Question

The Winslow Company is trying to decide whether to build a high priced or moderately priced development. The CEO, has assessed the value of the construction enterprise depends on the short term state of the economy which is classified as strong or weak. He has determined the payoff table as follows:

	Strong	Weak
High Priced	$3,950,000	-$1,400,000
Moderately Priced	$760,000	$133,000

The CEO initially assess the probability of a strong economy to be 0.55.

The CEO is contemplating hiring a consultant firm which would better determine the short state of the economy. Results of the consulting firm analysis would be either favorable or unfavorable to a strong economy.

A) Determine the optimal strategy for CCC using EMV analysis.

B) Determine the optimal strategy if the initial probability of a strong economy is 0.40.

C) Determine the EVSI for initial probability of a strong economy vary from 0.34 to 0.50 in units of 2%.

Answer 1

A) Given, probability of a strong economy to be 0.55. Therefore, probability of a weak economy will be 1-0.55 =0.45

Hence for building high priced development, the expected payoff will be 0.55*($3,950,000) + 0.45*(-$1,400,000)=$1,542,500.

However, for building moderately priced development, the expected payoff will be 0.55*($760,000) + 0.45*($133,000)=$477,850. This is much lower than the expected pay-off for building high-priced development.

Thus, using EMV (Expected Monetary Value) analysis we find that the optimal strategy is to go in favor of high priced development.

B) Calculating in the same way, with initial probability of strong economy as 4.0, will result in expected pay off for high priced development (i.e., $740,000) still better than that for moderately priced development (i.e. $383,800). [Note, this is calculated as before by replacing 0.455 as 0/4 and 0.45 as 0.6]

C) Can be estimated using the formula for Expected Value of Sample Information (EVSI)=EMV'-EMV*, which is the difference in EMV between the alternatives, calculated for prior probability 0.34 and posterior probability 0.50. .