(a) Consider the Holt-Laury (H-L) risk elicitation task run in class. Pick some example values for p (such as -1, 0, 0.5, 1 and 2) and calculate the switch point for each that is, the decision at which an EUT decision maker with CRRA utility function, and that p parameter value, switches from choosing option A to choosing option B. [Hint: see the excel spreadsheet on Canvas with the data from the risk elicitation experiments.] See how your switch point compares, then refine your search. Can you 'estimate' a parameter for yourself? (b) Consider the Ink-bomb risk elicitation task run in class, except denote by N the maximum number of boxes that the subject can tick. Assuming a CRRA functional form over money, show that if a subject chooses to tick x boxes their expected utility is:3 = (N~~) EU (x; p) = (x)(1-p) (1 - p) Ignoring the fact that the subject can only choose a discrete number of boxes, use the first order conditions to find the optimal number of boxes, x*, satisfies the following condition: (N-x) p(N-x*) = x* How does the number of marked boxes relate to the value of p? Can you re- arrange this first order condition to 'estimate' a p parameter given the number 3Note, choosing values of 1 or higher will not work here. Any ideas why? 1097 Experimental Economics 4 RGQT: Risk of boxes ticked? Estimate' a p parameter for yourself, given the number of boxes you ticked in the class? (c) How consistent are your choices from the H-L task and the ink bomb task? (d) Given your estimates, how would you be predicted to choose in the GP and EG tasks?