A few minutes ago, Joe Doe learned that his company was having a bad year and thus merit salary…

A few minutes ago, Joe Doe learned that his company was having a bad year and thus merit salary…
  A few minutes ago, Joe Doe learned that his company was having a bad year and thus merit salary increases will be smaller than expected. His division’s budget has been set and so he knows that he will receive a salary increase of $400 over his present salary. Mr. Doe has also been offered a transfer to another division in the company. He is unsure of the salary situation in the other division. However, his best information leads him to conclude that if he took the new job, there is a 60% chance that he would receive a salary increase of $600 over his present salary, and a 40% chance that he would receive only a $150 increase over his present salary. To summarize, Joe Doe can either stick with his current job and get a salary increase of $400, or take a transfer to a new job and get a salary increase of either $600 with a 60% probability, or $150 with a 40% probability. Amount ($X) Value (v($X)) $0 -5 $150 -2.5 $200 -2 $300 0 $350 0.5 $400 1 $600 1.85   Probability (p) Decision Weight (π(p)) 0.0 0.1 0.1 0.13 0.2 0.15 0.3 0.23 0.4 0.31 0.5 0.39 0.6 0.47 0.7 0.55 0.8 0.63 0.9 0.71 1.0 1.0 a. If Joe Doe was risk neutral, had constant marginal utility for money, made his decision using expected utility theory, and only cared about the salary increase from each job, would Joe choose to stay in his current job or take the transfer to the other division? Show your expected utility calculations.       May 05 2022 06:09 PM

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