Raiffa's "Multi Criteria Decision Making" (MCDM) from 1976 Fred Wenstøp: Consistent choice

  24. The MCDM Method: Problem structuring Fred Wenstøp: Consistent choice

  25. Terminology • Criteria • operationalize the goals (objectives, ends) • Scores • the resulting values of the criteria when a decision is implemented • Weights • express the importance of the criteria and reflect the decision maker's subjective values (preferences) • Goal hierarchy (value tree) • structure of the decision maker's objectives • Option (decision alternative) • an action which influences the scores of the criteria Fred Wenstøp: Consistent choice

  26. Common preference models • w:weights, x: scores, u: utility function • Additive utility function • Multiplicative utility function • Multilinear utility function Fred Wenstøp: Consistent choice

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